Search Results (987)

Mitigating heat stress in high-density historical districts remains a critical challenge in urban renewal due to complex morphological heterogeneity. Existing research often relies on isolated intervention measures, lacking systematic, multi-strategy assessments driven by high-precision spatial data. This study addresses this gap by establishing a quantitative framework that couples thermal infrared remote sensing with Computational Fluid Dynamics (CFD) to optimize microclimate responses in Beijing’s Liulichang Historic District. Remote sensing data were utilized to retrieve high-resolution Land Surface Temperature (LST), providing accurate thermal boundary conditions for micro-scale wind-thermal simulations. A baseline scenario (S0) and seven renewal strategies (S1–S7)—integrating varying configurations of greenery, water bodies, and permeable pavements—were evaluated using pedestrian-level comfort indices. Results reveal that single-factor interventions yield marginal improvements or thermodynamic trade-offs; specifically, adding greenery (S1) in narrow street canyons increased aerodynamic roughness, thereby obstructing ventilation and inducing localized warming. Conversely, composite strategies significantly enhanced microclimatic quality. The “greenery-water-permeable pavement” strategy (S4) achieved optimal synergistic effects, characterized by substantial cooling and spatial homogenization. Regression analysis identified water bodies as the dominant cooling driver, where a 10% increase in water coverage resulted in a temperature reduction of approximately 5.17 °C. Conversely, greenery alone showed no statistically significant cooling contribution (p > 0.05) without the synergistic presence of water or pavement modifications. This research suggests that urban renewal in high-temperature zones (>36 °C) should prioritize composite cooling networks. Furthermore, vegetation layouts near wind corridors must be precisely regulated to prevent ventilation degradation. These findings provide a scientific basis for the climate-adaptive sustainable regeneration of culturally significant, high-density urban blocks. Full article

Engineering drawings are fundamental to industries such as oil and gas, construction, and manufacturing. However, current practices relying on manual design or rigid parametric templates often suffer from inefficiency and layout inconsistencies. To address these issues, the layout task is formulated as the Orthogonal Rectangle Packing Problem with Multiple Configurations and Complex Constraints (ORPPMC). The Deep Reinforcement Learning for Multi-Configuration Drawing Layout (DRL-MCDL) framework is proposed, which integrates the Pointer Network for Drawing Element Sequencing (PN-DES) with the Target-Type-Matching-based Multi-Pattern Positioning Strategy (TTM-MPPS). Within this framework, PN-DES employs deep reinforcement learning and feature fusion to combine element attributes with layout configurations for optimal sequence inference, while TTM-MPPS performs precise positioning in accordance with industrial rules to ensure strict adherence to aesthetic requirements. Ablation experiments validate the contribution of each module. Experimental results on real-world engineering drawings demonstrate that DRL-MCDL achieves a Feasibility Rate (FR) exceeding 98.5% on standard instances (12–40 elements), significantly outperforming traditional methods. Furthermore, it maintains a high inference efficiency with an Average Time (AT) of less than 0.3 s, striking an optimal balance between layout quality and computational speed. Full article

The strong electromagnetic interference environment on the battlefield has brought new challenges to the networking collaboration of jammers and the estimation of jamming effects. Traditional successful jamming indicators are difficult to meet the needs of continuous, low-power, and flexible jamming, causing difficulties in emergency scheduling of jamming resources. Aiming at the overall degradation of the communication party’s signal reception quality, this paper proposes the restrictive conditions of “overall limited jamming” and the analysis and evaluation index of “multistage jamming-to-signal ratio (J/S)”, which meets the scheduling requirements of distributed jamming resources in harsh environments. Based on the jammer layout that can achieve overall high-intensity jamming, the electromagnetic environment estimation, power scheduling, and collaboration strategies of jammers are designed, a communication countermeasure game algorithm under blocked networking collaboration is established, and the independent dynamic scheduling of jamming resources is realized. The experimental results show that the Concentric Circle Broadcasting Algorithm (CCBA) not only maintains effective communication jamming (the proportion of high-intensity jamming is no less than 50%, and the proportion of normal signal reception of communication nodes is no more than 6%), but also extends the system operation duration by 66.8–269.6% compared with the comparative algorithms for the 600 MHz fixed-frequency and 1 MHz bandwidth communication system. This work is limited to the line-of-sight (LOS) scenario, and future research will extend it to non-line-of-sight (NLOS) scenarios. Full article

