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International Journal of Energy and Water Resources 2025年 1-19页

作者： Houmsi, M.R. Ishaq, A. Mohammad, S.J. Jagun, Z.T. New Era and Development in Civil Engineering Research Group Scientific Research Center Al-Ayen University Thi-Qar Nasiriyah 64001 Iraq Department of Water and Environmental Engineering School of Civil Engineering Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru 81300 Malaysia Department of Water Resources and Environmental Engineering Ahmadu Bello University Kaduna Zaria 1045 Nigeria Department of Real Estate School of Built Environment Engineering and Computing Leeds Beckett University City Campus Leeds United Kingdom

This study examines the efficacy of microbial fuel cells (MFCs) in treating landfill leachate while generating bioenergy. The MFCs achieved substantial reductions in chemical oxygen demand (62%) and nitrogen concentrations (78%), highlighting their role in sustainable waste management. Anammox bacteria and microbial consortia were identified as critical in optimizing nitrogen and COD removal. Experimental findings revealed an optimal power density (PD) of 283.38 mW/m² and a coulombic efficiency (CE) of 24.98% under specific conditions: NH4-N concentration of 800 mg/L, COD of 1325 mg/L, pH 6.88, and voltage of 528.59 mV. Using advanced machine learning models—CatBoost, XGBoost, Adaboost, and multiple linear regression—we predicted power density with high precision (R-squared: 0.92, RMSE: 0.05, MAE: 0.08). CatBoost emerged as the most accurate model, achieving an R-squared value of 0.999 and demonstrating robust predictive capabilities. A linear relationship between power density and COD concentration showed the importance of maintaining balanced organic matter levels for efficient MFC operation. This research bridges data-driven modelling and environmental engineering, providing practical strategies to enhance MFC performance. By integrating machine learning with bioelectrochemical systems, it offers actionable insights for sustainable leachate treatment, renewable energy production, and eco-friendly waste management practices. © The Author(s), under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and research Branch, Islamic Azad University 2025.

关键词： Ensemble Algorithms Hyper-parameters Leachate landfill Microbial fuel cells Power density

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Hybrid machine learning for predicting hydration heat in pipe-cooled mass concrete structures

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Construction and Building Materials 2025年 481卷

作者： Van Tran, Mien La, Hung Nguyen, Tan 268 Ly Thuong Kiet Street District 10 Ho Chi Minh70000 Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh70000 Viet Nam Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Smart Computing in Civil Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

Excessive heat from cement hydration in mass concrete can cause thermal cracking, compromising durability. Pipe-cooling systems mitigate this, yet optimizing efficiency remains complex due to nonlinear interactions among material properties, environmental conditions, and cooling parameters. This study is based on a high-quality dataset from real-world wind turbine foundation projects in Vietnam, offering critical insights into pipe-cooled mass concrete behavior under varying conditions. A hybrid machine learning framework is developed using a stacking ensemble model (XGB-CatB-Lasso) to predict temperature evolution. Hyperparameter tuning via Covariance Matrix Adaptation Evolution Strategy (CMA-ES) enhances performance, achieving a test R2 of 0.9564, surpassing conventional models in accuracy and generalization. Cooling system parameters dominate temperature regulation, surpassing material composition effects. Cooling duration, measurement location, and initial concrete temperature account for over 70 % of predictive power, with cooling water inlet temperature and flow rate further influencing heat dissipation. 3D Partial Dependence Plots (PDPs) reveal that pipe cooling shortens peak hydration heat duration to less than 72 hours, followed by an 8°C drop over the next 48 hours, reinforcing adaptive cooling needs. Intermediate factors, including flow rate (20–28 liter/min), pipe spacing (0.7–0.81 m), and water content (>176 liter), improve cooling but play a secondary role. Cement content between 294–418 kg/m³ increases temperature by ∼2.0°C, reinforcing that adaptive cooling, not mix adjustments, ensures effective thermal regulation. Predictive uncertainty was also analyzed using Monte Carlo simulations with ± 5 % input noise, providing further validation of model robustness under real-world variability. This AI-driven framework, grounded in real project data, enables real-time temperature monitoring and dynamic cooling control, enhancing structural durability and ene

