Search Results (51,764)

In hot-forming, integrating in situ quality monitoring is essential for the early detection of thermally induced geometric deviations, especially in the production of hybrid bulk metal parts. Although hybrid components are key to meeting modern technical requirements and saving resources, they exhibit complex shrinkage behavior due to differing thermal expansion coefficients. During forming, these components are exposed to considerable temperature gradients, which result in density fluctuations in the ambient air. These fluctuations create an inhomogeneous refractive index field (IRIF), which significantly affects the accuracy of optical geometry reconstruction systems due to light deflection. This study utilizes existing simulation IRIF data to predict the magnitude and orientation of refractive index fluctuations. A light deflection simulation run on a GPU-accelerated ray tracing framework is used to assess the impact of IRIFs on optical measurements. The results of this simulation are used as a basis for selecting optimized measurement positions, reducing and quantifying uncertainties in surface reconstruction, and, therefore, improving the reliability of quality control in hot-forming applications. Full article

With the continuous development of industrial automation, diesel engines play an increasingly important role in various types of construction machinery and power generation equipment. Improving the dynamic and static performance of the speed control system of single-cylinder diesel engines can not only significantly improve the efficiency of the equipment, but also effectively reduce energy consumption and emissions. Particle swarm optimization (PSO) fuzzy PID control algorithms have been widely used in many complex engineering problems due to their powerful global optimization capability and excellent adaptability. Currently, PSO-based fuzzy PID control research mainly integrates hybrid algorithmic strategies to avoid the local optimum problem, and lacks optimization of the dynamic noise suppression of the input error and the rate of change of the error. This makes the algorithm susceptible to the coupling of the system uncertainty and measurement disturbances during the parameter optimization process, leading to performance degradation. For this reason, this study proposes a new framework based on the synergistic optimization of the untraceable Kalman filter (UKF) and PSO fuzzy PID control for the speed control system of a single-cylinder diesel engine. A PSO-optimized fuzzy PID controller is designed by obtaining accurate speed estimation data using the UKF. The PSO is capable of quickly adjusting the fuzzy PID parameters so as to effectively alleviate the nonlinearity and uncertainty problems during the operation of diesel engines. By establishing a Matlab/Simulink simulation model, the diesel engine speed step response experiments (i.e., startup experiments) and load mutation experiments were carried out, and the measurement noise and process noise were imposed. The simulation results show that the optimized diesel engine speed control system is able to reduce the overshoot by 76%, shorten the regulation time by 58%, and improve the noise reduction by 25% compared with the conventional PID control. Compared with the PSO fuzzy PID control algorithm without UKF noise reduction, the optimized scheme reduces the overshoot by 20%, shortens the regulation time by 48%, and improves the noise reduction effect by 23%. The results show that the PSO fuzzy PID control method with integrated UKF has superior control performance in terms of system stability and accuracy. The algorithm significantly improves the responsiveness and stability of diesel engine speed, achieves better control effect in the optimization of diesel engine speed control, and provides a useful reference for the optimization of other diesel engine control systems. In addition, this study establishes the GT-POWER model of a 168 F single-cylinder diesel engine, and compares the cylinder pressure and fuel consumption under four operating conditions through bench tests to ensure the physical reasonableness of the kinetic input parameters and avoid algorithmic optimization on the distorted front-end model. Full article