To address pressure-drop-induced safety risks in high-drop gravity-fed irrigation pipelines, this study investigates coordinated prevention and control strategies that integrate air release and vacuum valve groups with flow-adaptive valve closure rules. A large-scale self-pressurized irrigation network (1.33 × 10⁸ m²) in Karamay, Xinjiang, China, is selected as a representative case study. Based on one-dimensional transient flow modeling, pressure drop and negative-pressure characteristics induced by inlet valve closure in the main pipeline are analyzed using wave speed theory, governing differential equations, and the finite difference method. A coordinated protection framework is proposed that explicitly links valve operating patterns with the spatial configuration of protective devices. Unlike conventional schemes that rely on empirical layouts and fixed closure rules, this study introduces a critical-flow-velocity-based valve grouping method combined with flow-dependent valve closure strategies. Simulation results demonstrate that a strategically optimized configuration of air release and vacuum valves along the main pipeline is sufficient to eliminate negative pressure under all operating conditions. For flow rates below 6 m³/s, linear valve closure ensures safe operation, whereas a two-stage closure is required for higher flow rates (6–10 m³/s). As flow increases, reducing the fast-closure ratio and extending the total closure time effectively suppress pressure-drop-dominated transient effects at vulnerable inlet sections. By effectively mitigating transient pressure surges, the proposed coordinated “valve closure-protection device” strategy improves system adaptability to flow variability and provides practical engineering guidance for the safe operation of gravity irrigation systems, particularly high-gradient self-pressurized networks. Full article

Addressing the dual challenges of efficient water resource utilization and high construction costs in agricultural production, this study proposes a low-cost sprinkler irrigation system featuring a joint optimized design of water supply facilities and sprinkler layout. Initially, to mitigate water wastage at the field boundaries, an enhanced sprinkler layout is designed. This design strategically adjusts sprinkler spacing to position units along the irrigation area’s perimeter, leveraging their adjustable spray angles for semicircular coverage, thereby achieving superior water conservation compared to traditional honeycomb full coverage layouts. Subsequently, considering the non-linear relationship between pipeline cost and its length and flow rate, a supply network comprising five independent pipelines running perpendicular to the river is constructed. Furthermore, water storage tanks are strategically located at the head of each pipeline near the water source to reduce costs. Finally, constrained by the daily soil moisture levels required for crop survival, an inference-based dimension reduction algorithm is employed to jointly optimize the daily pipeline flow rate and storage tank capacity for each supply line. Specifically, by constructing the functional mapping between flow rate and tank capacity, the complex bivariate optimization problem is reduced to a single-variable extremum problem. Additionally, a calculation method for the feasible region of decision variables is proposed to ensure solution validity. The results demonstrate that the proposed scheme achieves a minimum total construction cost of CNY 2,611,404.00 with a total storage tank capacity of 114,892.40 L, and generates a detailed daily irrigation strategy. This study offers a significant model reference and a technical pathway for developing agricultural irrigation systems that are both economical and efficient. Full article

As the development of High-Speed Railways (HSRs) shifts from scale expansion to quality and efficiency, high-density timetables face increasing challenges regarding operational stability. Traditional capacity metrics often prioritize volume over service quality, neglecting the economic and service implications of delays. To reconcile theoretical capacity with practical reliability, this paper proposes a novel Reliable Value (RV)-oriented framework for HSR timetabling. We construct a Reserve Capacity Incremental Heuristic Optimization Framework that employs a synergetic integrated stochastic optimization strategy. This methodology treats reserve capacity as a systematically varied analytical parameter rather than a static constant, integrating redundancy layout planning with dynamic recovery adjustments under stochastic delay scenarios. The RV metric quantitatively combines efficiency (Expected Running Time) and robustness (Indirect Capacity Loss). A case study on the Beijing–Shanghai high-speed railway corridor demonstrates a non-linear relationship between reserve capacity allocation and system value. The results identify an optimal saturation interval of 5 to 14 min, where the marginal gains in reliability maximize the overall system value without excessively compromising operational efficiency. These findings provide theoretical support for transitioning from static capacity planning to proactive, value-based resilience engineering through optimized redundancy allocation. Full article

