Search Results (49)

To address the challenges of enhancing driving stability and energy efficiency in distributed-drive electric vehicles, this paper proposes an extenics coordinated torque distribution control method that integrates energy efficiency optimization and vehicle stability. The primary contribution was the development of a vehicle stability assessment method grounded in extenics control theory, which was used to obtain the vehicle’s phase plane and stability region. Subsequently, an objective function with constraints for in-wheel motor torque distribution was formulated, targeting both optimal energy efficiency and maximum tire stability margin. Furthermore, the extension distances from the actual vehicle state to the stability boundaries were computed to determine adaptive weighting coefficients for these dual objectives. Finally, a Matlab/Simulink 2018a and Carsim2019 co-simulation platform was built to implement and test the proposed method. Simulations under the NEDC urban driving cycle and double-lane-change driving conditions were conducted to evaluate the following three distribution strategies: energy-optimal, stability-oriented, and extenics coordinated control. The results demonstrated that, regarding vehicle stability performance, extenics coordinated control showed a slightly inferior performance to the stability-oriented approach but substantially outperformed the energy-optimal strategy. In terms of energy consumption, the energy-optimal strategy achieved the lowest loss and the stability-oriented strategy showed the highest, while the extenics coordinated control presented intermediate results of 5.4 × 10⁹ J and 9.7 × 10⁷ J, respectively, under two driving conditions, representing reductions of 2.17% and 11.2% compared to the stability-oriented method. The proposed torque distribution method establishes an effective balance between energy-optimal and stability-oriented objectives. This method not only ensures satisfactory driving stability, but also reduces energy loss in in-wheel motors. Full article

The spatial mismatch between the supply and demand of rural values is a key cause of the rural identity crisis. Promoting a shift in rural value research from a resource-oriented to a subject-perception-oriented approach is a crucial pathway to addressing this crisis. From the perspective of subjective perception, this study introduces the concept of rural social values (RSVs). Taking Yangzhong City, Jiangsu Province, as a case study, the SolVES model, comparative analysis, and structural equation modeling (SEM) were employed to investigate the spatial matching between RSV supply and demand. The main findings are as follows: (1) RSV supply exhibits a complex pattern characterized by “ecological baseline constraints” and “urban–rural boundary differentiation”; (2) RSV demand is shaped by both the collective expectations of subjects and the actual supply level of rural areas; (3) RSV supply–demand matching exhibits a complex situation coexisting with universal deficits, structural surpluses, and regional misalignments; (4) geographical environment and socio-economic conditions are key factors influencing the spatial matching between supply and demand at the village level, while the impact of individual characteristics is overshadowed by the overall village environment. This study not only provides a new theoretical perspective for understanding the rural value identity crisis, but also offers practical references for rural spatial governance in Yangzhong City and similar regions. Full article

In industrial processes, mismatches between models and actual systems often degrade the performance of Model Predictive Control (MPC), potentially leading to instability or safety violations under dynamic operating conditions. To address this challenge, the paper introduces a hybrid control architecture named Trans-Tube-MPC, which leverages Transformer-based temporal modeling and tube-based robust constraints to enhance the robustness of the control system against model failures. The approach employs a Transformer network trained on closed-loop operational data to predict and compensate for state deviations caused by disturbances, while adaptive tube constraints dynamically adjust prediction boundaries to mitigate the risk of overcorrection. The innovation of this method lies in the introduction of a dynamically adjusted tube width, which adapts based on the prediction discrepancy between the Transformer model and the state-space model, thus allowing the control system to remain robust even in the face of model failures. Experimental studies demonstrate that the Trans-Tube-MPC framework can maintain control performance under significant model parameter deviations where conventional MPC would fail. The proposed method provides an effective solution to the problem of model mismatch and prediction error and shows significant advantages in dealing with control issues under model failure conditions, establishing a new way to reconcile data-driven adaptability with the reliability of control systems. Full article

