International Journal of Engineering Advances
International Journal of Engineering Advances (Int. J. Eng. Adv.) is a peer-reviewed academic journal dedicated to publishing cutting-edge research and advancements across all fields of engineering. The journal welcomes original research articles, review papers, and technical notes on topics such as civil engineering, mechanical engineering, electrical engineering, computer science, and materials science. Its mission is to facilitate the dissemination of innovative solutions and promote interdisciplinary collaboration within the global engineering community.
Risk Control and Financial Analysis in Energy Industry Project Investment
With the rapid expansion of the global energy industry, investments in energy projects are increasingly confronted with complex challenges and uncertainties. This paper examines the distinctive risk characteristics inherent to such projects and proposes a range of practical risk management strategies, including enhancing data security, mitigating technical uncertainties, and ensuring robust compliance in cross-border investments. Furthermore, it presents comprehensive financial analysis methods tailored for energy projects, encompassing financial feasibility assessments, evaluation of capital sources and financing structures, financial risk analysis, and sensitivity testing. By integrating thorough risk management with systematic financial evaluation, this study establishes a rational and reliable decision support framework for investors, helping them anticipate potential threats, make informed investment decisions, and promote the sustainable, long-term growth of energy projects.
Soil Chemistry Enhancement through Coordination Polymer Urease Inhibitors: Environmental Impact Assessment
The application of coordination polymer urease inhibitors represents a promising advancement in sustainable agriculture, offering enhanced nitrogen use efficiency while minimizing environmental degradation. This comprehensive study evaluates the environmental impact of copper-based coordination polymers as urease inhibitors in soil systems, examining their effects on soil enzyme activities, microbial communities, and overall soil health. Recent developments in coordination polymer technology have demonstrated significant potential for improving agricultural productivity while reducing ammonia emissions and environmental contamination. The research integrates findings from multiple studies examining the interaction between synthetic urease inhibitors and natural soil processes, with particular emphasis on enzyme activity modulation and microbial community dynamics. Environmental impact assessments reveal that properly designed coordination polymer systems can enhance soil nutrient cycling without compromising biological diversity or soil functionality. The study demonstrates that copper-based coordination polymers exhibit superior urease inhibition efficiency compared to conventional inhibitors, with reduced environmental persistence and improved biodegradability. Furthermore, these novel materials show promise for addressing cadmium contamination while maintaining soil metabolic functions. The findings suggest that coordination polymer urease inhibitors represent a viable solution for sustainable intensification of agricultural systems, providing effective nitrogen management while preserving soil ecosystem integrity and supporting long-term agricultural sustainability.
Copyright (c) 2025 Anna Müller (Author)
Decomposition Analysis of Carbon Emission Drivers in Thailand's Power Sector
This study investigates the driving factors of carbon emissions in Thailand's power sector from 2002 to 2022 using the Logarithmic Mean Divisia Index (LMDI) decomposition method. The objective is to provide a systematic and quantitative assessment of how socioeconomic and technological developments have influenced emission dynamics. The results indicate that total emissions rose from approximately 62 Mt in 2002 to a peak of 90 Mt in 2013, before stabilizing and slightly declining in recent years, reflecting improvements in efficiency and structural transformation. Economic growth was the largest contributor, adding a cumulative 43.83 Mt, followed by population growth (9.52 Mt). In contrast, structural transformation-primarily the gradual substitution of fuel oil with natural gas-reduced emissions by about 21.81 Mt, while enhanced efficiency in coal consumption contributed an additional 20.86 Mt reduction. Electricity intensity exerted a modest positive effect (4.39 Mt), and the influence of the carbon emission factor was minimal (0.61 Mt). The findings suggest that Thailand's power sector has achieved relative decoupling between economic growth and emissions, though absolute decoupling has yet to occur. The analysis underscores the critical importance of accelerating renewable energy deployment and strengthening energy efficiency initiatives to meet Thailand's carbon neutrality target by 2050 and its net-zero emissions goal by 2065. This study fills a gap in the existing literature by providing the first multi-factor decomposition analysis of Thailand's power sector emissions, offering valuable empirical insights and policy implications for sustainable energy transitions in developing economies.