As population aging accelerates, age-related declines in visual sensitivity and attentional control make older drivers more vulnerable to suboptimal in-vehicle interface designs. Head-up displays (HUDs) are intended to reduce gaze shifts by overlaying information within the forward field of view, yet empirical evidence remains limited on how specific HUD presentation strategies reshape older drivers’ visual attention allocation. Grounded in theories of visual attention and cognitive load, this study systematically investigates three design variables that are increasingly common in contemporary HUDs (including AR-HUDs): (1) dynamic versus static navigation cues, (2) pedestrian warning strategies under different lighting conditions, and (3) the spatial placement of high-priority information. We first conducted a formative user study to define variables and operationalizations, and then carried out three within-subject driving-simulator experiments using controlled HUD stimuli and eye tracking. Objective gaze measures (e.g., fixation count, total fixation duration, and time to first fixation) were combined with subjective preference ratings to characterize attentional capture, search efficiency, and potential attentional costs. Findings reveal a robust trade-off: continuously changing navigation cues enhance attentional capture but can also increase attentional “stickiness,” unnecessarily consuming older drivers’ limited attentional resources. In pedestrian hazard tasks, real-time overlay warnings that were spatially aligned with the hazard significantly improved visual localization under low-light conditions, outperforming early warnings and multi-stage strategies. Across tasks and layout conditions, the central HUD region showed a stable attentional advantage—placing critical information centrally elicited greater visual attention and stronger subjective preference. These results provide mechanistic evidence for how HUD parameters modulate older drivers’ attention and yield actionable implications for prioritization, temporal pacing of dynamic navigation cues, and a “center-first” layout strategy to guide age-friendly HUD design. Full article

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a 1D-2D-coupled hydrodynamic model (InfoWorks ICM). The model was calibrated using continuous monitoring data, achieving a Nash–Sutcliffe Efficiency (NSE) of 0.91. Its spatial accuracy was subsequently validated against historical waterlogging records, showing a strong consistency between simulated flood-prone areas and observed flood locations. We simulated waterlogging distribution under rainfall events with return periods of 0.5 to 5 years. Results reveal two key deficiencies in the current drainage system under a 0.5-year return period storm event. Firstly, 75.3% of the pipe segments are hydraulically overloaded, failing to meet the design standard. Secondly, this widespread network overload contributes to surface waterlogging, with 9.58 ha (1.80% of the total area) being waterlogged. We evaluated three strategies: Low Impact Development (LID), underground storage tanks, and intercepting sewers. A hybrid grey-green infrastructure (HGGI) system was proposed, integrating source reduction and terminal storage. The HGGI system reduced waterlogged areas by 83.58% (0.5-year event) and 64.87% (5-year event), outperforming single measures. Crucially, this hybrid system achieves minimal intervention in historic street patterns through trenchless construction for intercepting sewers, decentralized LID layout and underground storage tanks, avoiding large-scale road excavation while enhancing flood resilience. This study demonstrates that hybrid strategies can effectively balance flood resilience with environmental and cultural preservation in high-density historic districts. Full article