关键词： Concrete buildings

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RoboSpike: Fully Utilizing the Heterogeneous System with Subcallback Scheduling in ROS 2

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Li, Hongyi Yang, Qingyuan Ma, Songchen Zhao, Rong Ji, Xinglong Tsinghua University Center for Brain-Inspired Computing Research Optical Memory National Engineering Research Center Tsinghua University-China Electronics Technology HIK Group Co. Joint Research Center for Brian-inspired Computing IDG/McGovern Institute for Brain Research Tsinghua University Department of Precision Instrument Beijing100084 China Hong Kong University of Science and Technology ACCESS -AI Chip Center for Emerging Smart Systems Hong Kong Hong Kong

The advancement in artificial intelligence (AI) has greatly propelled the development of robotics, requiring the adoption of heterogeneous computing architectures with multi-core CPUs, GPUs, and accelerators to meet the growing computational needs of edge computing. Such heterogeneity, coupled with the inherently IO-intensive nature of robotic applications, poses substantial challenges for task scheduling and resource management. These challenges are particularly acute for systems striving to maximize computational resource utilization, which cannot be effectively addressed through callback-level scheduling. To overcome these obstacles, we developed RoboSpike, a systematic solution built on the Robot Operating System 2. We first implemented a subcallback scheduling mechanism utilizing coroutines to utilize the blocked CPUs which wait for I/O operations. Building on this mechanism, we extended the design to incorporate the coprocessor and introduced an auto-tuning algorithm to adapt to system performance variations. Finally, we performed the response time analysis to ensure that the RoboSpike is predictable in time. The evaluation results demonstrate that RoboSpike achieves substantial improvements, increasing throughput by 1.65 to 2.25 times in real-world scenarios. RoboSpike enhances the scheduling capabilities of ROS 2 by refining the granularity from the callback level, thus opening up new opportunities for performance improvement in robotic systems, especially in resource-limited scenarios with complex workloads. © 1982-2012 IEEE.

关键词： Robot Operating System

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Al-anodizing waste as a supplementary cementitious material for 3D-printed Portland cement

Waste Management Bulletin

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Waste Management Bulletin 2025年第2期3卷 10-20页

作者： da Silveira Júnior, Jairon Gomes Dors Sakata, Rafael Onghero, Lucas de Matos, Paulo Ricardo Rodríguez, Erich David Simão, Lisandro Novaes de Oliveira, Antonio Pedro de Araújo Moura, Ruan Carlos Maduro de Campos, Carlos Eduardo de Castro Pessôa, José Renato Tramontin Souza, Marcelo Department of Engineering and Computing State University of Santa Cruz (UESC) BA Ilhéus 45662-900 Brazil Academic Department of Civil Construction Federal Technological University of Paraná (UTFPR) PR Curitiba 80230-901 Brazil Department of Civil Engineering Federal University of Santa Catarina (UFSC) SC Florianópolis 88037-000 Brazil Department of Civil Engineering Center for Technological Sciences Santa Catarina State University (UDESC) SC Joinville 89219-710 Brazil Department of Structures and Civil Construction Technology Center Federal University of Santa Maria (UFSM) RS Santa Maria 97105-900 Brazil Research Group on Sustainability and Waste Management University of Ribeirão Preto (SP) 14096900 Brazil Department of Mechanical Engineering Federal University of Santa Catarina (UFSC) SC Florianópolis 88040-900 Brazil Department of Physics Federal University of Santa Catarina (UFSC) SC Florianópolis 88040-900 Brazil