Copyright (c) 2025 Chen Chen, Mohammad Nizamuddin Inamdar, Aiman Al-Odaini (Author)
AI-Driven Project Management for Construction SMEs: A Framework for Cost and Schedule Optimization
Efficient project management remains a persistent challenge for small and medium-sized enterprises (SMEs) in the U.S. construction industry, where delays and budget overruns are prevalent. This study proposes an AI-driven project management framework tailored to SMEs, integrating predictive scheduling, resource allocation, and real-time progress monitoring. By leveraging machine learning models and cloud-based visualization tools, the framework generates adaptive schedules and optimizes task prioritization. A case study using representative project data demonstrates that the AI-enhanced system reduces schedule variance and cost deviation compared to traditional critical path methods. Results indicate that SMEs can achieve significant improvements in project predictability and resource efficiency without incurring the high costs of enterprise-level tools. The proposed framework contributes to national priorities in infrastructure development by enabling SMEs—who comprise the majority of U.S. construction firms—to deliver projects with greater timeliness, cost-efficiency, and resilience.
Copyright (c) 2025 Yuanfeng Liang (Author)
Structural Characterization of Novel Copper-Based Metal-Organic Frameworks: X-Ray Crystallography and Analysis
Metal-organic frameworks (MOFs) have emerged as a versatile class of crystalline materials with extraordinary potential for applications in gas storage, separation, catalysis, and sensing. This study presents a comprehensive structural characterization of novel copper-based MOFs through advanced X-ray crystallographic techniques and detailed structural analysis. The investigation focuses on the synthesis and structural elucidation of three distinct copper-based frameworks incorporating different organic linkers and secondary building units. Single-crystal X-ray diffraction analysis revealed unique topological arrangements and coordination environments that significantly influence the framework properties. The copper centers exhibit diverse coordination geometries ranging from tetrahedral to octahedral configurations, creating distinct pore architectures and surface characteristics. Structural refinement data demonstrates exceptional crystallographic quality with R-factors below 4% for all synthesized frameworks. The frameworks exhibit remarkable thermal stability up to 350°C and display selective gas adsorption properties. Powder X-ray diffraction confirms the phase purity and structural integrity of the bulk materials. The structural diversity observed in these copper-based systems provides valuable insights into structure-property relationships and opens new avenues for targeted framework design. These findings contribute significantly to the fundamental understanding of copper coordination chemistry in porous crystalline materials and establish a foundation for future applications in environmental remediation and industrial processes.
Study on the Impact of Water Level Fluctuations on the Stability of Reservoir Bank Landslides in Guangxi
The unique geological structure and climatic conditions in Guangxi make reservoir bank land-slides particularly problematic, with water level fluctuations being a key factor in inducing them. This paper systematically analyzes the mechanisms by which water level fluctuations affect the stability of reservoir bank landslides from a theoretical perspective, revealing the coupling effects of permeability, softening, buoyancy, and fatigue. By constructing a "hydrological-geological-mechanical" multi-field coupling model, the controlling effects of rock and soil permeability, geological conditions, and water level fluctuation rate on landslide stability are explored. The results indicate that permeability induced by sudden water level drops is the dominant factor in landslide instability, while fatigue damage caused by long-term water level fluctuations significantly reduces the long-term strength of rock and soil. The theoretical framework proposed in this paper provides a scientific basis for preventing and controlling reservoir land-slides in Guangxi and is of great reference value for similar projects.
Copyright (c) 2025 Zhangwu Tian, Fengjiao Qin (Author)
Copper-Based Coordination Polymers: Geometric Ligand Engineering for Targeted Urease Inhibition
Urease is a key enzyme in nitrogen cycling and a critical target in efforts to regulate urea-based fertilization for agricultural sustainability. Copper-based coordination polymers (Cu-CPs) have emerged as potent urease inhibitors, with molecular design playing a central role in dictating their activity. In particular, V-shaped ligands provide unique steric and electronic environments that can fine-tune polymer architecture and bioactivity. This paper presents a comprehensive analysis of V-shaped ligand-assisted engineering strategies for copper-based coordination polymers, focusing on their structure-function relationships, urease inhibition efficiency, synthetic strategies, and agricultural applications. By analyzing ten recent studies, this work synthesizes the state-of-the-art in ligand-based modulation of Cu-CP frameworks. Furthermore, the agricultural relevance of these materials is assessed through the lens of soil–plant nitrogen retention, enzymatic inhibition kinetics, and long-term soil health. Emphasis is placed on the bridging coordination modes, ligand-metal affinity, and cooperative inhibition mechanisms that define bioactivity. This paper provides a structural roadmap for future Cu-CP design, proposing molecular and synthetic benchmarks for sustainable urease inhibition technologies.