Global warming has significantly intensified the risks of summer heatwaves, making outdoor thermal comfort during extreme heat periods a critical research focus. Under centralized rural village reconstruction policies, traditional settlements are being replaced by regularized modern communities characterized by new materials and standardized layouts. However, the impact of these morphological transitions on the micro-scale thermal environment remains under-researched, with a notable lack of comparative perspectives between traditional organic and modern standardized typologies. This study identifies six representative zones based on spatial configuration. By integrating UAV photogrammetry (Pix4Dmapper v4.5), AutoCAD 2019, and QGIS (v3.22), morphological characteristics were quantified, followed by microclimate simulations using ENVI-met v5.9. The results reveal that while peak daytime Physiological Equivalent Temperature (PET) in the standardized zones (49.2–51.8 °C) is slightly lower than in traditional zones (53.5–55.2 °C), a phenomenon of thermal homogenization emerges in the former. Specifically, values in standardized zones are highly concentrated around the median (53.5 °C), contributing to a significant upward trend in the minimum PET values, with nearly all sampling points exceeding 47.0 °C. Quantitative analysis identifies green coverage and perviousness as primary cooling drivers, while spatial openness and imperviousness promote thermal homogenization. In contrast, traditional zones retain critical cool refuges due to their spatial heterogeneity. This research provides an empirical foundation and quantitative reference for understanding the thermal performance differences across different rural spatial typologies. The findings offer insights for planners to optimize street layouts and shading strategies, ultimately mitigating heat stress and fostering climate-resilient modern countryside development. Full article

Strengthening square reinforced concrete (RC) columns with full ultra-high-performance fiber-reinforced concrete (UHPFRC) jacketing is highly effective, but such complete wrapping is often impractical due to architectural or geometric constraints. Previous studies have not systematically examined the performance of partial-coverage UHPFRC patterns for these sections. This study numerically investigates the axial performance of square RC columns strengthened with strategically arranged UHPFRC elements—including horizontal shortcuts, vertical strips, and hybrid configurations—using finite element analysis in ABAQUS. Key parameters include jacket thickness, element dimensions, column height, and reinforcement details. Results show that a 10 mm full UHPFRC jacket more than doubles axial capacity (+105.9% for 800 mm columns), with significant gains in stiffness. Vertical strips enhance strength but reduce ductility; horizontal shortcuts improve post-peak stability; and hybrids offer a balanced response. With full jacketing, internal steel details have minimal impact on peak capacity, while column height chiefly influences energy dissipation. This work establishes that optimized partial UHPFRC layouts—specifically strips, shortcuts, and their combinations—can achieve tailored performance improvements, introducing a novel, practical, and material-efficient design strategy for strengthening square columns where full wrapping is not feasible. Full article

Conventional configurations for neutral-point-clamped multilevel converters exhibit an uneven power loss distribution among their power semiconductor devices. In particular, this imbalance increases the temperature of power semiconductor devices situated at specific locations within the converter layout, thereby reducing the reliability of the system. To mitigate this issue, neutral-point-clamped multilevel converters can be implemented using a switching-cell array design. This design allows for multiple topology configurations and inherently introduces redundant conduction paths, thus reducing conduction losses and also providing greater flexibility in distributing the switching losses. This work analyzes the thermal behavior of various configurations of a four-level dc–ac neutral-point-clamped converter based on a switching-cell array. An active thermal control strategy is used to distribute the switching losses, in order achieve a more uniform temperature distribution across the converter. Experimental results confirm that, compared to conventional neutral-point-clamped converter implementations, configurations based on a switching-cell array combined with active thermal control achieve a more uniform distribution of power losses. This leads to significantly improved temperature uniformity across the converter, thereby reducing thermal stress and enhancing overall system reliability. Full article

The optimization of the MOSFET gate drive parameters is crucial for the trade-off between switching loss and electromagnetic interference (EMI). However, the nonlinear coupling among gate drive parameters, board-level parasitic, and switching performance limits the effectiveness of traditional MOSFET drive design methods. This paper proposes an adaptive tuning framework based on the proximal policy optimization (PPO) algorithm. An analytical switching model incorporating board-level parasitics is first derived to analyze the coupling between drive parameters and switching performance. The optimization problem is then formulated as a Markov decision process (MDP). Within this framework, domain randomization is applied during training. This enables the agent to learn a generalizable optimization strategy that remains robust across the varying parasitic inductances encountered in different PCB layouts. Compared to the traditional Non-dominated Sorting Genetic Algorithm II (NSGA-II), the proposed method uses the trained policy for direct inference. This reduces computation time by $98.7\%$ while maintaining a multi-objective performance difference within $10.06\%$. In addition, hardware verification shows a 10.7% average deviation between the measured and simulated results. These results demonstrate that the proposed method provides an efficient and scalable solution for MOSFET gate drive optimization. Full article

