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22 pages, 3794 KiB  
Article
Selection of Support System to Provide Vibration Frequency and Stability of Beam Structure
by Alexander P. Lyapin, Ilya V. Kudryavtsev, Sergey G. Dokshanin, Andrey V. Kolotov and Alexander E. Mityaev
Modelling 2024, 5(4), 1687-1708; https://doi.org/10.3390/modelling5040088 (registering DOI) - 14 Nov 2024
Abstract
The current engineering theories on bending vibrations and the stability of beam structures are based on solving eigenvalue problems through similarly formulated differential equations. Solving the eigenvalue problem for engineering calculations is particularly laborious, especially for non-classical supports, where factors like the stiffness [...] Read more.
The current engineering theories on bending vibrations and the stability of beam structures are based on solving eigenvalue problems through similarly formulated differential equations. Solving the eigenvalue problem for engineering calculations is particularly laborious, especially for non-classical supports, where factors like the stiffness of supports, axial forces, or temperature must be considered. In this case, the solution can be obtained only by numerical methods using specially created programs, which makes it difficult to select supports for a given planar beam structure in engineering practice. This work utilizes established solutions from eigenvalue problems in the theory of vibrations and stability of beams, incorporating factors such as axial forces, temperature, and support stiffness. This combined solution is applicable to beam structures of any type and cross-section, as it is determined solely by the selected support conditions (stiffness) and loading (axial force, temperature). Approximation of eigenvalue problem solutions through continuous functions allows the readers to use them for the analytical solution of the design problem of choosing a support system to ensure the frequency of vibrations and stability of the planar beam structure. At the same time, the known solutions given in the reference books on bending vibrations and stability become their particular solutions. This approach is applicable to solving problems of vibrations and loss of stability of various types (torsional, longitudinal, etc.), and is also applicable in other disciplines where solving problems for eigenvalues is required. Full article
(This article belongs to the Section Modelling in Engineering Structures)
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Figure 1
<p>Bending vibrations of a straight element. (<b>a</b>) Scheme; (<b>b</b>) frequency plot against axial force.</p>
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<p>Straight element stability.</p>
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<p>Graphical representation of support factor functions. (<b>a</b>) Graph <span class="html-italic">α</span><sub>1</sub>(<span class="html-italic">C</span><sub>1</sub>, <span class="html-italic">C</span><sub>2</sub>); (<b>b</b>) graph <span class="html-italic">µ</span><sub>1</sub>(<span class="html-italic">C</span><sub>1</sub>, <span class="html-italic">C</span><sub>2</sub>).</p>
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<p>Bending vibrations of curvilinear element from arc plane. (<b>a</b>) Hinge supports; (<b>b</b>) hinge–fixed supports; (<b>c</b>) fixed–fixed supports.</p>
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<p>Multi-support schemes. (<b>a</b>) Hinge–hinge; (<b>b</b>) fixed–fixed; (<b>c</b>) fixed–hinge.</p>
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<p>Influence of support stiffness on new values of support factors.</p>
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<p>Graphical interpretation of the solution of the resolving equation.</p>
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<p>Vibrations of a straight beam element. (<b>a</b>) Δ<span class="html-italic">T</span> = 90 °C, <span class="html-italic">k</span>* = 0 и N = 6; (<b>b</b>) Δ<span class="html-italic">T</span> = 90 °C, <span class="html-italic">k</span>* = 300 and N = 5.</p>
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<p>Curved beam structure. (<b>a</b>) Initial supports; (<b>b</b>) with intermediate supports.</p>
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<p>Curved beam vibrations. (<b>a</b>) Δ<span class="html-italic">T</span> = 90 °C и C = 1444, N = 7; (<b>b</b>) Δ<span class="html-italic">T</span> = 90 °C, C = 63,518, N = 7.</p>
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<p>Support factor approximation error.</p>
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25 pages, 3635 KiB  
Article
A LabVIEW-Based Generalized Experimental Test Platform for Precision Machining Control Algorithms
by Jian Song, Liangyu Cao, Yiming Wang, Fuzheng Zhang, Yixin Shi, Guina Wang, Xinlin Li and Yiyang Chen
Processes 2024, 12(11), 2542; https://doi.org/10.3390/pr12112542 (registering DOI) - 14 Nov 2024
Abstract
Precision machining technology has received significant attention from researchers and engineers. With the increasing complexity of product designs and continuous advancements in high-tech industries, the precision requirements for manufacturing are constantly escalating. For researchers who are new to precision machining, conducting experiments directly [...] Read more.
Precision machining technology has received significant attention from researchers and engineers. With the increasing complexity of product designs and continuous advancements in high-tech industries, the precision requirements for manufacturing are constantly escalating. For researchers who are new to precision machining, conducting experiments directly on commercial equipment is resource-intensive and does not accommodate diverse working scenarios. Therefore, designing a generalized precision machining experimental test platform is particularly important. This paper presents a practical plan to construct such a platform, integrating key components such as a gantry-type Cartesian coordinate robot, a 2D rotary table, a 2D precision slide stage, a galvanometer, and a telecentric lens. The platform serves as a test environment for verifying the feasibility of various precision machining control algorithms. It not only demonstrates the desired stability and scalability but also offers a user-friendly operational interface via the LabVIEW front panel. This facilitates simple and efficient experimental operations, providing an effective and reliable environment for testing precision machining control algorithms. Full article
(This article belongs to the Section Process Control and Monitoring)
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<p>An overview of precision machining experimental platform.</p>
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<p>Comparison of the optical path principle between: (<b>a</b>) normal lens and (<b>b</b>) telecentric lens.</p>
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<p>A schematic diagram of laser galvanometer projection.</p>
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<p>LabVIEW-based front panel of the camera-positioning program.</p>
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<p>LabVIEW back panel of the camera-positioning program.</p>
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<p>LabVIEW calls MATLAB scripts to control the gantry robot.</p>
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<p>Gantry-type rectangular coordinate robot LabVIEW operation panel.</p>
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<p>Flowchart of LabVIEW calling DLL library to control laser galvanometer.</p>
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<p>The LabVIEW front panel for the laser galvanometer.</p>
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<p>LabVIEW control commands for the 2D rotary table.</p>
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<p>LabVIEW front panel for 2D slide motion control.</p>
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<p>LabVIEW integrated control front panel.</p>
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<p>Visualization of positioning information.</p>
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<p>Segmentation results based on industrial production images.</p>
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<p>Segmentation results based on industrial production images using the telecentric lens.</p>
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<p>Relative paths between the galvanometer and rotary table.</p>
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<p>Relative paths between the galvanometer and slide table.</p>
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<p>The paths of galvanometer system for the 10th, 20th, 30th, and final trials.</p>
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<p>The paths of rotary table system for the 1st, 2nd, 3rd, and final trials.</p>
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<p>The paths of slide table system for the 1st, 2nd, 3rd, and final trials.</p>
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<p>Some more complex flower-like patterns.</p>
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<p>Performance of the experimental test platform.</p>
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17 pages, 7989 KiB  
Article
Numerical Investigation of Network-Based Shock Wave Propagation of Designated Methane Explosion Source in Subsurface Mine Ventilation System Using 1D FDM Code
by Sisi Que, Jiaqin Zeng and Liang Wang
Sustainability 2024, 16(22), 9935; https://doi.org/10.3390/su16229935 (registering DOI) - 14 Nov 2024
Abstract
In coal mining operations, methane explosions constitute a severe safety risk, endangering miners’ lives and causing substantial economic losses, which, in turn, weaken the production efficiency and economic benefits of the mining industry and hinder the sustainable development of the industry. To address [...] Read more.