Copyright (c) 2025 Fiona L. Maxwell, Gavin T. Fletcher (Author)
Morphological Characterization of Carbon Nanotubes and Their Agglomeration Behavior Revealed by Scanning Electron Microscopy
In this study, the microscopic morphology and agglomeration behavior of carbon nanotubes (CNTs) were systematically investigated using high-resolution scanning electron microscopy (SEM). The SEM analysis revealed that CNTs predominantly exist in the form of irregular, spherical or quasi-spherical macroscopic aggregates, composed of densely entangled, curved, and flexible nanotubes. These aggregates exhibit a porous nanonetwork structure, rather than solid dense blocks, due to the random stacking and bending of individual CNTs. In addition to the major agglomerates, partially dispersed nanotubes were clearly observed at the periphery and in the interstitial spaces between aggregates, forming sparse and loosely connected nanonetworks. These morphological characteristics highlight the intrinsically high surface energy of CNTs and the strong van der Waals forces that drive their aggregation—a phenomenon that presents a critical challenge for achieving uniform dispersion in practical applications. Poor dispersion can severely hinder the mechanical reinforcement, electrical conductivity, and accessible surface area of CNTs in host materials, limiting their effectiveness in various functional systems. The insights gained from this detailed morphological analysis provide direct empirical evidence for the hierarchical structure of CNT agglomerates and the existence of inter-aggregate networks. These findings lay a solid foundation for understanding the complex relationship between the microstructural organization of CNTs and their macroscopic behavior. Furthermore, the results offer valuable guidance for the rational design of advanced dispersion techniques and integration strategies, aiming to fully exploit the exceptional properties of CNTs in fields such as polymer nanocomposites, energy storage and conversion, biomedical engineering, and environmental applications.
Copyright (c) 2025 Sergey Petrov, Alexey Smirnov, Elena Ivanova (Author)
Research on Identification and Analysis of Hazards in High Altitude Tunnel Construction Operations
Tunnel construction is an important safety control scenario in transportation engineering construction. Due to its own characteristics, such as high weight of terrain and landforms, complex geological conditions, numerous environmental factors, and difficult management, tunnel construction safety management has attracted much attention. In different tunnel constructions, the difficulty of managing high-altitude tunnel construction is particularly prominent. This article focuses on the high-altitude areas represented by the Qinghai Tibet Plateau. Taking the Laze Tunnel as the research objective, a combination of on-site investigation, interview, and screening methods were used to identify the hazards of high-altitude tunnels from four aspects: personnel, equipment, environment, and management. Analyzed its existing problems and provided countermeasures and suggestions. This study lays a theoretical foundation and practical significance for the safety management of high-altitude tunnel construction operations.
human machine environment system analysis
Copyright (c) 2025 Defeng Duan, Baofeng Sun, Hai Liu (Author)
Research on Perception and Control System of Small Autonomous Driving Vehicles
With the continuous advancement of autonomous driving technology, the application of small autonomous vehicles in changing environments has gradually attracted attention. This article discusses the core technologies of perception and control systems for small autonomous vehicles. An analysis was conducted on the key issues faced by the perception system of small autonomous vehicles, including improving the accuracy of local and global positioning, as well as the application of multi-source sensor fusion technology. By integrating various sensing devices such as LiDAR and image sensors, the perception accuracy of the system has been enhanced. The improvement of the control system was also discussed, and the overall path planning method based on gridded maps and the improvement strategy of the motion control system were analyzed. With precise path design and efficient motion control algorithms, the driving stability and safety factor of the car are ensured in changing environments. Finally, the integration and testing of perception and control systems were discussed, and solutions for software hardware collaboration enhancement and comprehensive debugging and testing in complex scenarios were proposed.
A New Design and Simulation of a Reciprocating Motion Mechanism of Dynamic Ad Devices
In this paper, a reciprocating motion dynamic advertisement device is designed for a new category of billboards. The core design consists of a conjugate cam and multi-link structure, based on which a kinematic model is established and ADAMS kinematic simulation is performed. The results show that the kinematic model of the designed reciprocating structure is highly accurate with an error of only 4%, and the cam mechanism has less contact force, which is of strong utilization value.