Urbanization and climate change are exerting significant pressure on the living environments of traditional rural settlements. In western Sichuan, the persistently cold and humid winter further intensifies the risks for local residents. Linpan, a distinctive agricultural settlement form that has evolved over centuries, embodies climate-responsive construction wisdom shaped by long-term human–environment interaction. Within Linpan, residential units—composed of outdoor and indoor spaces—serve as the primary activity spaces for inhabitants. Their spatial configuration and construction practices directly regulate the thermal environment and consequently influence daily life. However, whether the winter thermal environment satisfies contemporary thermal comfort requirements, and which landscape and construction determinants can effectively enhance thermal adaptation, remains insufficiently understood. To address this gap, this study integrated meteorological field measurements, thermal comfort questionnaire surveys, and coupled numerical simulations to systematically investigate winter thermal conditions in both outdoor and indoor spaces of Linpan residential units. The optimization performance of key landscape determinants (vegetation configurations and ground materials) and construction determinants (building layouts and envelope materials) was evaluated. The results reveal climate-responsive passive design strategies based on actual inhabitants’ thermal adaptation, establishing a sustainable design framework for improving winter thermal comfort in traditional agricultural settlements. The findings provide scientific support for rural revitalization and contribute theoretical insights into climate-resilient preservation of vernacular dwellings under changing environmental conditions. Full article

Time difference of arrival (TDOA) localization enables high-accuracy positioning by analyzing arrival-time differences of target signals at distributed radar nodes, whose performance strongly depends on radar node topology. However, existing studies tend to focus more on improving localization accuracy, while overlooking the impact of radar geometric layout and surveillance coverage on localization performance. To this end, this paper proposes a topology optimization method for a distributed radar system based on an improved non-dominated sorting multi-objective particle swarm optimization (NS-MOPSO) algorithm. A geometric localization model is developed for a distributed TDOA radar system. Based on this model, three optimization objectives are formulated, including minimizing geometric dilution of precision (GDOP), maximizing target coverage, and improving the geometric balance of node placement. These three objective functions are incorporated into the NS-MOPSO framework to achieve a more reasonable radar geometric distribution. To enhance the optimization performance, a series of strategies are adopted, such as non-dominated sorting for Pareto-based solution selection, an improved crowding-distance scheme to encourage balanced multi-objective optimization, and Gaussian mutation to increase solution diversity and reduce the risk of premature convergence. To validate the proposed method, both simulation studies and real-world experiments were conducted under different node deployment scenarios. The results show that the optimized topology achieves a 6.4% reduction in RMSPE and a 4.3% increase in the proportion of high-quality localization regions compared with the best-performing comparative method, while also demonstrating faster convergence and improved stability. These findings confirm the effectiveness and robustness of the proposed approach in enhancing localization accuracy, expanding effective coverage, and improving overall system performance. Full article

Flotation workshop ventilation control virtual monitoring system alarm interfaces need to adapt to high-dynamic and high-interference industrial environments, while traditional interfaces have information overload and chaotic layout, leading to excessive cognitive load of operators and low alarm response efficiency, which makes it urgent to optimize the interface design. This study constructed a scenario characteristics-cognitive requirements-interface design coupling model, and conducted a 3 (alarm position) × 2 (display form) × 2 (target quantity) within-subjects experiment combined with eye-tracking technology and the NASA-TLX scale. The combination of “display beside 3D model + background color filling” performed optimally, with the single-target task achieving a 2.067 s reaction time and 99.5% accuracy, and the multi-target task 2.460 s and 94.6% accuracy, significantly reducing extraneous cognitive load. This study proposed optimization strategies including display optimization and lightweight presentation, enriching the application of Cognitive Load Theory in high-risk industrial interfaces and providing scientific references for similar system design. Full article