In coal mining operations, methane explosions constitute a severe safety risk, endangering miners’ lives and causing substantial economic losses, which, in turn, weaken the production efficiency and economic benefits of the mining industry and hinder the sustainable development of the industry. To address this challenge, this article explores the application of decoupling network-based methods in methane explosion simulation, aiming to optimize underground mine ventilation system design through scientific means and enhance safety protection for miners. We used the one-dimensional finite difference method (FDM) software Flowmaster to simulate the propagation process of shock waves from a gas explosion source in complex underground tunnel networks, covering a wide range of scenarios from laboratory-scale parallel network samples to full-scale experimental mine settings. During the simulation, we traced the pressure loss in the propagation of the shock wave in detail, taking into account the effects of pipeline friction, shock losses caused by bends and obstacles, T-joint branching connections, and cross-sectional changes. The results of these two case studies were presented, leading to the following insights: (1) geometric variations within airway networks exert a relatively minor influence on overpressure; (2) the positioning of the vent positively contributes to attenuation effects; (3) rarefaction waves propagate over greater distances than compression waves; and (4) oscillatory phenomena were detected in the conduits connecting to the surface. This research introduces a computationally efficient method for predicting methane explosions in complex underground ventilation networks, offering reasonable engineering accuracy. These research results provide valuable references for the safe design of underground mine ventilation systems, which can help to create a safer and more efficient mining environment and effectively protect the lives of miners. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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<p>(<b>a</b>) Top view of the Parallel Sample Network schematic. (<b>b</b>) Geometric model for Flowmaster of the Sample Parallel Network from the top view.</p>
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<p>Overpressure history in the case of 8% volumetric concentration methane explosion in the airway with dimensions of both width and height of 0.08 m and 4.25 m in length.</p>
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<p>Surface of pressure, time, and pipe length plots for (<b>a</b>) C17, (<b>b</b>) C2, (<b>c</b>) C5, (<b>d</b>) C8, (<b>e</b>) C9, (<b>f</b>) C4, (<b>g</b>) C13, and (<b>h</b>) C14.</p>
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<p>Surface of pressure, time, and pipe length plots for (<b>a</b>) C17, (<b>b</b>) C2, (<b>c</b>) C5, (<b>d</b>) C8, (<b>e</b>) C9, (<b>f</b>) C4, (<b>g</b>) C13, and (<b>h</b>) C14.</p>
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<p>Pressure distribution in pipe components at 0.065 s (in bar).</p>
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<p>Illustration depicting underground airways at the main experimental mine, Missouri S&amp;T, Rolla, MO.</p>
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<p>Geometric model experimental mine used in Flowmaster.</p>
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<p>Surface of temporal dimensions, pressure, and length plots of (<b>a</b>) C59 (region 1), (<b>b</b>) C9 (region 2), (<b>c</b>) C24 (region 3), (<b>d</b>) C11 (region 4), (<b>e</b>) C31 (region 5), (<b>f</b>) C29 (region 6), (<b>g</b>) C43 (region 7), (<b>h</b>) C50 (region 8), (<b>i</b>) C53 (shaft 1), and (<b>j</b>) C2 (portal 2).</p>
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<p>Surface of temporal dimensions, pressure, and length plots of (<b>a</b>) C59 (region 1), (<b>b</b>) C9 (region 2), (<b>c</b>) C24 (region 3), (<b>d</b>) C11 (region 4), (<b>e</b>) C31 (region 5), (<b>f</b>) C29 (region 6), (<b>g</b>) C43 (region 7), (<b>h</b>) C50 (region 8), (<b>i</b>) C53 (shaft 1), and (<b>j</b>) C2 (portal 2).</p>
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<p>The distribution of pressure in the airway network at (<b>a</b>) 0.039 s for regions 7 and 8, (<b>b</b>) 0.195 s for regions 7 and 8, (<b>c</b>) 0.039 s for regions 1 to 6, and (<b>d</b>) 0.195 s for regions 1 to 6 of the experimental mine (in bar).</p>
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20 pages, 8912 KiB  
Article
Test Results and Considerations for Design Improvements of L-CADEL v.3 Elbow-Assisting Device
by Marco Ceccarelli, Sergei Kotov, Earnest Ofonaike and Matteo Russo
Machines 2024, 12(11), 808; https://doi.org/10.3390/machines12110808 (registering DOI) - 14 Nov 2024
Abstract
The elbow-assisting device, L-CADEL, was analyzed by testing a prototype of design version three (v3) with the aim of discussing design improvements to solve problems and improve operational performance. The test results reported are from a lab testing campaign with 15 student volunteers [...] Read more.
The elbow-assisting device, L-CADEL, was analyzed by testing a prototype of design version three (v3) with the aim of discussing design improvements to solve problems and improve operational performance. The test results reported are from a lab testing campaign with 15 student volunteers from the engineering and physiotherapy disciplines. The main aspects of attention of the reported investigation are data analyses for motion diagnostics, comfort in wearing, operation efficiency, and the mechanical design of the arm platform and cable tensioning. Full article
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<p>The main requirements for design issues in a motion-assisting device for the elbow.</p>
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<p>Design of L-CADEL v.3 prototype: (<b>a</b>) conceptual design and (<b>b</b>) prototype installed on a user’s arm.</p>
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<p>Design of L-CADEL v.3 prototype: (<b>a</b>) block diagram and (<b>b</b>) electric circuit design.</p>
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<p>Arm ring platform of L-CADEL v.3 prototype: (<b>a</b>) a CAD model and (<b>b</b>) the built prototype installed on a user’s arm. (1 is the button for changing the motor’s rotation).</p>
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<p>Arm ring platform of L-CADEL v.3 prototype: (<b>a</b>) Conceptual design and (<b>b</b>) electric circuit design.</p>
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<p>Wrist ring platform of L-CADEL v.3 prototype: (<b>a</b>) a CAD model with sizes in mm and (<b>b</b>) the built prototype installed on a user’s wrist. (1 is an IMU sensor; 2 is a cable connection hook).</p>
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<p>EMG sensor of L-CADEL v.3 prototype: (<b>a</b>) EMG electrodes installed on the arm and (<b>b</b>) electric circuit design.</p>
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<p>The third platform for control unit and acquisition and elaboration data of L-CADEL v.3 prototype: (<b>a</b>) block diagram and (<b>b</b>) electric circuit design.</p>
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<p>Testing layout with L-CADEL v.3 prototype: (<b>a</b>) conceptual design and (<b>b</b>) a lab setup.</p>
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<p>A snapshot of a test with the L-CADEL.v3 prototype setup. (<b>a</b>) Starting configuration; (<b>b</b>) intermediate configuiration; (<b>c</b>) final arm flexed configuration.</p>
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<p>Acquired data during a test with L-CADEL.v3 prototype, as in <a href="#machines-12-00808-f010" class="html-fig">Figure 10</a>, in terms of the acceleration components Ax, Ay, Az, and module.</p>
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<p>Acquired data during a test with L-CADEL.v3 prototype, as in <a href="#machines-12-00808-f010" class="html-fig">Figure 10</a>, in terms of the pitch, roll, and yaw angles.</p>
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<p>Acquired data during a test with L-CADEL.v3 prototype, as in <a href="#machines-12-00808-f010" class="html-fig">Figure 10</a>, in terms of power consumption.</p>
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<p>Acquired data during a test with L-CADEL.v3 prototype, as in <a href="#machines-12-00808-f010" class="html-fig">Figure 10</a>, in terms of the EMG response.</p>
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<p>Schemes with aspects of attention for a new L-CADEL v.4 prototype: (<b>a</b>) arm ring platform and (<b>b</b>) wrist ring platform.</p>
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26 pages, 6966 KiB  
Article
Computational Evidence for Bisartan Arginine Blockers as Next-Generation Pan-Antiviral Therapeutics Targeting SARS-CoV-2, Influenza, and Respiratory Syncytial Viruses
by Harry Ridgway, Vasso Apostolopoulos, Graham J. Moore, Laura Kate Gadanec, Anthony Zulli, Jordan Swiderski, Sotirios Tsiodras, Konstantinos Kelaidonis, Christos T. Chasapis and John M. Matsoukas
Viruses 2024, 16(11), 1776; https://doi.org/10.3390/v16111776 (registering DOI) - 14 Nov 2024