This study investigates the use of Al-anodizing waste (AAW), a byproduct of the anodizing process for aluminum and its alloys, in cement composites designed for 3D printing applications. For cementitious materials to be suitable for 3D printing, they must maintain adequate stability to support overlapping layers while also exhibiting sufficient flowability and open time for effective pumping. The incorporation of AAW aims to improve the rheological properties of these mixtures, enhancing both their open time and buildability. To evaluate the potential of AAW in 3D printing cement composites, a comprehensive approach was adopted. This included rheological analysis, flow table testing, investigations into buildability, and assessments of mechanical performance. Additional techniques, such as isothermal calorimetry and in situ X-ray diffraction, were employed to examine the effect of AAW on the hydration kinetics of cement pastes. The findings highlighted several advantages of incorporating AAW into cement-based formulations, such as improved buildability, quick adjustments in rheological properties, prolonged open times, enhanced mechanical performance, cost-effectiveness, and increased sustainability by transforming a commonly discarded material into a valuable resource for civil construction. © 2025 The Authors

关键词： 3D printing Additive manufacturing Al-rich waste Buildability Open time

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Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks

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Scientific Reports 2025年第1期15卷 1-26页

作者： Vu-Hoang, Tran Nguyen, Tan Shiau, Jim Pham-Tran, Hung-Thinh Nguyen-Thoi, Trung Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Smart Computing in Civil Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam School of Engineering University of Southern Queensland Toowoomba 4350 QLD Australia Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical-Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City Viet Nam

This study investigates the uplift capacity of circular anchors embedded in frictional-cohesive soils under surcharge. The analysis focuses on three critical stability factors F_c, F_q, and F_γ using Terzaghi’s principle of superposition to evaluate ultimate bearing capacity. These factors are influenced by the soil’s internal friction angle, the geometric ratio of anchor depth to diameter, and the interface roughness between the anchor and soil. Three predictive models for these stability factors are developed using advanced computational methods, including finite element limit analysis (FELA) with adaptive meshing and Kolmogorov-Arnold Networks (KAN). This research is the first to apply KAN in anchor behavior studies, demonstrating its enhanced ability to model complex data relationships compared to artificial neural networks (ANN). Additionally, a closed-form solution for stability factors is derived through KAN, providing an efficient method for predicting bearing capacity. The optimized models exhibit high coefficient of determination (R²) values and low root mean square errors (RMSE) for training and testing datasets. Sensitivity analysis validates the robustness of the proposed models. These findings advance the understanding of circular anchors’ bearing capacity in frictional-cohesive soils, offering practical design insights for various soil conditions. © The Author(s) 2025.

关键词： Closed-form solution Frictional-cohesive soils Kolmogorov-Arnold networks (KAN) Sensitivity analysis Terzaghi stability factors Uplift capacity

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Probabilistic stability analyses of active shallow trapdoor in spatially random sand

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Probabilistic engineering Mechanics 2025年 80卷

作者： Lai, Fengwei Nguyen, Tan Shiau, Jim Huang, Ming College of Civil Engineering Fuzhou University Fuzhou350108 China Smart Computing in Civil Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam School of Engineering University of Southern Queensland QLD Australia

Understanding the influence of spatial variability in soil friction angle on trapdoor stability remains crucial, particularly in commonly encountered shallow active trapdoor configurations within sandy deposits. This study presents a probabilistic stability assessment of shallow active trapdoors in spatially random sands, employing Random Adaptive Finite Element Limit Analysis (RAFELA) integrated with Monte Carlo simulations (MCs). The numerical solutions, expressed in terms of stability number, are validated through both deterministic and probabilistic analyses. A comprehensive parametric study examines the effects of cover depth, soil friction angle, and spatial variability parameters (including coefficient of variation and horizontal/vertical correlation lengths) on the probability of failure (PF) corresponding to selected factors of safety (FoS). The observed failure mechanisms reveal distinctively variable sliding surfaces, highlighting the nature of random field problems in geomechanics. The study culminates in the development of practical contour-based design charts for a quick assessment of PF in active shallow trapdoors embedded in spatially random sands. These research outcomes offer valuable guidance for engineers, facilitating informed decision-making during preliminary design of buried structures. © 2025 Elsevier Ltd

