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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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Frontiers of Structural and civil engineering 2023年第2期17卷 284-305页

作者： Hai-Van Thi MAI May Huu NGUYEN Son Hoang TRINH Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

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Development of a hazard risk map for assessing pedestrian risk in urban flash floods:A case study in Cúcuta,Colombia

River

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River 2024年第1期3卷 8-23页

作者： Gerald Augusto Corzo Perez Diego Ivan Sanchez Tapiero Manuel Antonio Contreras Martínez Chris Zevenbergen IHE Delft Institute for Water Education Hydroinformatics and Digital InnovationDelftThe Netherlands Master in Environmental Engineering Civil Engineering ProgramFaculty of Engineering and ArchitectureUniversity of PamplonaPamplonaColombia Faculty of Civil Engineering and Geosciences Delft University of TechnologyDelftThe Netherlands

The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities,leading to severe flooding and significant economic losses for *** trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians,which is often overlooked in traditional flood hazard *** study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods,with a specific focus on Cúcuta,*** methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological *** computational algorithms for image recognition were used to measure water levels at 5-s intervals on November 6,2020,using drones for digital elevation model data *** Cúcuta,where flood risk is high and drainage infrastructure is limited,the PCSWMM(Computer-based Urban Stormwater Management Model)was calibrated and validated to simulate extreme flood *** model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban *** return periods(5,10,50,100),with extreme rainfall of 3 h,were used to estimate the variability of the risk *** output of the model was analyzed,and an integrated and time-varying comparison of the results was *** show that the regions of high-water depth and high velocity could vary significantly along the duration of the different extreme ***,from 5 to 100 years return period,the percentage of area at risk increased from 9.6%to 16.6%.The pedestrian sensitivity appears much higher than the increase in velocities or water depth *** study identified medium to high-risk locations,which are dynamic in *** can conclude dynamics are spatiotemporal,and the added information layer of pedestrians brings vulnerability information that is a

关键词： hazard and risk mapping pedestrian risk urban flood

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Analytical Evaluation of Natural Frequencies in Hollow-Core Slabs: A Practical Methodology for civil engineering Applications

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Iranian Journal of Science and technology - Transactions of civil engineering 2024年第2期49卷 1979-1991页

作者： Zenatti, Carlos N. Silveira, Guilherme S. Gidrão, Gustavo M. S. Novak, Paulo Rogério Bosse, Rúbia Mara Silvestro, Laura Marcos, Lara K. Civil Engineering Postgraduate Program PPGEC Federal University of Technology - Paraná (UTFPR) Paraná Pato Branco Brazil

This study presents an analytical methodology for predicting the natural frequencies of hollow-core slab panels, addressing a significant research and application need in structural engineering. The study suggests a numerical–experimental calibration utilizing the Finite Element Method (FEM) via ANSYS software to assess the modal response of hollow-core slabs validated according to literature study. Through the development of Irvine’s equation, this research proposes a simplified methodology for determining the natural frequency of slabs. The slabs were modeled as simply supported beams, and Irvine’s equations have been applied to simplify several degrees of freedom structure (SDOF) and determine the natural frequencies for various spans. The validation of the numerical–experimental model indicates a maximum error of 8.32% in the third vibration mode, demonstrating the accuracy and practicality of the proposed analytical method. This approach could be useful in determining the vibration serviceability presented in Brazilian Standard Procedure for the Design of Concrete Structures. It can help engineers and manufacturers to estimate structural compliance and vibration serviceability. © The Author(s), under exclusive licence to Shiraz University 2024.