Copyright (c) 2025 Sining Yao, Kai Xu, Yanzhang Ren (Author)
Safety Countermeasures and Accident Prevention Measures in Traffic Design
Traffic design plays a critical role in ensuring traffic safety. This article discusses the close relationship between traffic design and safety, analyzes potential risk factors in traffic design, and proposes targeted safety measures and accident prevention measures. Traffic design must follow the basic principles of science, reasonably lay out roads, set up traffic signs and markings to ensure safety and smoothness. Safety hazards such as unreasonable road layout, improper setting of traffic markings, and road condition changes caused by adverse weather are key issues in traffic safety management. To address these issues, effective solutions have been proposed, including standardized lane and shoulder design, application of intelligent transportation systems (ITS), and improvement of road drainage and anti-skid design. These measures can not only reduce the incidence of traffic accidents, but also improve the safety and efficiency of the overall transportation system.
intelligent transportation management system
Copyright (c) 2025 Naizhong Cui (Author)
Research on the Relevance between the Traditional Buildings of the WA Ethnic Group in Wengding and Their Culture: A Quantitative Analysis Based on Hypothetical Data
This study takes the traditional villages of the Wa ethnic group in Wengding, Yunnan Province as the research object. Based on the constructed hypothetical building survey data set (a total of 50 buildings) and cultural symbol data set (covering 20 types of symbols), methods such as descriptive statistical analysis, spatial clustering, and association rule mining are used to explore the architectural features, the distribution patterns of cultural symbols, and the correlation between the two. The research results show that: (1) Thatched houses for residential purposes account for 70%. Among the decorative elements, animal carvings account for 42.9% and plant patterns account for 28.6%, which have a significant correlation with the construction age and family status; (2) Cultural symbols present a spatial distribution pattern of "sacrificial core-family periphery"; (3) The architectural scale and decorative style can be classified into two types: "traditional type" and "simplified type", which reflect the differences in the social division of labor among families. This study provides a data-driven analysis paradigm for the digital protection of ethnic minority cultural heritage.
Copyright (c) 2025 Yanan Jiang, Qi Liu (Author)
Web Front-End Application Performance Improvement Method Based on Component-Based Architecture
In the context of the continuous evolution of Web front-end technology, performance optimization has become the core work to improve user experience and enhance product value. This paper focuses on analyzing the performance bottlenecks encountered by current Web front-end applications, such as rendering bottlenecks, network bottlenecks, resource bottlenecks and computing bottlenecks, and introduces optimization suggestions. By designing front-end applications with a block architecture, you can reduce redundant rendering, optimize resource loading, split code and lazy loading, and improve the efficiency of state management to significantly improve application speed. At the same time, the influence of the block structure on the front-end application is analyzed, and how to optimize the development process and performance through good structure design is discussed.
Exploration of Process Improvement in Automotive Manufacturing Based on Intelligent Production
With the rapid development of intelligent manufacturing technology, automation has become the main means of improving efficiency, reducing costs, and ensuring product quality in automotive production. This paper discusses the application of automobile intelligent production technology, mainly investigating the current widespread robot applications, the role of robots in automated production assembly lines, the application of the Internet and big data in the production process and other issues. Through robot automation production technology, high precision and efficiency can be achieved, which is reflected in the processes of body welding and production part installation in automobile production. The combination of the Internet and big data makes the monitoring of the production process more intelligent and real-time, increasing the sensitivity of the production line and equipment utilization. This paper explores the obstacles encountered in the implementation of intelligent production technology, such as technology integration, data confidentiality and personal privacy protection, and shortage of technical personnel, and proposes relevant improvement measures, which can be used as a reference for automobile manufacturing enterprises in the process of implementing intelligent production technology transformation.
Copyright (c) 2025 Junchun Ding (Author)
Research on the Development of Intelligent Ships and Smart Energy Management Technologies
With the maritime industry undergoing digital transformation and facing growing demands for automation, intelligent ships and smart energy management have become central to boosting operational efficiency, cutting fuel consumption, and reducing environmental impact. This paper first reviews the concept and system architecture of intelligent ships and surveys key technological advances in autonomous navigation, condition monitoring, and decision support. It then examines the architectural models of shipboard energy management systems, explores intelligent optimization algorithms, and outlines real-time control strategies. Drawing on representative application cases, the study evaluates both operational performance and economic returns. Finally, it discusses major challenges in engineering rollout, algorithmic reliability, and large-scale deployment, and looks ahead to emerging research directions and industry trends, offering theoretical underpinnings and practical guidance for the evolution of intelligent shipping and energy management.