The article is devoted to the issues of designing the exploitation of a seam deposit in the boundary areas of underground mines in terms of minimizing the risk of dynamic phenomena. Its main goal was to attempt to demonstrate the relationship between the method of extracting resources trapped in the boundary pillar and the magnitude of the induced seismicity of the rock mass accompanying this process. The substantive considerations concerned the single-wall model and were divided into two main parts—theoretical and verification. As part of the theoretical piece, based on model studies, a geomechanical assessment of the impact of the working face advance on changes in the stress–strain behaviour occurring in the burst-prone layer in terms of the possible loss of continuity of its original structure was carried out. The starting point for the key analyses were the results of numerical simulations based on the algorithms of S. Knothe and W. Budryk’s theories in combination with classical solutions of the mechanics of deformable bodies. Two variants of mining operations in a two-sided environment of goaf were considered, differing in the direction of progress, the degree of constraint of the start and end of the face advance, and mining circumstances in the vicinity of both sides of the advancing face. As part of the verification piece, the results of model analyses were related to an example polygon of a crossing longwall in one of the functioning, rockburst USCB hard coal mines. The scope of the research included a comparison of the experimentally indicated zones of occurrence of tremor-favourable effort processes in the roof of the seam with the actual location of the seismic phenomena foci recorded during the ongoing exploitation. The considerations included in the work formed the basis for formulating conclusions of a cognitive and applicable nature. Full article

To address the limitations of conventional single-track rail systems in challenging hilly and mountainous terrains, which are ill-suited for transporting heavy agricultural machinery, there is a critical need to develop a specialized the double-track rail transportation system optimized for orchard equipment. Recognizing this requirement, our research team designed and implemented a double-track rail transportation system. In this innovative system, the rail functions as the pivotal component, with its structural properties significantly impacting the machine’s overall stability and operational performance. In this study, resistance strain gauges were employed to analyze the stress–strain distribution of the track under a full load of 750 kg, a critical factor in the system’s design. To further investigate the structural performance of the double-track rail, the impact hammer method was utilized in conjunction with triaxial acceleration sensors to conduct experimental modal analysis (EMA) under actual support conditions. By integrating the Eigensystem Realization Algorithm (ERA), the first 20 natural modes and their corresponding parameters were successfully identified with high precision. A comparative analysis between finite element simulation results and experimental measurements was performed, revealing the double-track rail’s inherent vibration characteristics under constrained modal conditions versus actual boundary constraints. These valuable findings serve as a theoretical foundation for the dynamic optimization of rail structures and the mitigation of resonance issues. The advancement of hilly and mountainous rail transportation systems holds significant promise for enhancing productivity and transportation efficiency in agricultural operations. Full article

Modern fighter aircraft have an increasing need for at least a moderate level of stealth, and the shape design must bear a part of this constraint. However, the high frequency of close range radar makes high-fidelity radar cross-section computation methods such as the boundary element method too expensive to use in a gradient-free optimization process. On the other hand, asymptotic methods are not able to accurately predict the RCS of complex shapes such as intake cavities. Hence, the need arises for efficient and accurate methods to compute the gradient of high-fidelity radar cross-section computation methods with respect to shape parameters. In this paper, we propose an adjoint formulation for the boundary element method to efficiently compute these gradients. We present a novel approach to calculate the gradient of high-fidelity radar cross-section computations using the boundary element method. Our method employs an adjoint formulation that allows for the efficient computation of these gradients. This is particularly beneficial in shape optimization problems where accurate and efficient methods are crucial to designing modern fighter aircraft with stealth capabilities. By avoiding the need for solving the actual adjoint problem in certain cases, our formulation provides a more streamlined solution while still maintaining high accuracy. We demonstrate the effectiveness of our method by performing shape optimization on various shapes, including simple geometries like spheres and ellipsoids, as well as complex aircraft shapes with multiple variables. Full article