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus (RSV) are significant global health threats. The need for low-cost, easily synthesized oral drugs for rapid deployment during outbreaks is crucial. Broad-spectrum therapeutics, or pan-antivirals, are designed to target multiple viral [...] Read more.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus (RSV) are significant global health threats. The need for low-cost, easily synthesized oral drugs for rapid deployment during outbreaks is crucial. Broad-spectrum therapeutics, or pan-antivirals, are designed to target multiple viral pathogens simultaneously by focusing on shared molecular features, such as common metal cofactors or conserved residues in viral catalytic domains. This study introduces a new generation of potent sartans, known as bisartans, engineered in our laboratories with negative charges from carboxylate or tetrazolate groups. These anionic tetrazoles interact strongly with cationic arginine residues or metal cations (e.g., Zn2+) within viral and host target sites, including the SARS-CoV-2 ACE2 receptor, influenza H1N1 neuraminidases, and the RSV fusion protein. Using virtual ligand docking and molecular dynamics, we investigated how bisartans and their analogs bind to these viral receptors, potentially blocking infection through a pan-antiviral mechanism. Bisartan, ACC519TT, demonstrated stable and high-affinity docking to key catalytic domains of the SARS-CoV-2 NSP3, H1N1 neuraminidase, and RSV fusion protein, outperforming FDA-approved drugs like Paxlovid and oseltamivir. It also showed strong binding to the arginine-rich furin cleavage sites S1/S2 and S2′, suggesting interference with SARS-CoV-2’s spike protein cleavage. The results highlight the potential of tetrazole-based bisartans as promising candidates for developing broad-spectrum antiviral therapies. Full article
(This article belongs to the Special Issue Molecular Epidemiology of SARS-CoV-2, 3rd Edition)
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<p>Docking of experimental sartans (e.g., ACC519TT, Cpd13, BisA, etc.), FDA-approved sartans (e.g., candesartan, olmesartan, losartan, etc.), and known inhibitors (e.g., R1104 and R7335) of the SARS-CoV-2 NSP3 Mac1 domain. (<b>A</b>) Overview of the docking setup showing the X-ray crystallographic structure for the SARS-CoV-2 Mac1 domain, PDB 6YWL, rendered as gray ribbons, and the water-accessible surface (blue shading) with its bound native ligand, ADPR (yellow atoms as spheres). The docking region of interest in which energy grids were constructed is indicated by the walled “periodic” box with colored lines of dimensions (x/red = 26 Å, y/green = 22 Å, and z/blue = 20 Å). (<b>B</b>) Docking results for 27 selected ligands targeting the NSP3 Mac1 domain of SARS-CoV-2. Docking was carried out against two PDB crystallographic structures: 6YWL (blue bars) and 7KQP (light green bars). Ligand docking was performed using AutoDock VINA with AMBER14 force field point charges and dihedral barriers (900 runs per ligand). Docking results are expressed as ligand binding energies (kcal/mol) and calculated dissociation constants (Log10Kd in pM units). Of the 27 docked ligands, Cpd13, a di-phenylcyano-derivative of the anionic bisartan ACC519TT, exhibited the strongest Mac1 binding at 11.45 and 12.41 kcal/mol for the 6YWL and 7KQP Mac1 receptors, respectively. Compared to ACC519TT binding (10.59 and 11.84 kcal/mol, respectively, for binding to the 6YWL and 7KQP receptors), ADPR, which is the native ligand for the Mac1 domain, exhibited somewhat weaker binding (10.32 and 10.07 kcal/mol, respectively, for 6YWL and 7KQP). Surprisingly, compounds R1104 and R7335, which are experimentally proven inhibitors of the NSP3 Mac1 domain [<a href="#B52-viruses-16-01776" class="html-bibr">52</a>], exhibited poor binding energies compared to nearly all the FDA-approved and experimental sartans. (<b>C</b>) Structures of ADPR, the di-phenylcyano-(bisartan)-derivative Cpd13, and bisartan ACC519TT. Chemical key: H, hydrogen; N, nitrogen; O, oxygen; P, phosphorus. (<b>D</b>) Docking validation for ADPR: Docked ADPR pose (green C atoms as spheres) in the Mac1 receptor superimposed onto the 6YWL X-ray structure with bound ADPR (cyan C atoms as spheres). RMSD for the superimposed protein-ligand complexes was ≤ 0.0001 Å. These data indicate that AutoDock VINA was able to accurately calculate the correct X-ray pose for this complex ligand. ADPR was stabilized in the Mac1 domain by approximately six hydrogen bonds (thick yellow dashed lines), as well as pi–pi (red lines) and hydrophobic interactions (green lines). (<b>E</b>) Binding mechanism of Cpd13 (di-phenylcyano-derivative of ACC519TT) in the NSP3 Mac1 domain. The docked ligand was stabilized mainly by ionic pi–cation interactions (thin red lines) between one of the terminal phenylcyano groups and Mac1 residue Phe132. The other phenylcyano group entered hydrophobic interactions (thin green lines) with Phe156 and Ala52. Phe156 also was bonded to the phenyl group adjacent to the benzimidazole group of Cpd13 by pi–cation interactions (thin red or magenta lines). (<b>F</b>) Binding of ACC519TT (yellow C atoms rendered as tubes) in the Mac1 pocket involved numerous hydrophobic interactions (green lines) between the phenyl groups of ACC519TT and residues Ala52, Ile131, Ala129, Pro136, Leu160, Leu126, Val155, Val49, Ile23, and Phe156. Additional pi–pi interactions (red line) were observed between Phe156 and one of the phenyl groups of ACC519TT. Abbreviations: ACC519TT, benzimidazole bis-N,N’-biphenyltetrazole; ACC519T[1], benzimidazole-N-biphenyltetrazole; ADPR, adenosine 5′-diphosphoribose; Ala, alanine; AMBER, Another Model Building Energy Refinement; Asn, asparagine; Asp, aspartic acid; Azil, azilsartan; Bis, bisartan; Cande, candesartan; Epro, eprosartan; EXP3174, Gly, glycine; Irbe, irbesartan; Ile, isoleucine; Leu, leucine; Lo, losartan; Mac1- macrodomain-1; NSP3, non-structural protein 3; Olme, olmesartan; PDB, Protein Data Bank; Phe, phenylalanine; Pro, proline; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Ser, serine; Telm, telmisartan; Val, valine; Å, angstrom.</p>
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<p>Docking of selected ligands to the SARS-CoV-2 NSP3 PLpro (PDB: 7LBR and 7JRN). Experimentally proven drugs investigated include PLpro inhibitors (i.e., XR8-89 [<a href="#B56-viruses-16-01776" class="html-bibr">56</a>]; GRL0617, Jun9-72-2, and Jun9-74-4 [<a href="#B14-viruses-16-01776" class="html-bibr">14</a>]). <b>Upper panel</b>, (<b>A</b>): The 7LBR PLpro domain X-ray crystallographic structure (blue ribbons) superimposed onto PLpro 7JRN (maroon ribbons). Overall RMSD for aligned structures = 0.478 Å. Approximate boundaries of the docking region, which contained the catalytic Cys11 residue, are indicated by the gray rectangle. The 2-phenylthiophene-based inhibitor “7LBRLignd” (XR8-89) [<a href="#B56-viruses-16-01776" class="html-bibr">56</a>] bound in the “BL2” groove proximal to the catalytic site is also indicated (cyan atoms). The 7LBR structure has been rendered as the Van der Waals surface (yellow shading). <b>Upper panel</b>, (<b>B</b>): Docked bisartan ACC519TT (dusty blue carbon atoms) superimposed on the docked PLpro inhibitor XR8-89 (maroon carbon atoms) for the 7LBR receptor. ACC519TT adopted a conformation along the BL2 groove that was similar to XR8-89 (molecule pair RMSD = 9.49 Å), with both ligands sharing a number of close contacts with 7LB6 residues, including Leu162, Tyr273, Tyr264, Pro299, Tyr268, and Gln269. Non-bond drug–receptor interactions included hydrophobic (green lines), pi–pi resonance (red lines), cation–pi (blue to light-blue lines), and hydrogen bonds (dashed yellow lines). Locations of the dual anionic tetrazole groups are labeled in blue as Tet#1 and Tet#2. <b>Upper panel</b>, (<b>C</b>): The bisartan tetrazole functionalities appeared bioisosteric with the terminal aminocyclobutane and cyclopentane groups of XR8-89. A similar relationship was observed for the central benzimidazole group of ACC519TT that overlapped the central benzene ring of XR8-89. <b>Lower panel</b>, (<b>D</b>): Docking results expressed as ligand binding energies in kcal/mol. Log<sub>10</sub>Kd values in pM units were computed from the binding energies [<a href="#B32-viruses-16-01776" class="html-bibr">32</a>]: color key: blue bars = docking to the PLpro domain of PDB 7LBR and green bars = docking to the PLpro domain of PDB 7JRN. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; ACC519T[1], benzimidazole-<span class="html-italic">N</span>-biphenyltetrazole; Azil, azilsartan; Bis, bisartan; Cande, candesartan; cpd, compound; DIZE, diminazene aceturate; Epro, eprosartan; Gln, glutamine; Gly, glycine; Irbe, irbesartan; Leu, leucine; Lo, losartan; Mac1, macrodomain-1; Met, methionine; Nirmat, nirmatrelvir; NSP3, non-structural protein 3; Olme, olmesartan; PLpro, papain-like protease; Pro, proline; RMSD, root-mean-standard deviation; RSV, respiratory syncytial virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Tyr, tyrosine; XR8-89, 7:BR-Ligand; Å, Angstrom.</p>
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<p>(<b>A</b>) Docking results of selected ligands targeting the RSV F-postfusion (i.e., drug-induced) protein that mediates virus entry into host cells. In its native (host-free) state, the homotrimeric F-protein exists in a metastable “prefusigenic or prefusion” conformation and must undergo a structural rearrangement that facilitates membrane fusion [<a href="#B61-viruses-16-01776" class="html-bibr">61</a>]. Ligands were docked into the three-fold symmetric domain (3FSD) of the virion F-protein (PDB 5EA4) located in the upper (surface) central cavity where the three chains intersect, denoted in the side-view projection by the red square in (<b>B</b>). Induced-fit binding of the potent RSV F-protein inhibitor JNJ-49153390 within the 3FSD interlocks two of the protomers in the pocket, effectively stabilizing the prefusion conformation and preventing host cell fusion and infection. Docking results indicated the bisartan ACC519TT bound significantly more strongly (12.53 kcal/mol) into the 3FSD pocket compared to all other drugs tested. The binding energy of JNJ-49153390 (8.28 kcal/mol), as well as those of two other structurally similar experimentally proven F-protein inhibitors (i.e., cpd2-5EA4 and cpd44-5EA4) were substantially lower. (<b>C</b>) Structure of 5EA4 with docked ACC519TT (in the drug-bound postfusogenic conformation) showing the three color-coded protomers (Key: yellow = Chain-A; magenta = Chain-B; gray = Chain-C) in the down-axis view rotated 90° from the side view in B. (<b>D</b>) Magnified down-axis view from C showing binding mechanism of ACC519TT involving a putative tethering of all three protomers by interactions with symmetrically arranged 5EA4 residues Phe488 and Phe140 (in each chain). Unlike the binding of JNJ-49153390, ACC519TT binding also involved strong electrostatic (salt bridge/pi–cation) interactions (blue lines) of the tetrazole#2 (Tet#2) functional group with a deeply buried Arg339 residue in Chain-B. The tetrazole#1 (Tet#1) group of ACC519TT was effectively coordinated by two of the symmetrically arranged phenylalanine residues (Phe488-A and Phe488-C) through pi–pi resonance bonding (red lines). This type of dual protomer binding by ACC519TT was similar to that reported by Battles and coworkers [<a href="#B61-viruses-16-01776" class="html-bibr">61</a>] regarding JNJ-49153390. Finally, additional hydrophobic interactions (green lines) between Phe140-C and one of the phenyl groups proximal to Tet#1 and adjacent to the central benzimidazole moiety also contributed to ACC519TT stability in the 3FSD pocket. (<b>E</b>) Side-view image rotated 90° from D showing docked ACC519TT (yellow C atoms) superimposed onto the X-ray crystallographic pose of the F-protein antagonist JNJ-41953390 (magenta C atoms). This view illustrates more clearly the interaction of Tet#2 with the buried Arg339 residue of Chain-B through ionic (blue lines) and hydrogen bonding (thick dashed yellow line). (<b>F</b>) Chemical structures of the six ligands evaluated. Chemical key: O. oxygen; S, sulfur; Br, bromine; N, nitrogen. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; ACC519T[1], benzimidazole-<span class="html-italic">N</span>-biphenyltetrazole; Asp, aspartic acid; Arg, arginine; cpd, compound; F-protein, fusion protein; PDB, Protein Data Bank; Phe, phenylalanine; RSV, respiratory syncytial virus; S, sulfur; Tet, tetrazole; JNJ49153390, 5EA4-Ligand; 3FSD, 3-fold-symmetric domain.</p>
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<p>Binding of bisartan ACC519TT to the furin cleavage sites of the SARS-CoV-2 spike (S) protein. (<b>A</b>) Full-sequence homology model (Swiss Model 05) of the SARS-CoV-2 spike protein showing locations of the S’ and S1/S2 FCSs. The three homotrimeric chains are color coded: Chain-A = yellow with Van der Waals surface (yellow shading); Chain-B = green; Chain-C = blue. The model is rotated so that the S2′ FCS of Chain-A with docked bisartan ACC519TT (cyan carbon atoms) is shown located in the center of the model. (<b>B</b>) Docked pose of bisartan ACC519TT in the S1/S2 spike FCS consensus loop region showing the interaction of tetrazole#1 (Tet#1) with Arg685. (<b>C</b>) ACC519TT conformation following 90 ns of an NPT MD simulation at 311 °K, 0.9%wt/vol saline with periodic boundaries (see Methods) of an isolated model “fragment” of the S1/S2 FCS binding domain depicted in (<b>E</b>). Water and NaCl ions have been hidden for clarity. The four terminal fragment residues of the FCS model in (<b>E</b>) were capped and frozen during the MD simulation. Analysis of the MD trajectory indicated the total system energy was essentially equilibrated throughout the simulation (blue line in (<b>F</b>)). Despite the significant thermal motion of the FCS model (RMSD ranged from about 1 to 4 Å), the bisartan remained stably bound for the 90 ns duration of the MD simulation (drug RMSD ranged from about 1 to 5 Å). The comparison of the initial docked drug pose in (<b>B</b>) with that following the MD simulation (<b>C</b>) revealed that the bound ligand re-oriented, abandoning its initial Tet#1 interaction with Arg685 and establishing new stabilizing interactions with Arg residues 682 and 683 via ionic pi–cation bonding mechanisms (blue lines). Additional drug–receptor bond types included hydrophobic (green lines) and pi–pi (red lines) interactions. (<b>D</b>) Magnified view of the conformational pose of bisartan ACC519TT in the S2′ FCS pocket following VINA docking (see Methods). Details of the ligand–receptor interactions in the S2′ site are shown to the right (blue arrow). Color key: thin colored lines = primary intermolecular interactions; green = hydrophobic interactions; red = pi–pi; magenta = ionic; blue = pi–cation. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; Ala, alanine; Arg, arginine; Cys, cysteine; FCS, furin cleavage site; Ile, isoleucine; Gln, glutamine; Glu, glutamic acid; Gly, glycine; His, histidine; Leu, leucine; Lys, lysine; Phe, phenylalanine; Pro, proline; RMSD, root-mean-standard deviation; S, subunit; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Ser, serine; Tet, tetrazole; Thr, threonine; Tyr, tyrosine.</p>
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<p>Docking of three FDA-approved drugs (orange borders), experimental drugs (purple borders), theoretical tri-tetrazole compounds (green borders), and our imidazole-biphenyltetrazole, ACC519TT (black border) to five influenza neuraminidases from the PDB. The four-letter name prefixes indicate the PDB complex from which the ligand was extracted prior to docking to the Arg-rich catalytic pocket of the apo-receptor. The number of AutoDock VINA runs per ligand ranged from 100 to 300 using AMBER14 charges and parameters. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; AMBER, Another Model Building Energy Refinement; Arg, arginine; PDB, Protein Data Bank. Chemical key: H, hydrogen; N, nitrogen; O, oxygen; S, sulfur.</p>
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<p>Mechanism of bisartan ACC519TT interactions with residues comprising the different neuraminidase catalytic domains. In four of the five neuraminidase models (i.e., 2HTQ, 6BR6, 6HP0, and 2HTU) both anionic tetrazole groups of the bisartan formed strong salt bridges (blue lines = cation–pi interactions) with two or more cationic arginine residues (carbon represented by yellow spheres). In the case of 2HU0, only one of the terminal tetrazole groups formed bonds with arginine residues (R371 and R118). The other tetrazole group formed pi–pi (red lines) and hydrophobic (green lines) interactions with Tyr347. In all the cases, the ligand displayed a “wrapped” conformation in which the tetrazole moieties were docked into positions relatively close to one another. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; Ala, alanine; Arg, arginine; Asn, asparagine; Asp, aspartate; Glu, glutamic acid; Ile, isoleucine; Lys, lysine; Pro, proline; Ser, serine; Thr, threonine; Trp, tryptophan; Tyr, tyrosine; Val, valine.</p>
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<p>Equilibrium MD of ACC519TT docked in the neuraminidase 6BR6 catalytic site (NVT ensemble, 311 °K, 0.9 wt/% NaCl, pH 7.4). (<b>A</b>) Cuboid periodic cell with boundaries = 8.0 Å from any protein atom (Na and Cl atoms are shown as yellow and green balls in solution). (<b>B</b>) Docked ACC519TT (gray carbon atoms) at t = 0 ns showing main interactions with 6BR6 receptor (Key: green lines = hydrophobic; blue lines = salt bridge [cation–pi]; and red lines = pi–pi). (<b>C</b>) <b>Upper panel:</b> Ligand binding energy in kcal/mol (blue line); note that higher values = stronger binding to the receptor. Orange line = overall system potential energy. <b>Middle panel:</b> Frame captures of the ligand–receptor complex at designated intervals (ns). <b>Lower panel:</b> Ligand radius of gyration, RMSD (blue and orange lines, respectively), and receptor RMSD (gray line). The ligand remained stably bound in the pocket for the duration of the 36 ns run simulation. This stability was reflected in the relatively consistent ligand–receptor binding energy (blue line, upper panel). Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; Arg, arginine; Asp, aspartic acid; Glu, glutamic acid; His, histidine; Lys, lysine; MD, molecular dynamics; RMSD, root-mean-standard deviation; Tyr, tyrosine; Val, valine; Å, angstrom.</p>
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<p>(<b>A</b>) Minimum-energy ACC519TT–neuraminidase complex (at about 10.5 ns) extracted from the 36 ns MD trajectory of 6BR6. Blue transparent shading corresponds to the 6BR6 water-accessible surface. (<b>B</b>) The anionic tetrazole groups form stable salt-bridge (cation–pi) interactions (blue lines) involving R118, R292, and R371. These are the same three Arg residues that were involved in bonding with the dual anionic tetrazole groups of ACC519TT in the original docked configuration at t = 0 ns. Abbreviations: ACC519TT, benzimidazole <span class="html-italic">bis</span>-<span class="html-italic">N,N′</span>-biphenyltetrazole; Arg, arginine; Glu, glutamic acid; Ile, isoleucine; His, histidine; Lys, lysine; MD, molecular dynamics; Thr, threonine; Tyr, tyrosine; Val, valine.</p>
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<p>Re-docking of extracted native ligands into the catalytic pocket of the five neuraminidase models evaluated. In each case, the X-ray crystallographic structure (dusty blue carbon atoms) was superimposed against the docked complex (maroon carbon atoms) before calculating the RMSD values for the superimposed ligands. Docking to 6HP0 (RMSD = 2.7141 Å) and 2HTQ (RMSD = 0.9092 Å) yielded the best fit with their respective X-ray conformations, whereas poorer-quality fits were observed for PDB 2HU0 (RMSD = 3.2189 Å), 6BR6 (RMSD = 5.0573 Å), and 2HTU (RMSD = 4.7050 Ang). Abbreviations: Ala, alanine; Arg, arginine; Asn, asparagine; Asp, aspartic acid; His, histidine; Ile, isoleucine; Glu, glutamic acid; PDB, Protein Data Bank; RMSD, root-mean-square deviation; Ser, serine, Trp, tryptophan, Tyr, tyrosine; Å, angstrom.</p>
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<p>Docking data comparing VINA binding energies and per-atom efficiencies for 10 drugs against three different neuraminidase receptors: neuraminidase in complex with sialic acid, its single mutant 1×Mut (R153A), and the triple mutant 3×Mut (R153A-R294A-R372A).</p>
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19 pages, 8484 KiB  
Article
A Spatial 4-DOF Laser Collimation Measurement System
by Han Jiang, Ke Zhang, Lufeng Ji, Ruiyu Zhang and Changpei Han
Appl. Sci. 2024, 14(22), 10491; https://doi.org/10.3390/app142210491 (registering DOI) - 14 Nov 2024
Viewed by 32
Abstract
A compact and miniaturized laser collimation system was proposed to measure the four-degrees-of-freedom of an optical payload in high-altitude space. Compared with other systems, this system has a simple structure and low cost, high measurement accuracy, and a large measurement range. The optical [...] Read more.