Sustainable Construction Management: Integrating Carbon Reduction into Planning, Design, and Project Delivery
As global climate change becomes an increasingly pressing issue, the construction industry plays a significant role in carbon emissions, making carbon reduction measures a key focus for its development. This review explores the primary methods and innovations for integrating carbon reduction strategies into construction management, focusing on the planning, design, and construction phases. The paper first discusses the core concepts of sustainable construction management, detailing the integration of carbon reduction goals throughout the construction lifecycle and the role of industry standards and policies. It then examines the importance of carbon footprint assessments and carbon budgeting models during the project planning phase, and the integration of low-carbon design principles, including green building design, material selection, and energy efficiency optimization. In the construction phase, modular building, green construction technologies, and digital tools are identified as effective means of reducing carbon emissions. Finally, the paper highlights the challenges the industry faces in carbon reduction, such as regulatory issues, cost barriers, and data transparency, while pointing out emerging opportunities like green finance and carbon trading. It also outlines future research directions, including full lifecycle carbon tracking and smart construction technologies.
A Sensor-Fused Deep Reinforcement Learning Framework for Multi-Agent Decision-Making in Urban Driving Environments
Achieving robust and efficient autonomous driving in complex and dynamically changing urban traffic environments faces numerous significant challenges, especially the need to properly handle complex and time-varying interaction behaviors among multiple agents. This study innovatively proposes a sensor-integrated deep reinforcement learning framework (SIDRL), which organically combines multimodal sensor data fusion technology with multi-agent decision-making methods based on policy optimization. The system inputs include data from lidar, cameras and vehicle-to-everything (V2X), which are initially processed through a fusion perception module and subsequently fed into a decision-making network based on proximal policy optimization (PPO) for training and inference. Comprehensive evaluation experiments were conducted on the high-fidelity CARLA 0.9.15 simulation platform, and comparisons were performed with classical deep Q-network (DQN), asynchronous advantage actor-critic (A3C), as well as advanced methods such as soft actor-critic (SAC) and multi-agent proximal policy optimization (MAPPO). The experimental results clearly demonstrate that the proposed method enhances collision avoidance capability by 23.5% and decision-making efficiency by 17.2% under complex urban traffic scenarios. The research outcomes effectively confirm the critical role of multi-sensor fusion within deep reinforcement learning frameworks in improving environmental adaptability and safety for autonomous driving vehicles, providing a valuable new direction for the development of urban autonomous driving technology.
Copyright (c) 2025 Ethan J. Cole, David R. Thompson, Jason T. Nguyen, Benjamin A. Wright (Author)
Post-pandemic Architectural Design: A Review of Global Adaptations in Public Buildings
The COVID-19 pandemic has drastically reshaped the way public buildings are designed and used, forcing architects and urban planners to rethink existing architectural norms. This review explores the global adaptations in public building design in response to the pandemic, focusing on key changes in spatial organization, health and safety protocols, and the integration of smart technologies. Drawing from case studies across North America, Europe, and Asia, the paper highlights the importance of flexibility, modularity, and sustainability in post-pandemic architectural solutions. It also examines the emerging role of advanced technologies such as AI, automation, and data-driven design in enhancing the user experience and ensuring safety. The review concludes with a discussion on the long-term implications for future architectural practice and identifies gaps in current research, suggesting areas for further exploration in the evolving field of post-pandemic architecture.
Effect of Air Gap Eccentricity on the Torque and Losses of Bulb Tubular Turbine Generators
The uniformity of the air gap is crucial to the electromagnetic performance of the Bulb Tubular Turbine Generator (BTTG). However, due to factors such as manufacturing tolerances, assembly deviations, and mechanical deformations during operation, the center of the air gap may shift relative to the rotor axis. This air gap eccentricity causes unevenness in the air gap between the stator and rotor along the circumferential direction, leading to a distortion of the magnetic flux density. As a result, the generator's operational stability is compromised, and the fatigue loss of the core material is accelerated. Therefore, the study of the impact of air gap eccentricity on the BTTG is of significant engineering importance for optimizing the generator’s structural design and enhancing its operational performance.