关键词： Analytical method Hollow-core slab Modal analysis Natural frequency

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Application of machine learning technique for predicting and evaluating chloride ingress in concrete

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Frontiers of Structural and civil engineering 2022年第9期16卷 1153-1169页

作者： Van Quan TRAN Van Loi GIAP Dinh Phien VU Riya Catherine GEORGE Lanh Si HO Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

The degradation of concrete structure in the marine environment is often related to chloride-induced corrosion of reinforcement ***,the chloride concentration in concrete is a vital parameter for estimating the corrosion level of reinforcement *** research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting(GB),artificial neural network(ANN),and random forest(RF)in combination with particle swarm optimization(PSO).The input variables for modeling include exposure condition,water/binder ratio(W/B),cement content,silica fume,time exposure,and depth of *** results indicate that three models performed well with high accuracy of prediction(R2⩾0.90).Among three hybrid models,the model using GB_PSO achieved the highest prediction accuracy(R2=0.9551,RMSE=0.0327,and MAE=0.0181).Based on the results of sensitivity analysis using SHapley Additive exPlanation(SHAP)and partial dependence plots 1D(PDP-1D),it was found that the exposure condition and depth of measurement were the two most vital variables affecting the prediction of chloride *** the number of different exposure conditions is larger than two,the exposure significantly impacted the chloride content of concrete because the chloride ion ingress is affected by both chemical and physical *** study provides an insight into the evaluation and prediction of the chloride content of concrete in the marine environment.

关键词： gradient boosting random forest chloride content concrete sensitivity analysis

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

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Frontiers of Structural and civil engineering 2022年第8期16卷 990-1002页

作者： Hai-Bang LY Thuy-Anh NGUYEN Binh Thai PHAM May Huu NGUYEN Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

This study examined the feasibility of using the grey wolf optimizer(GWO)and artificial neural network(ANN)to predict the compressive strength(CS)of self-compacting concrete(SCC).The ANN-GWO model was created using 115 samples from different sources,taking into account nine key SCC *** validation of the proposed model was evaluated via six indices,including correlation coefficient(R),mean squared error,mean absolute error(MAE),IA,Slope,and mean absolute percentage *** addition,the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence *** results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s *** that,an examination of the parameters impacting the CS of SCC was provided.

关键词： artificial neural network grey wolf optimize algorithm compressive strength self-compacting concrete

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Dimensionality reduction and prediction of soil consolidation coefficient using random forest coupling with Relief algorithm

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Frontiers of Structural and civil engineering 2022年第2期16卷 224-238页

作者： Hai-Bang LY Huong-Lan Thi VU Lanh Si HO Binh Thai PHAM Department of Civil Engineering University of Transport TechnologyHanoi100000Vietnam Civil and Environmental Engineering Program Hiroshima UniversityHiroshima739-8527Japan Department of Science Technology and International CooperationUniversity of Transport TechnologyHanoi100000Vietnam

The consolidation coefficient of soil(C_(v))is a crucial parameter used for the design of structures leaned on soft *** general,the C_(v) is determined experimentally in the ***,the experimental tests are time-consuming as well as ***,researchers tried several ways to determine C_(v) via other simple soil *** this study,we developed a hybrid model of Random Forest coupling with a Relief algorithm(RF-RL)to predict the C_(v) of *** conduct this study,a database of soil parameters collected from a case study region in Vietnam was used for *** performance of the proposed models was assessed via statistical indicators,namely Coefficient of determination(R^(2)),Root Mean Squared Error(RMSE),and Mean Absolute Error(MAE).The proposal models were constructed with four sets of soil variables,including 6,7,8,and 13 *** results revealed that all models performed well with a high performance(R^(2)>0.980).Although the RF-RL model with 13 variables has the highest prediction accuracy(R^(2)=0.9869),the difference compared with other models was negligible(i.e.,R^(2)=0.9824,0.9850,0.9825 for the cases with 6,7,8 inputs,respectively).Thus,it can be concluded that the hybrid model of RF-RL can be employed to predict C_(v) based on the basic soil parameters.