A compact and miniaturized laser collimation system was proposed to measure the four-degrees-of-freedom of an optical payload in high-altitude space. Compared with other systems, this system has a simple structure and low cost, high measurement accuracy, and a large measurement range. The optical structure of the system was designed, the measurement principle of the four-degree-of-freedom was described in detail, the interference between the distance measurement and the angle measurement in the optical path was analyzed, and the installation error was analyzed. The error was minimized under different temperature conditions to improve the robustness of the system. An engineering prototype was built based on the system design scheme and an experiment was conducted to measure a target with a measured distance of 500 mm. The current indicators reached the requirements for the ground testing of optical payloads. The application of the system can be used to measure six degrees of freedom simultaneously by installing two systems in different coordinate systems. The system can also be used in industry; for example, by measuring the machine tool error in real time and compensating for it, the system can improve the positioning and motion accuracy. It can also be used for feedback control of the robot’s motion by measuring and controlling it. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
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<p>Optical schematic diagram of the system.</p>
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<p>X/Y direction straightness ranging optical path.</p>
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<p>X/Y direction ranging optical path.</p>
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<p>Principal diagram of ranging light path.</p>
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<p>The pitch angle in the X direction and yaw angle in the Y direction, which are used to measure the optical path.</p>
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<p>Principal diagram of angle measurement light path.</p>
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<p>System coordinates.</p>
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<p>The angular cone prism, rotated around edge angle O.</p>
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<p>The corner cone prism rotates around the non-edge O point.</p>
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<p>CMOS installation error model.</p>
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<p>Influence of CMOS translation installation error on the <span class="html-italic">X</span>-axis.</p>
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<p>Neuronal structural model.</p>
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<p>BP neural network temperature compensation model’s structure.</p>
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<p>Four-degrees-of-freedom measuring system test device.</p>
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<p>PI Company’s H-825 displacement table.</p>
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<p>Calibration experiments: (<b>a</b>) X straightness calibration curve; (<b>b</b>) Y straightness calibration curve; (<b>c</b>) calibration curve of pitch in the X direction; (<b>d</b>) calibration curve of yaw in the Y direction.</p>
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<p>Results of the stability experiments: (<b>a</b>) X straightness SD = 1.11 μm; (<b>b</b>) Y straightness; (<b>c</b>) pitch SD = 0.91 arcsec; (<b>d</b>) yaw SD = 0.90 arcsec.</p>
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<p>Article’s technical route.</p>
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14 pages, 8154 KiB  
Article
Research on the 3D Visualization Method of Web-Based Seismic Wave CT Results and the Application in Underground Caverns
by Tianwen Li and Jieyun Xing
Buildings 2024, 14(11), 3622; https://doi.org/10.3390/buildings14113622 (registering DOI) - 14 Nov 2024
Viewed by 66
Abstract
This paper introduces a novel 3D visualization technique for seismic tomography results utilizing WebGL technology, which operates independently of specific software platforms and offers highly efficient visualization. The method constructs the mesh using wave velocity as a reference point, applies vertex and surface [...] Read more.
This paper introduces a novel 3D visualization technique for seismic tomography results utilizing WebGL technology, which operates independently of specific software platforms and offers highly efficient visualization. The method constructs the mesh using wave velocity as a reference point, applies vertex and surface coloring techniques to the model, and integrates CT detection data, resulting in a detailed color rendering and a clear visual representation of the model. The visualization outcomes are presented on an intelligent construction platform with a response time maintained within 2 s. To validate the efficacy of the proposed method, it was applied to the underground cavern project of a hydropower station and compared with the geological 3D design software developed independently by the Northwest China Institute of Architectural Engineering. The comparative results demonstrate that the proposed visualization technique effectively identifies weak geological layers and displays the distribution of surrounding rock types in underground structures. This provides intuitive references for devising support schemes for underground structures and facilitates digital management during project construction. Full article
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<p>Schematic diagram of reference points.</p>
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<p>Visualized results of web-based CT seismic wave.</p>
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<p>Three-dimensional wave velocity visualization results of underground cavern based on WebGL technology.</p>
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<p>Three-dimensional wave velocity visualization results of underground cavern based on software.</p>
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<p>Cubic mesh surrounding the underground chamber. (The blue lines in <a href="#buildings-14-03622-f005" class="html-fig">Figure 5</a> and <a href="#buildings-14-03622-f006" class="html-fig">Figure 6</a> represent boreholes and flat holes).</p>
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<p>Spatial data of cubic network created and interpolated based on assigned data.</p>
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<p>The geophysical wave velocity data of the cubic network is assigned to the underground engineering surface model.</p>
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<p>Surrounding rock quality classification model obtained by assigning cubic network data to the underground engineering model.</p>
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24 pages, 9054 KiB  
Article
Investigation of a Modular High-Pressure Heat Exchanger with Metal Foam Packing for a Pneumatic–Hydraulic Drive
by Roman Dyga and Sebastian Brol
Materials 2024, 17(22), 5557; https://doi.org/10.3390/ma17225557 (registering DOI) - 14 Nov 2024
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Abstract
The results of the first stage of work aimed at improving a hybrid drive system in which the combustion engine is supported by a pneumatic–hydraulic motor are presented. The purpose of the described work was to show that a heat exchanger with a [...] Read more.
The results of the first stage of work aimed at improving a hybrid drive system in which the combustion engine is supported by a pneumatic–hydraulic motor are presented. The purpose of the described work was to show that a heat exchanger with a design adapted to the operating conditions of a pneumatic–hydraulic motor would allow sufficient air heating at the expense of waste heat from the combustion engine, thus increasing the efficiency of the drive system. It was assumed that the key component of the heat exchanger would be copper foam in order to increase the heat exchange surface. A prototype modular heat exchanger was designed and tested. An open-cell copper foam with a porosity of 0.9 and a pore density of 40PPI was placed in the heat exchanger. Experimental and numerical air heating studies were carried out under various heat exchanger operating conditions. The tests were conducted at initial air temperatures of −123 °C, −71 °C, and 22 °C and air pressures of 2.5 × 106 and 7.0 × 106 Pa. The air mass flux was in the range of 3.6–1644 kg/(m2s). It was found that the tested heat exchanger allows a reduction in air consumption in the drive system of 11% to 58% and increases the efficiency of the air expansion system by 16% to 30%. The maximum efficiency of the heat exchanger is 96%. The results of the work carried out will help to improve the pneumatic–hydraulic drive systems of work machines and vehicles. Full article
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<p>Pneumatic–hydraulic system (<b>a</b>) configuration; (<b>b</b>) conversion efficiency. MGT—main gas tank; PV—pneumatic valve; HV—hydraulic valve.</p>
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<p>Pneumatic–hydraulic unit with a heat exchanger. ICE—internal combustion engine; MGT—main gas tank; PV—pneumatic valve; HV—hydraulic valve.</p>
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<p>Heat exchanger design: (<b>a</b>) single plate; (<b>b</b>) stack of plates with foam-filled channel.</p>
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<p>Prototype heat exchanger.</p>
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<p>Schematic of the test stand.</p>
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<p>Location of thermocouples in the heat exchanger.</p>
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<p>Change in air temperature at the outlet of the exchanger during periodic operation of the exchanger.</p>
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<p>Effect of the heat exchanger temperature and air mass flow on the heat flux.</p>
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<p>Heat transfer coefficient and pressure drop in air flow through a heat exchanger versus air velocity.</p>
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<p>The Nusselt equation compared to the experimental data.</p>
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<p>Numerical simulation domain: (<b>a</b>) external surfaces, (<b>b</b>) fluid space.</p>
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<p>Simulation result for variant W-II.600: (<b>a</b>) temperature distribution; (<b>b</b>) pressure distribution.</p>
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<p>Effects of air heating when flowing through one versus three heat exchanger modules: (<b>a</b>) air temperature at exchanger outlet; (<b>b</b>) increase in air temperature.</p>
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<p>Effects of air heating when flowing through one versus three heat exchanger modules: (<b>a</b>) air temperature at exchanger outlet; (<b>b</b>) increase in air temperature.</p>
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<p>Heat transfer coefficient for heating air in one versus three heat exchanger modules.</p>
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<p>Air pressure drop in the heat exchanger: (<b>a</b>) as a function of air velocity; (<b>b</b>) as a function of mass flow rate.</p>
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<p>Variation in heat exchanger power as a function of air mass flow.</p>
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<p>Heat exchanger efficiency in relation to its performance and number of modules.</p>
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<p>Reduction in drivetrain air consumption under various operating conditions.</p>
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<p>Temperature change of the heating oil in the heat exchanger.</p>
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<p>Temperature distributions: (<b>a</b>) heat exchanger block; (<b>b</b>) surface of the air channel.</p>
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13 pages, 12590 KiB  
Article
Stainless Steel 316L Fabricated by Fused Deposition Modeling Process: Microstructure, Geometrical and Mechanical Properties
by Maria Zaitceva, Anton Sotov, Anatoliy Popovich and Vadim Sufiiarov
J. Manuf. Mater. Process. 2024, 8(6), 259; https://doi.org/10.3390/jmmp8060259 - 14 Nov 2024
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Abstract
Additive manufacturing (AM) methods are widely used to produce metal products. However, the cost of equipment for processes based on material melting is high. In this paper, a promising, less expensive method of producing metal products from metal-filled Ultrafuse 316L filament by FDM [...] Read more.