Maintaining the long-term viability of a wheat–maize planting system, particularly the synchronous improvement of crop production and soil organic carbon (SOC) sequestration, is crucial for ensuring food security in the North China Plain. A field experiment in which wheat–maize was regarded as an integral fertilization unit was carried out in Shanxi Province, China, adopting a split-plot design with different distribution ratios of phosphorus (P) and potassium (K) fertilizer between wheat and maize seasons in the main plot (A) (a ratio of 3:0, A1; a ratio of 2:1, A2) and different application rates of pure nitrogen (N) during the entire wheat and maize growth period (B) (450 kg·ha⁻¹, B1; 600 kg·ha⁻¹, B2). Moreover, no fertilization was used in the entire wheat and maize growth period for the control (CK). The findings showed that A2B1 treatment led to the highest response, with an average wheat yield of 7.75 t·ha⁻¹ and an average maize yield of 8.40 t·ha⁻¹ over the last 9 years. The highest SOC content (15.13 g·kg⁻¹), storage (34.20 t·ha⁻¹), and sequestration (7.11 t·ha⁻¹) were also observed under the A2B1 treatment. Both enhanced crop yield and SOC sequestration resulted from improvements in cumulative carbon (C) input, soil nutrients, and stoichiometry under the A2B1 treatment. It was confirmed that total N (TN), alkali-hydrolysable N (AN), available P (AP), available K (AK), and the ratios of C:K, N:K, and N:P had positive effects on crop yield through the labile components of SOC and on SOC sequestration through microbial necromass C. To conclude, our findings highlight the urgent need to optimize fertilizer management strategies to improve crop production and SOC sequestration in the North China Plain. Full article

Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are highly prevalent chronic conditions, frequently coexisting due to their shared pathophysiological mechanisms and risk factors. Epidemiological studies estimate that up to 30% of COPD patients have comorbid T2DM, contributing to worsened disease progression, more hospitalizations, and higher mortality rates. Systemic inflammation in COPD contributes to insulin resistance by increasing pro-inflammatory cytokines (TNF-α, IL-6, and CRP), which impair glucose metabolism and beta-cell function. Conversely, hyperglycemia in T2DM exacerbates oxidative stress, leading to endothelial dysfunction, reduced lung function, and impaired pulmonary repair mechanisms. A comprehensive narrative review was conducted to evaluate the interplay between COPD and T2DM, examining shared pathophysiological mechanisms, clinical consequences, and management strategies. The co-occurrence of COPD and T2DM accelerates disease development, elevates hospitalization rates, and deteriorates overall prognosis. Pharmacological interactions complicate illness treatment, requiring a multidisciplinary therapy strategy. Recent data underscore the need to integrate palliative care, facilitate shared decision-making, and provide psychological support to enhance patient outcomes. Efficient therapy of COPD-T2DM comorbidity necessitates a customized, interdisciplinary strategy that targets both respiratory and metabolic health. Preliminary prognostic dialogues, palliative care, and holistic lifestyle modifications can improve patient quality of life and clinical results. Full article

This paper presents findings from the LEOPARD project, part of the LEAP-RE program, a joint European Union (EU) and African Union initiative to advance renewable energy solutions. The study employs a simulation-based approach to optimize solar-integrated microgrid configurations for rural electrification. The project deployed a solar-integrated pilot microgrid at the Songhai agroecological center in Benin to address key challenges, including load profile estimation, energy balancing, and diesel dependency reduction. A hybrid methodology integrating predictive modeling, real-time solar and weather data analysis, and performance simulations was employed, leading to a 65% reduction in diesel reliance and an LCOE of EUR 0.47/kWh. Quality control measures, including compliance with IEC 61215 and IEC 62485-2 standards, ensured system reliability under extreme conditions. Over 150 days, the system consistently supplied energy, preventing 10.16 tons of ${CO}_2$ emissions. Beyond the Benin pilot, the project conducted feasibility assessments in Senegal to evaluate microgrid replicability across different socio-economic and environmental conditions. These analyses highlight the scalability potential and the economic viability of expanding solar microgrids in rural areas. Additionally, this research explores innovative business models and real-time diagnostics to enhance microgrid sustainability. By providing a replicable framework, it promotes long-term energy access and regional adaptability. With a focus on community involvement and capacity building, this study supports efforts to reduce energy poverty, strengthen European–African collaboration, and advance the global clean energy agenda. Full article