Vibration test jigs are essential components for evaluating the dynamic performance and durability of automotive parts, such as lamps. This study aimed to derive optimal jig configurations that simultaneously maximize natural frequency and minimize structural weight through topology optimization. A fixed-grid finite-element model was constructed by incorporating realistic lamp mass and boundary conditions at the mounting interfaces to simulate actual testing scenarios. Four optimization formalizations were investigated: (1) compliance minimization, (2) compliance minimization with natural-frequency constraints, (3) natural-frequency maximization, and (4) natural-frequency maximization with compliance constraints. Both full-domain and reduced-domain designs were analyzed to assess the influence of domain scope. The results indicate that formulations that use only natural-frequency objectives often result in shape divergence and convergence instability. In contrast, strategies incorporating frequency as a constraint—particularly compliance minimization with a natural-frequency constraint—exhibited superior performance by achieving a balance between stiffness and weight. Furthermore, the reduced-domain configuration enhanced the natural frequency owing to the greater design freedom, although this resulted in a trade-off of increased weight. These findings underscore the importance of selecting appropriate formalization strategies and domain settings to secure reliable vibration performance and support the necessity of multi-objective optimization frameworks for the practical design of vibration-sensitive structures. Full article

This paper presents a meshless Galerkin method for analyzing the nonlinear behavior of corrugated sandwich plates. A corrugated sandwich plate is a composite structure comprising two flat face sheets and a corrugated core, which can be approximated as an orthotropic anisotropic plate with distinct elastic properties in two perpendicular directions. The formulation is based on the first-order shear deformation theory (FSDT), where the shape functions are constructed using the moving least-square (MLS) approximation. Nonlinear stress and strain expressions are derived according to von Kármán’s large deflection theory. The virtual strain energy functionals of the individual plates are established, and their nonlinear equilibrium equations are formulated using the principle of virtual work. The governing equations for the entire corrugated sandwich structure are obtained by incorporating boundary conditions and displacement continuity constraints. A Newton–Raphson iterative scheme is employed to solve the nonlinear equilibrium equations. The computational program is implemented in C++, and extensive numerical examples are analyzed. The accuracy and reliability of the proposed method are validated through comparisons with ANSYS finite element solutions using SHELL181 elements. The method used in this paper can avoid the problems of mesh reconstruction and mesh distortion in the finite element method. In practical application, it simplifies the simulation calculation and understands the mechanical behavior of sandwich plates closer to actual engineering practice. Full article

An approximate compact model was developed to provide a convenient method of exploring the initial design space when investigating the performance of micro-electronic devices such as nano-scaled piezoelectronic transistors, where fast ball-park estimates can be very helpful. First of all, the compact model was verified by comparing its predictions with those of accurate axi-symmetric finite element analysis (FEA) using special boundary and interface conditions that enable the replication of the analytical model behaviour. Verification is achieved for a radio frequency (RF) switch and a smaller very-large-scale integrated (VLSI) device, where percentage differences between the compact and FEA model predictions are of the order 10⁻⁴ for the RF switch and 10⁻⁵ for the VLSI device. This confirms the consistency of complex property data (especially electro-thermo-elastic constants) and geometrical parameter input to both types of models and convincingly demonstrates that the analytical models and FEA for the two devices have been implemented correctly. A second type of boundary and interface condition is also used that is designed to replicate the actual behaviour of the devices in practice. The boundary and interface constraints applied for the verification procedure are relaxed so that there is perfect interface bonding between layers. For this unconstrained case, the resulting deformation is very complex, involving both bending effects and edge effects arising from property mismatches between neighbouring layers. The results for the RF switch show surprisingly good agreement between the predictions of the analytical and FEA results, provided the thickness of the piezoelectric layer is not too thick, implying that the analytical model should help to reduce the parameter design space for such devices. However, for the VLSI device, our results indicate that the compact model leads to much larger errors. For such systems, the compact model is unlikely to be able to reliably reduce the parameter design space, implying that accurate FEA will then need to be used. Full article