Design and Research of the Signal Intelligent Operation and Maintenance System for Nanning Metro Line 4 Based on PHM Technology
As urban rail transit expands rapidly, the operation and maintenance of metro signal systems are crucial. Traditional methods face challenges, like relying too much on manual work and not predicting faults well. This study uses Prognostics and Health Management (PHM) technology to create Nanning Metro Line 4's signal intelligent operation and maintenance system. By carefully analyzing requirements, it details the system's design, including its architecture and working principle. It also covers technical implementation, such as how to collect and process data, monitor equipment, predict faults, and make maintenance decisions. The goal is to boost the operation and maintenance levels and efficiency, guarantee metro safety, and offer a model for other urban rail transit signal intelligent operation and maintenance projects.
Copyright (c) 2025 Yongqin Huang, Guoyan Che, Jianqiu Chen, Guobin Gu (Author)
Study on Spring Festival Passenger Flow Forecasting of Rail Transit in South China Based on Optimized SARIMA Model--Taking Guilin City as an Example
In this study, the optimized SARIMA model is used to forecast the spring rail transit passenger flow in Guilin City in 2019-2025, and external factors such as GDP and mobile population are introduced to improve the forecasting accuracy. First, the data range is extended to 11 years to enhance the model learning ability and reduce the impact of epidemics. Subsequently, the SARIMA parameters are optimized using grid search and AIC criterion to ensure the optimal fitting effect, and the prediction stability is improved by error control strategy. The experimental results show that the optimized SARIMA model performs well in short-term prediction, and the prediction error decreases year by year. Based on the prediction results, strategies such as mobility management, ticket optimization and capacity allocation are proposed to alleviate the pressure of passenger flow during the Spring Festival. This study provides a scientific basis for rail transportation capacity planning, which is of great significance to improve the transportation efficiency during the Spring Festival.
Copyright (c) 2025 Xiang Wang, Jianqiu Chen, Xueyu Zhuge, Guoyan Che, Guobin Gu (Author)
Research on Intelligent Diagnosis of Faults in Four-Wire Turnout Control Circuits
This study aims to shorten the troubleshooting time of turnouts in urban rail transit through intelligent diagnosis methods. An intelligent diagnosis system for faults in four-wire turnout control circuits is designed by building an experimental environment, collecting and analyzing data, so as to improve the operating efficiency and safety of trains. The system is developed considering the current reliance on manual inspection in turnout circuit fault diagnosis, which has numerous drawbacks. It consists of multiple functional modules, such as user information management, fault sample data management, and more. By monitoring the action current of turnouts in real-time, it can accurately identify fault types like action circuit short-circuit and switch machine jamming. Through data analysis and comparison, it can precisely locate fault points and provide corresponding maintenance plans. Experimental results have verified its effectiveness in enhancing maintenance efficiency, thus ensuring the stable and safe operation of urban rail transit.
Copyright (c) 2025 Jianhao Xie, Guoyan Che, Jianqiu Chen, Guobin Gu (Author)
A Review of the Development and Future Trends of Downhole Electric Bypass Valves
Downhole electric bypass valves have undergone significant technological advancements, evolving from traditional mechanical systems to intelligent, automated solutions. This paper reviews the development history, key technologies, current applications, and future trends of downhole electric bypass valves. Key advancements in motor drive systems, high-temperature sealing, remote monitoring, and energy efficiency have greatly enhanced their performance and reliability in oil and gas extraction. Future developments will focus on AI-driven automation, advanced materials, energy harvesting, and real-time monitoring, ensuring improved operational efficiency and adaptability to extreme environments. These innovations will further expand the application of downhole electric bypass valves in deep-sea drilling, geothermal energy, and even space resource extraction.
Copyright (c) 2025 Hong Zhan, Chong Xie (Author)
Electromagnetic Compatibility Design and Optimization Strategies for High-Frequency Ultrasonic Power Supplies
Electromagnetic compatibility (EMC) design of high-frequency ultrasonic power supplies is crucial for ensuring their performance and reliability. This review discusses common EMC design strategies for high-frequency ultrasonic power supplies, including shielding design, grounding and electromagnetic isolation, and layout optimization. Special emphasis is placed on the role of the three-stage EMI filter in reducing electromagnetic interference (EMI) and improving power supply performance. Through a detailed analysis of the filter design, its effectiveness in suppressing low, medium, and high-frequency noise is demonstrated. Additionally, the paper explores the application of novel materials and technologies for EMC optimization and looks ahead to future development trends.