Additive manufacturing (AM) methods are widely used to produce metal products. However, the cost of equipment for processes based on material melting is high. In this paper, a promising, less expensive method of producing metal products from metal-filled Ultrafuse 316L filament by FDM was investigated. The aim of this work was to compare the debinding methods and investigate the microstructure, phase composition, and geometric and mechanical properties. The results showed that catalytic debinding can be replaced by thermal debinding as no significant effect on the structure and properties was found. In addition, a filament study was performed and data on the particle size distribution, morphology, and phase composition of the metal particles were obtained. Thermodynamic modeling was performed to better understand the phase distribution at the sintering stage. The δ-Fe fraction influencing the corrosion properties of the material was estimated. The conformity of geometric dimensions to the original 3D models was evaluated using 3D scanning. The applied printing and post-processing parameters allowed us to obtain a density of 98%. The material and technology represent a promising direction for applications in the field of lightweight engineering in the manufacturing of parts with bioinspired designs, shells, and sparse filler structures with useful porosity designs (like helicoidal structures). Full article
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<p>Scheme of catalytic debinding.</p>
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<p>Process line of FDM additive manufacturing with metal-filled filament.</p>
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<p>Images of filament: (<b>a</b>) cross section, (<b>b</b>) longitudinal section; metal particles after (<b>c</b>) removal of binder in nitric acid, (<b>d</b>) thermal debinding, (<b>e</b>) powder cross section.</p>
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<p>DSC curve of filament.</p>
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<p>Sample appearance at the production stages.</p>
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<p>Cross sections of 3D-printed samples: (<b>a</b>,<b>b</b>) green models, (<b>c</b>,<b>d</b>) sintered parts.</p>
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<p>The XRD patterns of samples.</p>
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<p>Image of sample microstructure after sintering.</p>
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<p>Image of parts manufactured by FDM with metal-filled filament after sintering.</p>
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<p>Comparison of geometric dimensions of parts with 3D models: (<b>a</b>) green model; (<b>b</b>) sintered part.</p>
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26 pages, 4000 KiB  
Article
Comparative Study Between Active AMD and ABS Devices by Using μ-Synthesis Robust Control
by Karima Chaker, Badreddine Sbartai and Shehata E. Abdel Raheem
Appl. Sci. 2024, 14(22), 10481; https://doi.org/10.3390/app142210481 - 14 Nov 2024
Viewed by 104
Abstract
The field of civil engineering has witnessed significant development since the emergence of innovative control strategies that enhanced the construction of structures, imparting valuable resistance against dynamic loads like wind or earthquakes. Despite numerous articles highlighting the potential of various control approaches to [...] Read more.
The field of civil engineering has witnessed significant development since the emergence of innovative control strategies that enhanced the construction of structures, imparting valuable resistance against dynamic loads like wind or earthquakes. Despite numerous articles highlighting the potential of various control approaches to reduce vibration, their effectiveness in mitigating the dynamic effects on structures under real-world conditions appears limited once implemented. A variety of factors, including practical constraints, the choice of the control system device, the shape of the structure, and the amount of control energy deployed, contribute to this lack of efficiency. Within this context, the literature primarily addressed the discrepancy between the mathematical model and the actual structure model, commonly referred to as parameter uncertainties, in the controller design process. In other words, logical continuity in this field involves the application of a more adapted control approach, which enhances performance by incorporating more practical aspects in the controller synthesis procedure. These aspects include the dynamics of the control device, high-frequency neglected modes, and the inherent limitations or constraints of the control equipment. Thus, this study treats two main active control systems, ABS and AMD. While applying an approach known as μ-synthesis, the robust control was retained because of its ability to include all these considerations when they act simultaneously. We used this control to make sure that a three-degree-of-freedom structure responds as little as possible to seismic requests, which are shown by an uncertain model. We then conducted a comparative study between these two systems, focusing on displacement reduction and control force, while exploring a classic AMD control system at the top of the structure and an ABS control system at the bottom. This approach proved to be a powerful way to deal with the uncertainties affecting the structure and achieve the stability design objectives, given the satisfying simulation results. Full article
(This article belongs to the Section Civil Engineering)
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<p>Representation of uncertainties. (<b>a</b>) Dynamic uncertainty: additive form. (<b>b</b>) Dynamic uncertainty: multiplicative form.</p>
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<p>Control configuration by μ synthesis.</p>
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<p>AMD system attached to the top floor.</p>
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<p>ABS attached to the first floor.</p>
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<p>Performances control formulation in disturbances rejection problem.</p>
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<p>Time domain representation of the seismic acceleration (El Centro, 1979).</p>
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<p>Displacements of the structure with AMD System (μ<sub>C-MD</sub>): (<b>a</b>) first floor displacement, (<b>b</b>) second floor displacement, (<b>c</b>) third floor displacement.</p>
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<p>Displacements of the structure with AMD System (μ<sub>C-MD</sub>): (<b>a</b>) first floor displacement, (<b>b</b>) second floor displacement, (<b>c</b>) third floor displacement.</p>
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<p>Accelerations of the structure with AMD System (μ<sub>C-MD</sub>): (<b>a</b>) first floor acceleration, (<b>b</b>) second floor acceleration, (<b>c</b>) third floor acceleration.</p>
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<p>Accelerations of the structure with AMD System (μ<sub>C-MD</sub>): (<b>a</b>) first floor acceleration, (<b>b</b>) second floor acceleration, (<b>c</b>) third floor acceleration.</p>
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<p>Displacements of the structure with ABS (μ<sub>C-BS</sub>): (<b>a</b>) first floor displacement, (<b>b</b>) second floor displacement, (<b>c</b>) third floor displacement.</p>
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<p>Accelerations of the structure with ABS (μ<sub>C-BS</sub>): (<b>a</b>) first floor acceleration, (<b>b</b>) second floor acceleration, (<b>c</b>) third floor acceleration.</p>
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<p>Control force with AMD.</p>
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<p>Control force with ABS.</p>
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<p>Comparison between control force of AMD and ABSs.</p>
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<p>Comparison of RMS values of displacements with AMD and ABSs.</p>
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<p>Comparison of RMS values of accelerations with AMD and ABSs.</p>
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<p>First floor displacements comparison in nominal and worst case with ABS and AMD systems.</p>
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<p>Third floor displacements comparison in nominal and worst case with ABS and AMD systems.</p>
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22 pages, 5007 KiB  
Article
As-Built Performance of Net-Zero Energy, Emissions, and Cost Buildings: A Real-Life Case Study in Melbourne, Australia
by Morshed Alam, William Graze, Tom Graze and Ingrid Graze
Buildings 2024, 14(11), 3614; https://doi.org/10.3390/buildings14113614 - 14 Nov 2024
Viewed by 175
Abstract
This research investigated the real-world operational performance of five purposely designed and built net-zero-energy houses in Melbourne, Australia. The embodied energy and carbon emissions of these houses were calculated based on their architectural and engineering drawings, as well as the relevant databases of [...] Read more.
This research investigated the real-world operational performance of five purposely designed and built net-zero-energy houses in Melbourne, Australia. The embodied energy and carbon emissions of these houses were calculated based on their architectural and engineering drawings, as well as the relevant databases of embodied energy and emission factors. Operational data, including solar production, consumption, end uses, battery usage, grid import, and grid export, were measured using the appropriate IoT devices from May 2023 to April 2024. The results showed that all the studied houses achieved net-zero energy and net-zero carbon status for operation, exporting between 3 to 37 times more energy than they consumed to the grid (except for house 2, where the consumption from the grid was zero). The embodied carbon of each case study house was calculated as 13.1 tons of CO2-e, which could be paid back within 4 to 9 years depending on the operational carbon. Achieving net-zero cost status, however, was found to be difficult due to the higher electricity purchase price, daily connection charge, and lower feed-in tariff. Only house 2 was close to achieving net zero cost with only AUD 37 out-of-pocket cost. Increasing the energy exported to the grid and storing the generated solar energy may help achieve net-zero cost. The installation of batteries did not affect the net-zero energy or emission status but had a significant impact on net-zero operational costs. However, the calculated payback period for the batteries installed in these five houses ranged from 43 to 112 years, making them impractical at this stage compared to the typical 10-year warranty period of the batteries. With rising electricity purchase prices, decreasing feed-in tariffs (potentially to zero in the future/already the case in some areas), and government incentives for battery installation, the payback period could be reduced, justifying their adoption. Moreover, the installed 13.5 kWh Tesla battery was too big for households with lower energy consumption like houses 2 and 5, which used only 25% of their total battery capacity most of the year. Therefore, selecting an appropriately sized battery based on household consumption could further help reduce the payback period. Full article
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<p>The concept of creating net-zero buildings [<a href="#B9-buildings-14-03614" class="html-bibr">9</a>].</p>
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<p>Floor plans of the studied townhouses.</p>
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<p>Solar panels and batteries installed in the case study houses.</p>
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<p>Embodied energy and carbon of materials.</p>
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<p>Annual electricity production, consumption, and export from (<b>a</b>) house 1, (<b>b</b>) house 2, (<b>c</b>) house 3, (<b>d</b>) house 4, and (<b>e</b>) house 5.</p>
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<p>Energy consumed by various circuits in (<b>a</b>) house 1, (<b>b</b>) house 3, and (<b>c</b>) house 4.</p>
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<p>Energy consumed by various circuits in (<b>a</b>) house 1, (<b>b</b>) house 3, and (<b>c</b>) house 4.</p>
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<p>Battery payback period under various tariff scenarios.</p>
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<p>Percentage of battery capacity used throughout the year in all houses.</p>
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<p>End uses of electricity during winter in (<b>a</b>) house 1, (<b>b</b>) house 3 and (<b>c</b>) house 4.</p>
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<p>End uses of electricity during winter in (<b>a</b>) house 1, (<b>b</b>) house 3 and (<b>c</b>) house 4.</p>
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<p>Annual onsite solar energy production vs. consumption ratio.</p>
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5 pages, 188 KiB  
Editorial
Metaheuristic Algorithms in Optimal Design of Engineering Problems
by Łukasz Knypiński, Ramesh Devarapalli and Marcin Kamiński
Algorithms 2024, 17(11), 522; https://doi.org/10.3390/a17110522 (registering DOI) - 14 Nov 2024
Viewed by 134
Abstract
Metaheuristic optimization algorithms (MOAs) are widely used to optimize the design process of engineering problems [...] Full article
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimal Design of Engineering Problems)
12 pages, 2690 KiB  
Article
Perborate Activated Peroxymonosulfate Process for Improving the Coagulation Efficiency of Microcystis aeruginosa by Polymeric Aluminum Chloride
by Fan Chen, Lu Li, Shunfan Qiu, Shiyang Chen, Lingfang Yang, Lin Deng and Zhou Shi
Molecules 2024, 29(22), 5352; https://doi.org/10.3390/molecules29225352 (registering DOI) - 14 Nov 2024
Viewed by 154
Abstract
In this study, the sodium perborate (SP)-activated peroxymonosulfate (PMS) process was used to enhance the coagulation efficiency of cyanobacteria with polymeric aluminum chloride (PAC), aiming to efficiently mitigate the impact of algal blooms on the safety of drinking water production. The optimal concentrations [...] Read more.