In actual industry applications, the failure categories of practical equipment are usually a subset of laboratory conditions failure categories. Due to the strict constraints, partial transfer learning can address a more practical diagnostic scenario. In view of this, this paper proposes a target domain-specific classifier weight partial transfer adversarial network. Initially, the 1-D convolutional neural network is employed as the basic architecture. By training the domain discriminator and feature generator with an adversarial strategy, the recognition ability of the domain discriminant network and the feature extraction ability of the feature generation network can be enhanced. After that, a weighted learning strategy is introduced to guide the model to learn the cross-domain invariant feature. Also, a specific target domain classifier is utilized to redivide the target domain decision boundary to accurately classify the unlabeled target domain samples. Finally, five mainstream deep neural network methods are taken for comparison using the data from Western Reserve University and the motor-magnetic brake test designed by us. The results show that the proposed method reaches 90.18% and 96.53% classification accuracy on two datasets, respectively, which demonstrates superior performance compared with the state-of-the-art methods. Full article

A good quantitative knowledge of regional sources and sinks of atmospheric carbon dioxide (CO₂) is essential for understanding the global carbon cycle. It is also a key prerequisite for elaborating cost-effective national strategies to achieve the goals of the Paris Agreement. However, available estimates of CO₂ fluxes for many regions of the world remain uncertain, despite significant recent progress in the remote sensing of terrestrial vegetation and atmospheric CO₂. In this study, we investigate the feasibility of inferring reliable regional estimates of the net ecosystem exchange (NEE) using column-averaged dry-air mole fractions of CO₂ (XCO₂) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations as constraints on parameters of the widely used Vegetation Photosynthesis and Respiration model (VPRM), which predicts ecosystem fluxes based on vegetation indices derived from multispectral satellite imagery. We developed a regional-scale inverse modeling system that applies a Bayesian variational optimization algorithm to optimize parameters of VPRM coupled to the CHIMERE chemistry transport model and which involves a preliminary transformation of the input XCO₂ data that reduces the impact of the CHIMERE boundary conditions on inversion results. We investigated the potential of our inversion system by applying it to a European region (that includes, in particular, the EU countries and the UK) for the warm season (May–September) of 2021. The inversion of the OCO-2 observations resulted in a major (more than threefold) reduction of the prior uncertainty in the regional NEE estimate. The posterior NEE estimate agrees with independent estimates provided by the CarbonTracker Europe High-Resolution (CTE-HR) system and the ensemble of the v10 OCO-2 model intercomparison (MIP) global inversions. We also found that the inversion improves the agreement of our simulations of XCO₂ with retrievals from the Total Carbon Column Observing Network (TCCON). Our sensitivity test experiments using synthetic XCO₂ data indicate that the posterior NEE estimate would remain reliable even if the actual regional CO₂ fluxes drastically differed from their prior values. Furthermore, the posterior NEE estimate is found to be robust to strong biases and random uncertainties in the CHIMERE boundary conditions. Overall, this study suggests that our approach offers a reliable and relatively simple way to derive robust estimates of CO₂ ecosystem fluxes from satellite XCO₂ observations while enhancing the applicability of VPRM in regions where eddy covariance measurements of CO₂ fluxes are scarce. Full article

Urban rail transit passenger flow forecasting often relies on the traditional “four-step” method, where the division of traffic analysis zones (TAZs) is critical to ensuring prediction accuracy. As the fundamental units for describing trip origins and destinations, TAZs also encompass socioeconomic attributes such as land use, population, and employment. However, traditional TAZs, typically based on administrative boundaries, fail to reflect evolving urban travel behavior, particularly when transit stations are located near TAZ boundaries. Additionally, the emergence of urban big data allows for more refined spatial analyses based on individual travel patterns, addressing the limitations of administrative divisions. This study proposes an innovative TAZ aggregation model based on travel similarity, integrating public transit smart-card data and GIS data from bus networks. First, individual spatiotemporal travel patterns are mapped and discretized in both the spatial and temporal dimensions. Travel characteristic data are then extracted for spatial grid units. The TAZ division problem is defined as a multiobjective optimization problem, including factors such as travel similarity, the homogeneity of travel intensity, the statistical accuracy of the area, geographic information preservation, travel ratio constraints, and shape constraints. Multiple TAZ division schemes are produced and assessed using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), resulting in the selection of the optimal scheme. The proposed method is implemented on bus passenger travel data in Beijing, showing that the optimized scheme significantly reduces the number of zones with travel ratios exceeding 10%. Compared with existing schemes, the optimized division yields more uniform distributions of travel ratios, area, and travel density, while significantly minimizing the number of zones with a high travel concentration. These results demonstrate that the proposed method better reflects residents’ actual travel behaviors, offering a notable improvement over traditional approaches. This research provides a novel and practical framework for data-driven TAZ optimization. Full article