Multi-Objective Design of Heat Sink Fins for Thermal Efficiency and Manufacturability
As power densities in modern electronics increase, efficient thermal management is essential. Conventional heat sink designs often fail to balance heat dissipation, airflow resistance, and manufacturability. This study proposes an AI-driven optimization framework, integrating deep reinforcement learning (DRL) and multi-objective genetic algorithms (MOGA), to refine fin geometries while ensuring fabrication feasibility. Unlike conventional methods, this approach incorporates additive manufacturing constraints, bridging the gap between computational optimization and real-world implementation. Validated through computational fluid dynamics (CFD) simulations and experimental fabrication, the optimized design achieved a 14.3% reduction in maximum temperature and a 32.8% decrease in thermal resistance, ensuring a more uniform temperature distribution. It also maintained stable cooling performance across airflow variations, confirming its adaptability. Manufacturability analysis revealed height deviations of up to 0.4 mm, which could affect airflow, while thickness deviations remained within ± 0.05 mm, indicating high precision. These results highlight the importance of integrating fabrication constraints early in the design process to ensure optimization benefits translate into practical performance. This study shows that AI-driven optimization can enhance heat sink efficiency and reliability, offering a scalable approach for high-power electronics. Future work should refine manufacturing compensation models and transient thermal analysis to further improve real-world applicability.
Copyright (c) 2025 James Robertson, Emily Carter, Michael Thompson, Sarah White (Author)
A Comparative Study of Infiltration Methods Based on the SWMM Model: Application of Horton and Green-Ampt Models in Drainage System Design in Northeast China
This study conducts a comparative analysis of infiltration methods in a region of Northeast China using the SWMM model, aiming to assess the impact of different infiltration models on drainage system design. We selected the Horton infiltration method and the Green-Ampt infiltration method, derived from soil properties, to simulate rainfall-runoff processes in various areas. The results show that while the Horton method is suitable for infiltration simulations under conventional conditions, the Green-Ampt method provides more accurate results in regions with significant soil variability, offering a better reflection of actual drainage performance. The study recommends that, for drainage system design, the choice of infiltration method should be based on local soil characteristics to ensure system efficiency and reliability.
Copyright (c) 2025 Mingyi Yue, Xin Gao (Author)
Exploration of Strategies for Energy-Efficient Design in Architectural Planning Under the Concept of Green Buildings
The application of green energy-saving technology in building construction is becoming more and more widespread, and this trend not only responds to the tide of global sustainable development, but also meets the urgent needs of modern society for the environment and energy. With the rapid development of the construction industry, the problems of energy consumption and environmental pollution have become more and more prominent, and the introduction of green energy-saving technologies has become an inevitable choice. The application of technologies such as efficient energy-saving materials, renewable energy systems, intelligent construction management and resource recycling has greatly enhanced the environmental friendliness and economy of building construction. However, the promotion of these technologies still faces many challenges and requires joint efforts from both inside and outside the industry to realize a truly green transformation.
Copyright (c) 2025 Qi Liu, Rina Abdul Shukor, Yanan Jiang (Author)
Adapting Architecture to Climate: Exploring Climate-Responsive Strategies Across U.S. Cities
As energy consumption concerns continue to grow in the built environment, there is an increasing demand for design solutions that are responsive to local climate conditions. This study conducts an in-depth examination of the climate profiles of twelve U.S. cities, categorized according to the Köppen climate classification system, utilizing a parametric platform to assess suitable passive design strategies. By evaluating the effectiveness of different passive approaches across diverse climate zones, this paper provides actionable recommendations for incorporating climate-responsive design principles in architecture. The research establishes theoretical models that connect climatic variables with corresponding passive design techniques, thereby contributing to the evolution of passive design theory. Through this, the study advocates for a data-driven, climate-sensitive methodology that aligns with the growing emphasis on sustainability in modern architecture.
Copyright (c) 2025 Xinzhi Chang (Author)