关键词： Fracture mechanics

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Impact of structural degradation on the seismic resilience of self-built housing: an approach based on intelligent circular resilience

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Journal of Building Pathology and Rehabilitation 2025年第2期10卷 1-22页

作者： Velasquez, Hector Aroquipa Hurtado, Álvaro Soto, Duber Angel, Christiam Research Group on Numerical and Computational Methods Graphic and Scientific Computing Instituto de Investigación Científica Universidad de Lima Santiago de Surco Peru Civil Engineering School Universidad Nacional Autónoma de Tayacaja Daniel Hernández Morillo Pampas Peru Universidad Peruana de Ciencias Aplicadas Lima Peru School of Architecture Urban Planning and Construction Engineering Politecnico di Milano Milan Italy

Self-built housing systems within seismic regions reveal critical deficiencies in structural performance and safety, as these buildings frequently do not meet construction standards, leading to heightened vulnerability during earthquakes. This study evaluates the structural functionality degradation over time and its impact on seismic resilience. A four-step methodology was implemented, comprising: (1) visual inspection, (2) materials testing, (3) structural analysis, and (4) structural degradation assessment through a weighted valuation method. This was applied to 120 self-built houses in Lima, Peru, focusing on stiffness, strength, and ductility parameters. Structural components were evaluated using non-destructive testing methods, while construction pathologies were identified and categorized. The concrete compressive strength (f′c) varies from 110–200 kg/cm2. Additionally, diaphragm configurations, horizontal and vertical irregularities exhibited moderate performance. Common pathologies, including unreinforced walls and improper masonry brick alignment, were observed in over 65% of the houses analyzed. Consequently, structural degradation ranged from 3 to 38% for time spans between 1–30 years. An elastic analysis assessing the seismic response of representative buildings indicated an inter-story drift of around 1.2%. In conclusion, these findings emphasize the need for structural reinforcement. Improving construction practices, enforcing compliance with seismic standards, and providing technical oversight are essential steps to enhancing the seismic resilience of these.

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Airborne pathogen monitoring and dispersion modelling on passenger ships: A review

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Science of the Total Environment 2025年 980卷 179571页

作者： Kumar, Prashant Hama, Sarkawt Cheung, Ho Yin Wickson Hadjichristodoulou, Christos Mouchtouri, Varvara A. Anagnostopoulos, Lemonia Kourentis, Leonidas Wang, Zhaozhi Galea, Edwin R. Ewer, John Grandison, Angus Jia, Fuchen Siilin, Niko School of Engineering Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey GuildfordGU2 7XH United Kingdom Institute for Sustainability University of Surrey Surrey GuildfordGU2 7XH United Kingdom Laboratory of Hygiene and Epidemiology Faculty of Medicine University of Thessaly Larissa41222 Greece Fire Safety Engineering Group School of Computing and Mathematical Sciences Faculty of Engineering and Science University of Greenwich GreenwichSE10 9LS United Kingdom VTT Technical Research Centre of Finland Ltd Espoo02150 Finland Aalto University Department of Civil Engineering Espoo00076 Finland

The COVID-19 pandemic demonstrated a profound inability of pre-pandemic passenger ship policies implemented by both ship operators and governmental authorities to detect and address newly emerging diseases. The essentiality of maritime transport puts into focus the risk of approach to address known and new emerging airborne infectious diseases that, due to increasing capacity, are likely to occur on passenger ships. In order to enhance the passenger experience, prepare shipping for pandemics like COVID-19, and improve the resilience and safety of the industry, this review critically synthesises existing literature on (1) monitoring ventilation conditions and aerosol dispersion, linking them to airborne transmission risk using airborne aerosols and ventilation performance as input parameters for computational fluid dynamics (CFD) simulations, and (2) modelling airborne disease transmission risk in controlled passenger ship environments. This review analysed 39 studies on aerosol monitoring, thermal comfort, and infection risk modelling on passenger ships (2000−2023). Additionally, 55 papers on CFD modelling of airborne pathogen dispersion were reviewed: 22 included validation, with most focused on built environments and only four specifically addressing ship environments. Two major challenges relate to the complexity and poorly characterised ventilation boundary conditions on passenger ships, and the other is the lack of suitable validation data. For this reason, ship experimental studies are required for CFD model validation. Only a handful of studies were found that have measured aerosol concentrations on board passenger ships. To the best of our knowledge, there have been no studies conducted on aerosol mass or airborne transmission sampling on board passenger ships or other types of vessels. The results of this review have the potential to create synergistic connections between experimental and modelling studies to inform, characterise and improve the development

