Search Results (75)

Nanothermodynamics provides the theoretical foundation for understanding stable distributions of statistically independent subsystems inside larger systems. In this review, it is emphasized that extending ideas from nanothermodynamics to simplistic models improves agreement with the measured properties of many materials. Examples include non-classical critical scaling near ferromagnetic transitions, thermal and dynamic behavior near liquid–glass transitions, and the 1/f-like noise in metal films and qubits. A key feature in several models is to allow separate time steps for distinct conservation laws: one type of step conserves energy and the other conserves momentum (e.g., dipole alignment). This “orthogonal dynamics” explains how the relaxation of a single parameter can exhibit multiple responses such as primary, secondary, and microscopic peaks in the dielectric loss of supercooled liquids, and the crossover in thermal fluctuations from Johnson–Nyquist (white) noise at high frequencies to 1/f-like noise at low frequencies. Nanothermodynamics also provides new insight into three basic questions. First, it gives a novel solution to Gibbs’ paradox for the entropy of the semi-classical ideal gas. Second, it yields the stable equilibrium of Ising’s original model for finite-sized chains of interacting binary degrees of freedom (“spins”). Third, it confronts Loschmidt’s paradox for the arrow of time, showing that an intrinsically irreversible step is required for maximum entropy and the second law of thermodynamics, not only in the thermodynamic limit but also in systems as small as $N=2$ particles. Full article

Spring–dashpot models have long been used to simulate the mechanical behavior of polymers, but their usefulness is limited because multiple model parameter values can reproduce the experimental data. In view of this limitation, this study explores the possibility of improving uniqueness of parameter values so that the parameters can be used to establish the relationship between deformation and microstructural changes. An approach was developed based on stress during the loading, relaxation, and recovery of polyethylene. In total, 1000 sets of parameter values were determined for fitting the data from the relaxation stages with a discrepancy within 0.08 MPa. Despite a small discrepancy, the 1000 sets showed a wide range of variation, but one model parameter, ${\sigma }_{v,L}\left(0\right)$, followed two distinct paths rather than random distribution. The five selected sets of parameter values with discrepancies below 0.04 MPa were found to be highly consistent, except for the characteristic relaxation time. Therefore, this study concludes that the uniqueness of model parameter values can be improved to characterize the mechanical behavior of polyethylene. This approach then determined the quasi-static stress of four polyethylene pipes, which showed that these pipes had very close quasi-static stress. This indicates that the uniqueness of the parameter values can be improved for the spring–dashpot model, enabling further study using spring–dashpot models to characterize polyethylene’s microstructural changes during deformation. Full article

This paper investigates the inland container transportation problem with a focus on multi-size containers, fuel consumption, and carbon emissions. To reflect a more realistic situation, the depot’s initial inventory of empty containers is also taken into consideration. To linearly model the constraints imposed by the multiple container sizes and the limited number of empty containers, a novel graphical representation is presented for the problem. Based on the graphical representation, a mixed-integer programming model is presented to minimize the total transportation cost, which includes fixed, fuel, and carbon emission costs. To efficiently solve the model, a tailored branch-and-price algorithm is designed, which is enhanced by improvement schemes including a heuristic label-setting algorithm, decremental state-space relaxation, and the introduction of a high-quality upper bound. Results from a series of computational experiments on randomly generated instances demonstrate that (1) the proposed branch-and-price algorithm demonstrates a superior performance compared to the tabu search algorithm and the genetic algorithm; (2) each additional empty container in the depot reduces the total transportation cost by less than 1%, with a diminishing marginal effect; (3) the rational configuration of different types of trucks improves scheduling flexibility and reduces fuel and carbon emission costs as well as the overall transportation cost; and (4) extending customer time windows also contributes to lower the total transportation cost. These findings not only deepen the theoretical understanding of inland container transportation optimization but also provide valuable insights for logistics companies and policymakers to improve efficiency and implement more sustainable operational practices. Additionally, our research paves the way for future investigations into the integration of dynamic factors and emerging technologies in this field. Full article