The integration of power electronic equipment with complex internal structures, which are represented by switching elements or black-box models, is increasing because of the growing penetration of renewable energy into the power grid. The increase in model complexity causes greater computational workload and presents challenges for grid stability analysis. To address this issue, this paper proposes a method for estimating the parameters of a simple generic model capable of emulating the dynamic behavior of complex power-electronic models. For the estimation, the frequency scanning method is utilized, involving the injection of various frequency inputs into the complex model. The responses obtained are then utilized in the optimization process as the objective function. The use of frequency scanning is reasonable because it can cover a wide frequency range, thus comprehensively capturing the dynamic properties of the model. The optimization process aims to minimize the difference in responses to frequency scanning between the complicated and simple generic models. The accuracy of the generic model with estimated parameters is verified by Bode plot comparison and time-domain simulations. Simulation results demonstrated that the generic model, optimized via parameter estimation using the frequency scanning method, accurately replicated the response of the reference model, particularly in the low-frequency range. The proposed method allows for the integration of power electronic equipment, which may represent switching-based components or lack internal information, into stability analysis using existing power-system analysis tools. Full article

Accurate estimation of accelerometer biases in Inertial Measurement Units (IMUs) is crucial for reliable Unmanned Aerial Vehicle (UAV) navigation, particularly in GPS-denied environments. Uncompensated biases lead to an unbounded accumulation of position error and increased velocity error, resulting in significant navigation inaccuracies. This paper examines the effects of accelerometer bias on UAV navigation accuracy and introduces a vision-aided navigation system. The proposed system integrates data from an IMU, altimeter, and optical flow sensor (OFS), employing an Extended Kalman Filter (EKF) to estimate both the accelerometer biases and the UAV position and velocity. This approach reduces the accumulation of velocity and positional errors. The efficiency of this approach was validated through simulation experiments involving a UAV navigating in circular and straight-line trajectories. Simulation results show that the proposed approach significantly enhances UAV navigation performance, providing more accurate estimates of both the state and accelerometer biases while reducing error growth through the use of vision aiding from an Optical Flow Sensor. Full article

Green hydrogen is a promising energy carrier for the decarbonization of hard-to-abate sectors and supporting renewable energy integration, aligning with carbon neutrality goals like the European Green Deal. Iceland’s abundant renewable energy and decarbonized electricity system position it as a strong candidate for green hydrogen production. Despite early initiatives, its hydrogen economy has yet to significantly expand. This study evaluated Iceland’s hydrogen development through stakeholder interviews and a techno-economic analysis of alkaline and PEM electrolyzers. Stakeholders were driven by decarbonization goals, economic opportunities, and energy security but faced technological, economic, and governance challenges. Recommendations include building stakeholder confidence, financial incentives, and creating hydrogen-based chemicals to boost demand. Currently, alkaline electrolyzers are more cost-effective (EUR 1.5–2.8/kg) than PEMs (EUR 2.1–3.6/kg), though the future costs for both could drop below EUR 1.5/kg. Iceland’s low electricity costs and high electrolyzer capacity provide a competitive edge. However, this advantage may shrink as solar and wind costs decline globally, particularly in regions like Australia. This work’s findings emphasize the need for strategic planning to sustain competitiveness and offer transferable insights for other regions introducing hydrogen into ecosystems lacking infrastructure. Full article

In this paper, a nonlinear system is interpreted as an operator $ℱ$ transforming random vectors. It is assumed that the operator is unknown and the random vectors are available. It is required to find a model of the system represented by a best constructive operator $ℱ$ approximation. While the theory of operator approximation with any given accuracy has been well elaborated, the theory of best constrained constructive operator approximation is not so well developed. Despite increasing demands from various applications, this subject is minimally tractable because of intrinsic difficulties with associated approximation techniques. This paper concerns the best constrained approximation of a nonlinear operator in probability spaces. The main conceptual novelty of the proposed approach is that, unlike the known techniques, it targets a constructive optimal determination of all $3p+2$ ingredients of the approximating operator where p is a nonnegative integer. The solution to the associated problem is represented by a combination of new best approximation techniques with a special iterative procedure. The proposed approximating model of the system has several degrees of freedom to minimize the associated error. In particular, one of the specific features of the developed approximating technique is special random vectors called injections. It is shown that the desired injection is determined from the solution of a special Fredholm integral equation of the second kind. Its solution is called the optimal injection. The determination of optimal injections in this way allows us to further minimize the associated error. Full article