关键词： Risk assessment

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Corrigendum to “GeoTaichi: A Taichi-powered high-performance numerical simulator for multiscale geophysical problems” [Computer Physics Communications 301 (2024) 109219]

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Computer Physics Communications 2025年 309卷

作者： Y.H. Shi N. Guo Z.X. Yang Computing Center for Geotechnical Engineering Engineering Research Center of Urban Underground Space Development of Zhejiang Province Department of Civil Engineering Zhejiang University Hangzhou Zhejiang 310058 China Zhejiang Provincial Engineering Research Center for Digital & Smart Maintenance of Highway China

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Cost-effective aeration solutions for aquaculture: a study on paddle wheel and spiral aerators

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Aquaculture International 2025年第5期33卷 1-23页

作者： Roy, Subha M. Beg, Mirza Masum Tiyasha, Tiyasha Bhagat, Suraj Kumar Kim, Taeho Pareek, C.M. Kumar, Vinay Kumar, Reetesh Abdelrahman, Hisham A. Smart Aquaculture Research Centre Chonnam National University Yeosu 59626 South Korea Department of Fisheries Science Ramnagar College West Bengal Purba Medinipur 721453 India Department of Civil Engineering School of Engineering & Computing Dev Bhoomi Uttarakhand University Uttarkhand Dehradun 248007 India Department of Civil Engineering Faculty of Engineering & Technology Marwadi University Research Center Marwadi University Gujarat Rajkot 360003 India Department of Marine Production Management Chonnam National University Yeosu 59626 South Korea Agricultural and Food Engineering Department IIT Kharagpur West Bengal Kharagpur 721302 India Biomaterials and Tissue Engineering (BITE) Laboratory Department of Community Medicine Saveetha Medical College and Hospital Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai 602105 India Department of Biotechnology Galgotias University Greater Noida 201308 India Galgotias Multi-Disciplinary Research & Development Cell (G-MRDC) Galgotias University Greater Noida 201308 India Department of Veterinary Hygiene and Management Faculty of Veterinary Medicine Cairo University Giza 12211 Egypt Department of Biology Marine Biology and Environmental Science Roger Williams University Bristol 02809 RI United States

The primary objective is to select an appropriate aerator that maximizes the benefits while minimizing the operational costs of the aeration system in aquaculture operations. The choice of suitable aerators significantly impacts the cost of aquaculture operations. Therefore, this study focuses on the economic analysis of the paddle wheel aerator (PWA) and its modified counterpart, the spiral aerator (SA). The efficiency of the PWA and SA was assessed with respect to rotational speed (N), based on the efficiency a comparative economic analysis was conducted. The economics of aerators depends on the various pond sizes, initial dissolved oxygen (DO), and aerators running hours. Therefore, the total aeration cost for the chosen aerators was determined at various pond volumes (100, 200, 300, 700, 1000, 5000, and 10,000 m³ with depth of water 1.0 m) and initial DO of pond water denoted as C_P = 1 to 4 mg/L. According to market rates, the primary cost for PWA was ₹32,000, while that for SA was ₹42,000. From the findings, pond sizes in the range of 100 to 10,000 m³ PWA are more economical than SA. Therefore, a new selection method of economically feasible aerators in aquaculture pond was developed in this study. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Aeration Aquaculture Cost economics Handling Editor: Brian Austin Paddle wheel aerator Spiral aerator

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