In this study, the sodium perborate (SP)-activated peroxymonosulfate (PMS) process was used to enhance the coagulation efficiency of cyanobacteria with polymeric aluminum chloride (PAC), aiming to efficiently mitigate the impact of algal blooms on the safety of drinking water production. The optimal concentrations of SP, PMS, and PAC were determined by evaluating the removal rate of OD680 and zeta potential of the algae. Experimental results demonstrated that the proposed ternary PMS/SP/PAC process achieved a remarkable OD680 removal efficiency of 95.2%, significantly surpassing those obtained from individual treatments with PMS (19.5%), SP (5.2%), and PAC (42.1%), as well as combined treatments with PMS/PAC (55.7%) and PMS/SP (28%). The synergistic effect of PMS/SP/PAC led to the enhanced aggregation of cyanobacteria cells due to a substantial reduction in their zeta potential. Flow cytometry was performed to investigate cell integrity before and after treatment with PMS/SP/PAC. Disinfection by-products (DBPs) (sodium hypochlorite disinfection) of the algae-laden water subsequent to PMS/SP/PAC treatment declined by 57.1%. Moreover, microcystin-LR was completely degraded by PMS/SP/PAC. Electron paramagnetic resonance (EPR) analysis evidenced the continuous production of SO4, •OH, 1O2, and O2, contributing to both cell destruction and organic matter degradation. This study highlighted the significant potential offered by the PMS/SP/PAC process for treating algae-laden water. Full article
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<p>Comparison of different processes on cyanobacteria removal (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM, PAC dosage: 10 mg/L).</p>
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<p>Effect of SP and PMS dosage on cyanobacteria removal using PMS/SP/PAC treatment (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, PAC dosage: 10 mg/L).</p>
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<p>Effect of PAC dosage on cyanobacteria removal using PMS/SP/PAC treatment (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM).</p>
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<p>Cell integrity of algae treated with (<b>a</b>) control, (<b>b</b>) PAC, (<b>c</b>) PMS/PAC, and (<b>d</b>) PMS/SP/PAC (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM, PAC dosage: 10 mg/L).</p>
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<p>DBP yield from different treatments of cyanobacteria under chlorination in DI water (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM, PAC dosage: 10 mg/L).</p>
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<p>Microcystin-LR elimination using different treatment processes in the removal of cyanobacteria (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM, PAC dosage: 10 mg/L).</p>
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<p>The EPR spectra of (<b>a</b>) DMPO−OH and DMPO−SO<sub>4</sub> adducts, (<b>b</b>) DMPO−<math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="normal">O</mi> </mrow> <mrow> <mn>2</mn> </mrow> <mrow> <mo>•</mo> <mo>−</mo> </mrow> </msubsup> </mrow> </semantics></math> adducts, and (<b>c</b>) TEMP−<sup>1</sup>O<sub>2</sub> adducts (initial algal cell density: 5.0 × 10<sup>6</sup> cells/mL, SP dosage: 1 mM, PMS dosage: 3 mM, PAC dosage: 10 mg/L, [DMPO] = [TEMP] = 100 mM).</p>
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25 pages, 623 KiB  
Article
Quantitative and Qualitative Analysis of Main Parameters and Their Interactions in Thermoacoustic Refrigerators Performance
by Humberto Peredo Fuentes and Carlos Amir Escalante Velázquez
Appl. Sci. 2024, 14(22), 10470; https://doi.org/10.3390/app142210470 - 14 Nov 2024
Viewed by 241
Abstract
Efforts to optimize the design and enhance the efficiency of standing-wave thermoacoustic refrigerators (SWTARs), particularly those with parallel plate stacks, are crucial for achieving rapid and straightforward engineering estimates. This study primarily focused on optimizing the coefficient of performance (COP) by combining linear [...] Read more.
Efforts to optimize the design and enhance the efficiency of standing-wave thermoacoustic refrigerators (SWTARs), particularly those with parallel plate stacks, are crucial for achieving rapid and straightforward engineering estimates. This study primarily focused on optimizing the coefficient of performance (COP) by combining linear thermoacoustic theory (LTT) with the design of experiments (DOE) approach. The investigation centered around five key parameters affecting the COP once the working gas had been selected. Then, based on LTT, the COP was estimated numerically over defined intervals of those five parameters. Moreover, through quantitative and qualitative effect analyses, these five parameters and their interactions were determined. Utilizing a transfer function, the study aimed to delineate the best COP value (1.76) over a defined interval of the parameters as well as the contribution of the thermoacoustic main parameters (55.69%) and their interactions (two-way interactions = 33.30%, three-way interactions = 7.36%, and four-way interactions = 3.35%). Furthermore, a comparison between contour and surface responses and several statistical decision approaches applying the full factorial design verified the robustness of the study’s findings. Ultimately, the COP results obtained aligned with the existing literature, underscoring the validity and relevance of the study’s methodologies and conclusions. Full article
(This article belongs to the Special Issue Process Control and Optimization)
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<p>Structure diagram of a thermoacoustic refrigerator and selected five parameters (<math display="inline"><semantics> <mrow> <mi>D</mi> <mo>,</mo> <msub> <mi>X</mi> <mi>s</mi> </msub> <mo>,</mo> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>T</mi> <mi>m</mi> </msub> <mo>,</mo> <mi>B</mi> <mo>,</mo> <msub> <mi>L</mi> <mi>s</mi> </msub> </mrow> </semantics></math>).</p>
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<p>Structure diagram of a parallel stack.</p>
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<p>DOE geometric representation. In each case, high levels are highlighted in blue, low levels in red [<a href="#B32-applsci-14-10470" class="html-bibr">32</a>].</p>
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<p>Representative <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> response as a function of its dimensionless position <math display="inline"><semantics> <msub> <mi>x</mi> <mi>n</mi> </msub> </semantics></math> and length <math display="inline"><semantics> <msub> <mi>L</mi> <mrow> <mi>s</mi> <mi>n</mi> </mrow> </msub> </semantics></math> calculated with the developed numerical routine in Python: (<b>a</b>) COP responses obtained by Tijani with parameters defined in [<a href="#B18-applsci-14-10470" class="html-bibr">18</a>]: <math display="inline"><semantics> <msub> <mi>p</mi> <mi>m</mi> </msub> </semantics></math> = 10 bars, <math display="inline"><semantics> <msub> <mi>T</mi> <mi>m</mi> </msub> </semantics></math> = 250 K, <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>T</mi> <mrow> <mi>m</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = 0.3, <span class="html-italic">D</span> = 0.02, <span class="html-italic">f</span> = 400 Hz, k = 2.68 m<sup>−1</sup>, a = 935 m/s, <math display="inline"><semantics> <mi>σ</mi> </semantics></math> = 0.68, <math display="inline"><semantics> <mi>γ</mi> </semantics></math> = 1.67, B = 0.75, <math display="inline"><semantics> <msub> <mi>δ</mi> <mrow> <mi>κ</mi> <mi>n</mi> </mrow> </msub> </semantics></math> = 0.66; (<b>b</b>) COP responses obtained by Run 1 parameters defined in <a href="#applsci-14-10470-t005" class="html-table">Table 5</a>: <math display="inline"><semantics> <msub> <mi>p</mi> <mi>m</mi> </msub> </semantics></math> = 1 bar, <math display="inline"><semantics> <msub> <mi>T</mi> <mi>m</mi> </msub> </semantics></math> = 298 K, <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>T</mi> <mrow> <mi>m</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = 0.017, <span class="html-italic">D</span> = 0.01, <span class="html-italic">f</span> = 122.85 Hz, k = 2.00 m<sup>−1</sup>, a = 344 m/s, <math display="inline"><semantics> <mi>σ</mi> </semantics></math> = 0.7, <math display="inline"><semantics> <mi>γ</mi> </semantics></math> = 1.67, B = 0.25, <math display="inline"><semantics> <msub> <mi>δ</mi> <mrow> <mi>κ</mi> <mi>n</mi> </mrow> </msub> </semantics></math> = 1.62.</p>
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<p>Main factors for <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math>.</p>
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<p>Interaction of <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> factors.</p>
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<p>COP Pareto plot.</p>
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<p>COP cube plot.</p>
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<p><math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> contour plots center point hold values.</p>
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<p><math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> contour plots lower limits hold values.</p>
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<p><math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> surface with brightness 50% (Light 1: X = 0, Y = 1, Z = 1, Color = Automatic; Light 2: X = 0, Y = 0, Z = −1, Color = Automatic. Plot center point hold values.</p>
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<p><math display="inline"><semantics> <mrow> <mi>C</mi> <mi>O</mi> <mi>P</mi> </mrow> </semantics></math> surface with brightness 50% (Light 1: X = 0, Y = 1, Z = 1, Color = Automatic; Light 2: X = 0, Y = 0, Z = −1, Color = Automatic. Plot lower limits hold values.</p>
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19 pages, 6930 KiB  
Article
Deterministic Trajectory Design and Attitude Maneuvers of Gradient-Index Solar Sail in Interplanetary Transfers
by Marco Bassetto, Giovanni Mengali and Alessandro A. Quarta
Appl. Sci. 2024, 14(22), 10463; https://doi.org/10.3390/app142210463 - 13 Nov 2024
Viewed by 317
Abstract
A refractive sail is a special type of solar sail concept, whose membrane exposed to the Sun’s rays is covered with an advanced engineered film made of micro-prisms. Unlike the well-known reflective solar sail, an ideally flat refractive sail is able to generate [...] Read more.