The use of non-invasive methods can contribute to the development of predictive models for measuring carcass yield (CY) and hot carcass weight (HCW) in domestic ruminants. In this study, in vivo measurements of subcutaneous fat thickness (SFT) and ribeye area (REA) were performed on 111 Nellore heifers using ultrasound imaging. The animals were managed in crop–livestock integrated systems with different supplementation levels (SL). Four multiple regression equations were developed to estimate CY and HCW, using five predictor variables: SFT, REA, REA per 100 kg of body weight (REA100), live weight (LW), and SL. For the CY prediction models, when ultrasound measurements (SFT, REA, and REA100) were considered, the generated equations showed low R² and concordance correlation coefficient (CCC) values, indicating low predictive capacity for this trait. For HCW, the predictor variables stood out due to their high R² values. Additionally, the equation based solely on ultrasound measurements achieved a CCC greater than 0.800, demonstrating high predictive capacity. Based on these results, it can be concluded that ultrasound-derived measurements are effective for generating useful models to predict HCW. Thus, it will be possible to estimate the amount of carcass that will be produced even before the animals are sent to slaughterhouses. Full article

Saudi Arabia’s rapid urbanization and economic growth have increased the number of petrol stations crucial to national infrastructure. Despite oversight from seven local authorities, many stations fail to meet Ministry of Municipal and Rural Affairs (MMRA) standards due to decentralized management. This study develops a Condition Rating Index (CRI) for petrol stations, designed to serve as the backbone of a comprehensive decision support system for the operation and rehabilitation processes of petrol stations in Saudi Arabia. It is based on dividing petrol stations into four key areas: refueling tanks, pump stations, car service buildings, and commercial spaces. Performance factors for each area are identified and categorized hierarchically into main and sub-factors. The Analytical Hierarchy Process (AHP) is used to determine relative importance weights for these factors, while Multi-Attribute Utility Theory (MAUT) is used to assign utility scores (1–10 scale) reflecting performance levels, where 1 is poor, and 10 is optimal. The overall CRI for each petrol station is calculated by aggregating the scores of all four spaces, combining their relative importance weights with the specific CRI scores aligned with each factor’s utility level. These space-specific CRI scores reveal particular performance levels and rehabilitation needs for each area. The developed CRI functions as a transparent, integrated tool for effectively communicating performance levels and rehabilitation needs among all stakeholders. It serves as an effective decision support tool for prioritizing rehabilitation interventions based on performance levels and budget constraints, offering a comprehensive approach for enhancing petrol station management across Saudi Arabia. This paper develops a transparent and adaptable Condition Rating Index (CRI) that bridges gaps in petrol station management and aligns with sustainability goals. Full article

This paper explores the application of the ESP32 microcontroller in edge computing, focusing on the design and implementation of an edge server system to evaluate performance improvements achieved by integrating edge and cloud computing. Responding to the growing need to reduce cloud burdens and latency, this research develops an edge server, detailing the ESP32 hardware architecture, software environment, communication protocols, and server framework. A complementary cloud server software framework is also designed to support edge processing. A deep learning model for object recognition is selected, trained, and deployed on the edge server. Performance evaluation metrics, classification time, MQTT (Message Queuing Telemetry Transport) transmission time, and data from various MQTT brokers are used to assess system performance, with particular attention to the impact of image size adjustments. Experimental results demonstrate that the edge server significantly reduces bandwidth usage and latency, effectively alleviating the load on the cloud server. This study discusses the system’s strengths and limitations, interprets experimental findings, and suggests potential improvements and future applications. By integrating AI and IoT, the edge server design and object recognition system demonstrates the benefits of localized edge processing in enhancing efficiency and reducing cloud dependency. Full article