Laser Hot Wire (LHW) Directed Energy Deposition (DED) Additive Manufacturing (AM) processes are capable of manufacturing parts with a high deposition rate. There is a growing research interest in replacing large cast Nickel Aluminum Bronze (NAB) components using LHW DED processes for maritime applications. Understanding thermomechanical behavior during LHW DED of NAB is a critical step towards the production of high-quality NAB parts with desired performance and properties. In this paper, finite element simulations are first used to predict the thermomechanical time histories during LHW DED of NAB test coupons with an increasing geometric complexity, including single-layer and multilayer depositions. Simulation results are experimentally validated through in situ measurements of temperatures at multiple locations in the substrate as well as displacement at the free end of the substrate during and immediately following the deposition process. The results in this paper demonstrate that the finite element predictions have good agreement with the experimental measurements of both temperature and distortion history. The maximum prediction error for temperature is 5% for single-layer samples and 6% for multilayer samples, while the distortion prediction error is about 12% for single-layer samples and less than 4% for multilayer samples. In addition, this study shows the effectiveness of including a stress relaxation temperature at 500 °C during FE modeling to allow for better prediction of the low cross-layer accumulation of distortion in multilayer deposition of NAB. Full article

Considering the negative effects of time delay and noise on vehicle state estimation, a cascaded estimation means for the vehicle sideslip angle is proposed utilizing the ODUKF algorithm. To achieve strong-correlation decoupling between state variables and model interference of the EDWM, an augmented EDWM was constructed by introducing the tire relaxation length dynamic equation, which enables the precise model relationship between the longitudinal and transverse tire force relaxation length to be constructed while also achieving the decoupling of the system state from the unknown input. To achieve a vehicle driving state estimation, a hierarchical estimation architecture was adopted to design a cascading estimation method for the vehicle driving state. By using tire force estimation values as input for the vehicle driving state estimation, the required vehicle body postures can be estimated. At the same time, facing the problems of system delay and noise, an estimator derived from the ODUKF is designed by combining the model and cascade estimation strategy. The simulation comparative analysis and quantitative statistical results under multiple operating conditions provide evidence that the developed means effectively heighten the estimation accurateness and real-time performance while considering system time delay and noise. Full article

The Boltzmann equation with multiple-relaxation-time (MRT) collision operators has been widely employed in kinetic theory to describe the behavior of gases and liquids at the macro-level. Given the successful development of deep learning and the availability of data analytic tools, it is a feasible idea to try to solve the Boltzmann-MRT equation using a neural network-based method. Based on the canonical polyadic decomposition, a new physics-informed neural network describing the Boltzmann-MRT equation, named the network for MRT collision (NMRT), is proposed in this paper for solving the Boltzmann-MRT equation. The method of tensor decomposition in the Boltzmann-MRT equation is utilized to combine the collision matrix with discrete distribution functions within the moment space. Multiscale modeling is adopted to accelerate the convergence of high frequencies for the equations. The micro–macro decomposition method is applied to improve learning efficiency. The problem-dependent loss function is proposed to balance the weight of the function for different conditions at different velocities. These strategies will greatly improve the accuracy of the network. The numerical experiments are tested, including the advection–diffusion problem and the wave propagation problem. The results of the numerical simulation show that the network-based method can obtain a measure of accuracy at $O\left({10}^{-3}\right)$. Full article

In the realm of supply chain logistics, the Multi-Depot Multi-Supplier Vehicle Routing Problem (MDMSVRP) poses a significant challenge in optimizing the transportation process to minimize costs and enhance operational efficiency. This problem involves determining the most cost-effective routes for a fleet of vehicles to deliver goods from multiple suppliers to multiple depots, considering various constraints and non-linear relationships. The routing problem (RP) is a critical element of many logistics systems that involve the routing and scheduling of vehicles from a depot to a set of customer nodes. One of the most studied versions of the RP is the Vehicle Routing Problem with Time Windows (VRPTW), in which each customer must be visited at certain time intervals, called time windows. In this paper, it is considered that there are multiple depots (supply centers) and multiple suppliers, along with a fleet of vehicles. The goal is to efficiently plan routes for these vehicles to deliver goods from the suppliers to various customers while considering relaxed time windows. This research is intended to establish a new relaxation scheme that relaxes the time window constraints in order to lead to feasible and good solutions. In addition, this study develops a discrete optimization model as an alternative model for the time-dependent VRPTW involving multi-suppliers. This research also develops a metaheuristic algorithm with an initial solution that is determined through time window relaxation. Full article

In this paper, the time-resolved model of the photoacoustic signal for samples with a complex inner structure is derived including local non-equilibrium of structural elements with multiple degrees of freedom, i.e., structural entropy of the system. The local non-equilibrium is taken into account through the fractional operator. By analyzing the model for two types of time-dependent excitation, a very short pulse and a very long pulse, it is shown that the rates of non-equilibrium relaxations in complex samples can be measured by applying the derived model and time-domain measurements. Limitations of the model and further directions of its development are discussed. Full article