This paper investigates the best control method of the lowest specific fuel consumption (SFC) to reduce the specific fuel consumption of the triple-bypass variable cycle engine. Specific fuel consumption is the ratio of fuel flow to thrust. First, the Kriging model of the engine near the supersonic cruise and subsonic cruise state points was extracted using the component-level model of the triple-bypass variable cycle engine, and the PSM was obtained close to the steady-state point. The contribution of each control variable to the engine’s specific fuel consumption was computed using the PSM and, at the same time, due to the linear characteristics of the PSM, it was easy to deal with various constrained linear optimization problems, and the steady-state points with the smallest specific fuel consumption under the constraints could be obtained through the linear optimization algorithm; however, the surge margin and pre-turbine temperature of the optimized point were limited in the optimization process, the method of direct switching inevitably brought the problem of overshoot of the controlled quantity, and the actual controlled quantity could still exceed the safe operation boundary of the engine in the process of change. Moreover, the performance optimization control itself is premised on sacrificing the surge margin of the engine, and its operating boundary is closer to the surge line, so the limitation protection problem in the transition state cannot be ignored in the process of performance optimization control. In this paper, a multivariable steady-state controller was designed based on Model Predictive Control (MPC) to meet the needs of engine optimization control mode switching. The simulation results of the supersonic cruise mode show that the minimum fuel consumption control can reduce the fuel consumption of the engine by 2.6% while the thrust remains constant. Full article

Multi-agent pathfinding has been extensively studied by the robotics and artificial intelligence communities. The classical algorithm, conflict-based search (CBS), is widely used in various real-world applications due to its ability to solve large-scale conflict-free paths. However, classical CBS assumes discrete time–space planning and overlooks physical constraints in actual scenarios, making it unsuitable for direct application in unmanned aerial vehicle (UAV) swarm. Inspired by the decentralized planning and centralized conflict resolution ideas of CBS, we propose, for the first time, an optimal and efficient UAV swarm motion planner that integrates state lattice with CBS without any underlying assumption, named SL-CBS. SL-CBS is a two-layer search algorithm: (1) The low-level search utilizes an improved state lattice. We design emergency stop motion primitives to ensure complete UAV dynamics and handle spatio-temporal constraints from high-level conflicts. (2) The high-level algorithm defines comprehensive conflict types and proposes a motion primitive conflict detection method with linear time complexity based on Sturm’s theory. Additionally, our modified independence detection (ID) technique is applied to enable parallel conflict processing. We validate the planning capabilities of SL-CBS in classical scenarios and compare these with the latest state-of-the-art (SOTA) algorithms, showing great improvements in success rate, computation time, and flight time. Finally, we conduct large-scale tests to analyze the performance boundaries of SL-CBS+ID. Full article

A three-dimensional elastic–plastic finite element model of a six-roll cold rolling mill has been developed using the finite element software ABAQUS. The actual parameters of the rolling mill have been incorporated into the finite element model, with the working conditions applied as boundary constraints and load conditions. Subsequently, a non-symmetrical bending force is introduced to the finite element model. Through simulation calculations, this study analyzes the patterns of change in the transverse pressure of the rolling mill and roller pressure during non-symmetrical bending, as well as the variations in strip thickness, crown, edge drop, and flatness. Additionally, the regulating function of the bending force is examined. Each adjustment of 5 t in the asymmetric bending force results in an increase of approximately 0.01 mm in the thickness of the positive bending side of the strip while causing a decrease of about 0.01 mm in the thickness of the negative bending side. Therefore, the application of asymmetric bending forces proves to be effective in controlling the shape of lateral wave defects on the edges of steel strips. Full article