A refractive sail is a special type of solar sail concept, whose membrane exposed to the Sun’s rays is covered with an advanced engineered film made of micro-prisms. Unlike the well-known reflective solar sail, an ideally flat refractive sail is able to generate a nonzero thrust component along the sail’s nominal plane even when the Sun’s rays strike that plane perpendicularly, that is, when the solar sail attitude is Sun-facing. This particular property of the refractive sail allows heliocentric orbital transfers between orbits with different values of the semilatus rectum while maintaining a Sun-facing attitude throughout the duration of the flight. In this case, the sail control is achieved by rotating the structure around the Sun–spacecraft line, thus reducing the size of the control vector to a single (scalar) parameter. A gradient-index solar sail (GIS) is a special type of refractive sail, in which the membrane film design is optimized though a transformation optics-based method. In this case, the membrane film is designed to achieve a desired refractive index distribution with the aid of a waveguide array to increase the sail efficiency. This paper analyzes the optimal transfer performance of a GIS with a Sun-facing attitude (SFGIS) in a series of typical heliocentric mission scenarios. In addition, this paper studies the attitude control of the Sun-facing GIS using a simplified mathematical model, in order to investigate the effective ability of the solar sail to follow the (optimal) variation law of the rotation angle around the radial direction. Full article
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<p>Sketch of the SFGIS with the normal unit vector <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold-italic">n</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> and the reference unit vector <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold-italic">m</mi> <mo stretchy="false">^</mo> </mover> </semantics></math>, whose directions are fixed in a (spacecraft) body reference frame. Note that the sail nominal plane <math display="inline"><semantics> <mi mathvariant="script">P</mi> </semantics></math> is perpendicular to the Sun–spacecraft line, and the unit vector <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold-italic">m</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> belongs to the <math display="inline"><semantics> <mi mathvariant="script">P</mi> </semantics></math> plane. The conceptual scheme of the waveguide array was adapted from Ref. [<a href="#B1-applsci-14-10463" class="html-bibr">1</a>], courtesy of Dr. Shengping Gong.</p>
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<p>Sketch of the Radial–Transverse–Normal (RTN) reference frame <math display="inline"><semantics> <msub> <mi mathvariant="script">T</mi> <mi>RTN</mi> </msub> </semantics></math> of unit vectors <math display="inline"><semantics> <mrow> <mo stretchy="false">{</mo> <msub> <mover accent="true"> <mi mathvariant="bold-italic">i</mi> <mo stretchy="false">^</mo> </mover> <mi mathvariant="normal">R</mi> </msub> <mo>,</mo> <mspace width="0.166667em"/> <msub> <mover accent="true"> <mi mathvariant="bold-italic">i</mi> <mo stretchy="false">^</mo> </mover> <mi mathvariant="normal">T</mi> </msub> <mo>,</mo> <mspace width="0.166667em"/> <msub> <mover accent="true"> <mi mathvariant="bold-italic">i</mi> <mo stretchy="false">^</mo> </mover> <mi mathvariant="normal">N</mi> </msub> <mo stretchy="false">}</mo> </mrow> </semantics></math>. The sail clock angle <math display="inline"><semantics> <mrow> <mi>δ</mi> <mo>∈</mo> <msup> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mspace width="0.166667em"/> <mn>360</mn> <mo>]</mo> </mrow> <mo>∘</mo> </msup> </mrow> </semantics></math> is the single control parameter of an SFGIS-propelled spacecraft.</p>
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<p>Dimensionless components <math display="inline"><semantics> <mrow> <mo>{</mo> <msub> <mi>a</mi> <msub> <mi>p</mi> <mi mathvariant="normal">R</mi> </msub> </msub> <mo>/</mo> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>,</mo> <mspace width="0.166667em"/> <msub> <mi>a</mi> <msub> <mi>p</mi> <mi mathvariant="normal">T</mi> </msub> </msub> <mo>/</mo> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>,</mo> <mspace width="0.166667em"/> <msub> <mi>a</mi> <msub> <mi>p</mi> <mi mathvariant="normal">N</mi> </msub> </msub> <mo>/</mo> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>}</mo> </mrow> </semantics></math> of the propulsive acceleration vector as a function of the sail clock angle <math display="inline"><semantics> <mrow> <mi>δ</mi> <mo>∈</mo> <msup> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mspace width="0.166667em"/> <mn>360</mn> <mo>]</mo> </mrow> <mo>∘</mo> </msup> </mrow> </semantics></math>, when the solar distance is one astronomical unit.</p>
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<p>Time variation in the (unconstrained) sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> in the minimum-time Earth–Venus mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. Blue dot → starting point; red square → arrival point.</p>
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<p>Ecliptic projection and isometric view of the rapid transfer trajectory in an Earth–Venus mission scenario, when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> and the sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> is unconstrained. The <span class="html-italic">z</span>-axis of the isometric view is exaggerated to highlight the three-dimensionality of the transfer trajectory. Black line → spacecraft transfer trajectory; blue line → Earth’s orbit; red line → Venus’s orbit; filled star → perihelion; blue dot → starting point; red square → arrival point; orange dot → the Sun.</p>
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<p>Time variation of the (unconstrained) sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> in a minimum-time Earth–asteroid 433 Eros mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f004" class="html-fig">Figure 4</a>.</p>
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<p>Ecliptic projection and isometric view of the rapid transfer trajectory in an Earth–asteroid 433 Eros mission scenario, when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> and unconstrained sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 8
<p>Minimum flight time as a function of the characteristic acceleration <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>∈</mo> <mrow> <mo>[</mo> <mn>0.1</mn> <mo>,</mo> <mspace width="0.166667em"/> <mn>0.2</mn> <mo>]</mo> </mrow> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> in an Earth–Venus orbit-to-orbit transfer. The black dot refers to the special case of <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> discussed in the first part of the section.</p>
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<p>Ecliptic projection and isometric view of the rapid transfer trajectory in an Earth–Mars mission scenario, when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> and the sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> is unconstrained. The legend is reported in <a href="#applsci-14-10463-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 10
<p>Time variation of the (unconstrained) sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> in a minimum-time Earth–Mars mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f004" class="html-fig">Figure 4</a>.</p>
Full article ">Figure 11
<p>Ecliptic projection and isometric view of the rapid transfer trajectory of an Earth–Mercury mission scenario, when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math> and the sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> is unconstrained. The legend is reported in <a href="#applsci-14-10463-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 12
<p>Time variation in the (unconstrained) sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> in a minimum-time Earth–Mercury mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f004" class="html-fig">Figure 4</a>.</p>
Full article ">Figure 13
<p>Time variation of the constrained sail clock angle <math display="inline"><semantics> <mi>δ</mi> </semantics></math> in a minimum-time Earth–Venus mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f004" class="html-fig">Figure 4</a>. (<b>a</b>) Case of <math display="inline"><semantics> <mrow> <mi mathvariant="script">I</mi> <mo>=</mo> <msub> <mi mathvariant="script">I</mi> <mrow> <mo>①</mo> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) Case of <math display="inline"><semantics> <mrow> <mi mathvariant="script">I</mi> <mo>=</mo> <msub> <mi mathvariant="script">I</mi> <mrow> <mo>②</mo> </mrow> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 14
<p>Sun–spacecraft distance <span class="html-italic">r</span> as a function of time in a minimum-time Earth–Venus mission scenario when <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>0.175</mn> <mspace width="0.166667em"/> <mi>mm</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. The legend is reported in <a href="#applsci-14-10463-f004" class="html-fig">Figure 4</a>. (<b>a</b>) Case of <math display="inline"><semantics> <mrow> <mi mathvariant="script">I</mi> <mo>=</mo> <msub> <mi mathvariant="script">I</mi> <mrow> <mo>①</mo> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) Case of <math display="inline"><semantics> <mrow> <mi mathvariant="script">I</mi> <mo>=</mo> <msub> <mi mathvariant="script">I</mi> <mrow> <mo>②</mo> </mrow> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 15
<p>Sketch of an SFGIS with two control vanes. The force due to the solar radiation pressure acting on the two moving surfaces is applied at the vane pressure center <math display="inline"><semantics> <msub> <mi>C</mi> <mi>p</mi> </msub> </semantics></math>. The rotation of the surfaces, denoted by <math display="inline"><semantics> <mi>β</mi> </semantics></math>, is the vane control angle.</p>
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<p>Closed-loop control scheme with saturation of the input to the system.</p>
Full article ">Figure 17
<p>Results of the numerical simulation when <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>≃</mo> <mn>9.1724</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>8</mn> </mrow> </msup> <mspace width="0.166667em"/> <mi>rad</mi> <mo>/</mo> <msup> <mi mathvariant="normal">s</mi> <mn>2</mn> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 18
<p>Minimum settling time <math display="inline"><semantics> <msub> <mi>t</mi> <mi>s</mi> </msub> </semantics></math> to perform a rotation of <math display="inline"><semantics> <mrow> <msub> <mi>δ</mi> <mi>ref</mi> </msub> <mo>=</mo> <mn>1</mn> <mspace width="0.166667em"/> <mi>rad</mi> </mrow> </semantics></math> around <span class="html-italic">z</span> as a function of <span class="html-italic">k</span>.</p>
Full article ">Figure 19
<p>Optimal control parameters of the PDF controller as a function of <span class="html-italic">k</span>.</p>
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