Using porous wind barriers for the microclimate modification of agricultural lands, urban areas, and surrounding roads is a ubiquitous practice. This study establishes a new method for numerically modeling the turbulent flow in and around forest shelterbelts using an advanced multiple-relaxation-time lattice Boltzmann model (MRTLBM). A detailed description is presented for a large eddy simulation (LES) of turbulent winds by implementing barrier element drag force in the MRTLBM framework. The model results for a forest shelterbelt are compared with a field observational dataset. The study indicated that our implementation of drag force in MRTLBM is an accurate method for modeling turbulent flows in and around forest patches. Sensitivity analyses of turbulent flow related to the shelterbelt structure parameters and wind directions are also carried out. The analysis indicated that the optimal wind shelter effect in reducing the mean wind speed and turbulent kinetic energy is maximized using a narrow, medium porosity shelterbelt, with the wind direction perpendicular to the shelterbelt. These conclusions are in agreement with other observational and modeling studies. Finally, the computational time of a central processing unit (CPU) and graphics processing unit (GPU) was compared for a large domain with 25 million grids to demonstrate the MRTLBM advantage of LES in regards to computational speed with a mixed forest and building environment. The GPU is approximately 300 times faster than a CPU, and real-time simulation for this large domain is achieved using the Nvidia V100 GPU. Full article

Optimizing pain management in spinal surgery is crucial for preventing adverse events due to delayed mobilization. Magnesium sulfate has potential benefits in spinal surgery because of its analgesic properties and modulation of neurotransmitters and autonomic nervous system. Existing evidence regarding the use of magnesium sulfate is partial and controversial, necessitating a comprehensive meta-analysis to evaluate its efficacy and safety. The aim of this study was to conduct a comprehensive meta-analysis to evaluate the efficacy and safety of magnesium sulfate in spinal surgery compared to other available options. This meta-analysis adhered to the PRISMA guidelines. Patients undergoing spinal surgery were included, with the intervention group receiving intravenous magnesium sulfate (MS) at various doses or combinations, whereas the comparison group received other alternatives or a placebo. The efficacy and safety outcomes were assessed. Data were collected from multiple databases and analyzed using Review Manager version 5.4. Heterogeneity was assessed and fixed- or random-effects models were applied. The meta-analysis included eight studies (n = 541). Magnesium sulfate demonstrated significant reductions in pain at 24 h (MD −0.20, 95% CI: −0.39 to −0.02) and opioid consumption (SMD −0.66, 95% CI: −0.95 to −0.38) compared to placebo. Additionally, a decrease in the use of muscle relaxants (SMD −0.91, 95% CI: −1.65 to −0.17) and remifentanil (SMD −1.52, 95% CI: −1.98 to −1.05) was observed. In contrast, an increase in extubation time (MD 2.42, 95% CI: 1.14 to 3.71) and verbal response (MD 1.85, 95% CI: 1.13 to 2.58) was observed compared to dexmedetomidine. In conclusion, magnesium sulfate administration in spinal surgery reduced pain and opioid consumption, and prolonged orientation and verbal response. No significant differences in blood pressure or heart rate were observed between the groups. Full article

This paper explores the thermal behavior of multiple interface cracks situated between a half-plane and a thermal coating layer when subjected to transient thermal loading. The temperature distribution is analyzed using the hyperbolic heat conduction theory. In this model, cracks are represented as arrays of thermal dislocations, with densities calculated via Fourier and Laplace transformations. The methodology involves determining the temperature gradient within the uncracked region, and these calculations contribute to formulating a singular integral equation specific to the crack problem. This equation is subsequently utilized to ascertain the dislocation densities at the crack surface, which facilitates the estimation of temperature gradient intensity factors for the interface cracks experiencing transient thermal loading. This paper further explores how the relaxation time, loading parameters, and crack dimensions impact the temperature gradient intensity factors. The results can be used in fracture analysis of structures operating at high temperatures and can also assist in the selection and design of coating materials for specific applications, to minimize the damage caused by temperature loading. Full article