This paper evaluates the role of federated satellite systems (FSSs) in enhancing unmanned vehicle-supported military medical evacuation (MEDEVAC) missions. An FSS integrates multiple satellite systems, thus improving imaging and communication capabilities compared with standalone satellite systems. A simulation model is developed for a MEDEVAC mission where the FSS control of an unmanned aerial vehicle is distributed across different countries. The model is utilized in a simulation experiment in which the capabilities of the federated and standalone systems in MEDEVAC are compared. The performance of these systems is evaluated by using the most meaningful metrics, i.e., mission duration and data latency, for evacuation to enable life-saving procedures. The simulation results indicate that the FSS, using low-Earth-orbit constellations, outperforms standalone satellite systems. The use of the FSS leads to faster response times for urgent evacuations and low latency for the real-time control of unmanned vehicles, enabling advanced remote medical procedures. These findings suggest that investing in hybrid satellite architectures and fostering international collaboration promote scalability, interoperability, and frequent-imaging opportunities. Such features of satellite systems are vital to enhancing unmanned vehicle-supported MEDEVAC missions in combat zones. Full article

Accurate and objective evaluation of existing bridges is critical for ensuring the bridge’s safety and optimizing maintenance strategies. This study proposes an integrated Fuzzy Best and Worst Method and fuzzy comprehensive evaluation (FBWM-FCE) model to evaluate uncertainties in expert judgments and complex decision-making. A four-layer evaluation indicator system and five distinct grades for bridges were established, aligned with the JTG 5120-2004 and JTG/T H21-2011 standards. The FBWM innovatively employs triangular fuzzy numbers (TFNs) to reduce linguistic uncertainties and cognitive bias in bridge evaluation. Subsequently, by integrating FCE for multi-level fuzzy comprehensive operations, the method translates qualitative evaluations into quantitative evaluations using membership matrices and weights. A case study of Ding Jia Bridge and Jigongling Bridge validated the FBWM-FCE model, revealing Class III Bridge (fail condition), consistent with on-site inspections in the 2020 Bridge Inspection and Evaluation Report (Highway Administration of Hubei Provincial Department of Transportation). Comparative analysis demonstrated FBWM’s operational efficiency, requiring 20% fewer pairwise comparisons than AHP while maintaining higher consistency than BWM. The model’s reliability stems from its systematic handling of epistemic uncertainties, offering a high reduction in procedural complexity compared to standardized methods. These advancements provide a scientifically rigorous yet practical tool for bridge management, balancing computational efficiency with evaluation accuracy to support maintenance decisions. Full article

Conventional machines often face limitations due to complex controllers and bulky power supplies, which can hinder their reliability and operability. In contrast, self-excited movements can harness energy from a stable environment for self-regulation. In this study, we present a novel model of a self-rowing boat inspired by paddle boats. This boat is powered by a liquid crystal elastomer (LCE) turntable that acts as a motor and operates under consistent illumination. We investigated the dynamic behavior of the self-rowing boat under uniform illumination by integrating the photothermal reaction theory of LCEs with a nonlinear dynamic framework. The primary equations were solved using the fourth-order Runge–Kutta method. Our findings reveal that the model exhibits two modes of motion under steady illumination: a static pattern and a self-rowing pattern. The transition between these modes is influenced by the interaction of the driving and friction torques generated by photothermal energy. This study quantitatively analyzes the fundamental conditions necessary for initiating a self-rowing motion and examines how various dimensionless parameters affect the speed of the self-rowing system. The proposed system offers several unique advantages, including a simple structure, easy control, and independence from electronic components. Furthermore, it has the potential for miniaturization and integration, enhancing its applicability in miniature machines and systems. Full article