Exploring the deformation mechanism of the 2021 Mw 7.4 Maduo Earthquake is crucial for better understanding the seismic hazard of the faults with low strain rates inside the Bayan Har block. This study leverages deformation information derived from Sentient-1 A/B images and GPS data to investigate in detail the co- and postseismic deformation mechanisms using multiple methods. The main results are as follows. First, the postseismic InSAR time series robustly identified the reactivation of the Changmahe fault, indicating the impact of the Maduo event on surrounding active faults. Second, the joint inversion of Interferometric Synthetic Aperture Radar and GPS revealed that (1) there was a complementary and partially overlapping relationship between the coseismic slip and postseismic afterslip of the main rupture; and (2) the Changmahe fault exhibited thrust compression dislocation in the early stage and experienced a sustained compressive effect from afterslip in the one year after the mainshock. Third, modeling the processes of viscoelastic relaxation and poroelastic rebound revealed that the postseismic deformation was probably caused by a combination of afterslip (near-field) and viscoelastic relaxation (near and far field). Fourth, the stress changes driven by the Maduo event revealed that the seismic gaps inside the Maqin-Maqu segment and the Kunlun Pass-Jiangcuo fault will be potential seismic risks in the future. Full article

The impact of controlled breathing on cognitive and affective processing has been recognized since ancient times, giving rise to multiple practices aimed at achieving different psychophysical states, mostly related to mental clarity and focus, stress reduction, and relaxation. Previous scientific research explored the effects of forced unilateral nostril breathing (UNB) on brain activity and emotional and cognitive functions. Some evidence concluded that it had a contralateral effect, while other studies presented controversial results, making it difficult to come to an unambiguous interpretation. Also, a few studies specifically addressed wellbeing. In the present study, we invited a pilot sample of 20 participants to take part in an 8-day training program for breathing, and each person was assigned to either a unilateral right nostril (URNB) or left nostril breathing condition (ULNB). Then, each day, we assessed the participants’ wellbeing indices using their moods and mind wandering scales. The results revealed that, after the daily practice, both groups reported improved wellbeing perception. However, the effect was specifically related to the nostril involved. URNB produced more benefits in terms of stress reduction and relaxation, while ULNB significantly and increasingly reduced mind-wandering occurrences over time. Our results suggest that UNB can be effectively used to increase wellbeing in the general population. Additionally, they support the idea that understanding the effects of unilateral breathing on wellbeing and cognition requires a complex interpretive model with multiple brain networks to address bottom-up and top-down processes. Full article

Digital radio frequency memory (DRFM) has emerged as an advanced technique to achieve a range of jamming signals, due to its capability to intercept waveforms within a short time. multiple-input multiple-output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to combat DRFM-based jamming, where any two groups of waveform sets are also orthogonal. In this article, a group orthogonal waveform optimal design model is formulated in order to combat DRFM-based jamming by flexibly designing waveforms for MIMO radars. Aiming at balancing the intra- and intergroup orthogonal performances, the objective function is defined as the weighted sum of the intra- and intergroup orthogonal performance metrics. To solve the formulated model, in this article, a group orthogonal waveform design algorithm is proposed. Based on a primal-dual-type method and proper relaxations, the proposed algorithm transforms the original problem into a series of simple subproblems. Numerical results demonstrate that the obtained group orthogonal waveforms have the ability to flexibly suppress DRFM-based deceptive jamming, which is not achievable using p-majorization–minimization (p-MM) and primal-dual, two of the most advanced orthogonal waveform design algorithms. Full article

Aiming to address problems such as low sampling success rate and long computation time in the motion planning of a dual-arm cooperative system with multiple constraints, this paper proposes an Informed-Bi-Quick RRT* algorithm based on offline sampling. First, in the process of pre-sampling, the new algorithm relaxes the approximation of constrained manifolds by introducing the idea of incremental construction, and it incorporates the stochastic gradient descent method to replace global random sampling with local random sampling, which enriches the data set and shortens the offline sampling time of the data set. Second, the new algorithm improves the original Quick-RRT* algorithm by combining the two-tree idea and the multi-target bias expansion strategy, and it improves the adaptability of the algorithm to different obstacle environments. In addition, the loosely constrained motion and tightly constrained motion in the two-arm cooperative system are analyzed, and the adaptive planning of the two-arm trajectory in different motions is described in detail. In this paper, the two-arm cooperative model constructed with UR5 and UR10 robot arms is studied, and the ability of the proposed algorithm to deal with multiple constraints is verified by simulating assembly and handling tasks. The experimental results show that compared with other methods, the proposed algorithm has obvious advantages in path quality and planning efficiency. Full article