关键词： soil consolidation coefficient machine learning random forest Relief

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Surface-enhanced Raman spectroscopy for emerging contaminant analysis in drinking water

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Frontiers of Environmental Science & engineering 2023年第5期17卷 51-65页

作者： Seo Won Cho Haoran Wei Environmental Chemistry and Technology Program University of Wisconsin–MadisonMadisonWI 53706USA Department of Civil and Environmental Engineering University of Wisconsin–MadisonMadisonWI 53706USA

Emerging contaminants(ECs)in drinking water pose threats to public health due to their environmental prevalence and potential *** occurrence of ECs in our drinking water supplies depends on their physicochemical properties,discharging rate,and susceptibility to removal by water treatment *** health effects of long-term exposure to ECs justify their regular monitoring in drinking water *** this review article,we will summarize the current status and future opportunities of surface-enhanced Raman spectroscopy(SERS)for EC analysis in drinking *** principles of SERS are first introduced and a comparison of SERS and liquid chromatography-tandem mass spectrometry in terms of cost,time,sensitivity,and availability is ***,we discuss the strategies for designing effective SERS sensors for EC analysis based on five categories—per-and polyfluoroalkyl substances,novel pesticides,pharmaceuticals,endocrine-disrupting chemicals,and *** addition to maximizing the intrinsic enhancement factors of SERS substrates,strategies to improve hot spot accessibilities to the targeting ECs are equally *** is a review article focusing on SERS analysis of ECs in drinking *** discussions are not only guided by numerous endeavors to advance SERS technology but also by the drinking water regulatory policy.

关键词： Emerging contaminant Surface-enhanced Raman spectroscopy Drinking water monitoring Sensor Regulatory policy

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Strength and Permeability of Thermally Consolidated Soft Ground

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Geotechnical and Geological engineering 2025年第5期43卷 1-24页

作者： Srisakul, Watchara Chub-uppakarn, Tanan Chompoorat, Thanakorn Department of Engineering Technology Faculty of Engineering and Technology Rajamangala University of Technology Srivijaya Trang92150 Thailand Department of Civil and Environmental Engineering Faculty of Engineering Prince of Songkla University Songkhla90110 Thailand Southern Natural Disaster Research Center Prince of Songkla University Songkhla90110 Thailand Civil Engineering Program School of Engineering University of Phayao Phayao56000 Thailand

This study investigates the effects of thermal treatment on the mechanical behavior of highly compressible Pak Phanang clay, a soft soil with low strength that typically requires advanced ground improvement methods. Heating is considered a promising technique for enhancing foundation stability, particularly for critical infrastructure. The research focuses on the thermo-mechanical behavior of the clay, emphasizing consolidation and solidification processes that influence load-bearing capacity. Isotropically consolidated undrained triaxial tests were conducted at temperatures of 30 °C, 40 °C, 50 °C, and 60 °C with over-consolidation ratios (OCR) of 1, 2, 4, and 8. The results showed that increasing temperature significantly enhanced both peak deviator stress (qu) and the secant Young’s modulus (E50), with a strong linear correlation: E50=108.70×qu. Dry density increased and organic matter content slightly decreased under thermal treatment, particularly in normally consolidated clay. Excess pore water pressure (EPWP) increased linearly with temperature across all OCR values. Consolidation volume change also increased with temperature but decreased as OCR rose. The coefficient of consolidation (Cv) improved with temperature, leading to faster consolidation, especially in normally consolidated specimens. The coefficient of permeability (k) increased with temperature but declined with higher OCR, with k rising by 14.6%–24.2% from 30 °C to 60 °C in normally consolidated samples. Predictive models for qu and k based on temperature and OCR demonstrated high accuracy. Overall, the findings provide a reliable understanding of the thermal–mechanical response of this clay type, supporting its application in temperature-assisted ground improvement. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Shear strength

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Life Cycle Assessment and Sustainability Characteristics of Built Environment Systems 4th

Life Cycle Assessment and Sustainability Characteristics of ...

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4th International Conference on Coordinating engineering for Sustainability and Resilience and the Midterm Conference of the COST Action CircularB on Implementation of Circular Economy in the Built Environment, CESARE 2024

作者： Alkhawaldeh, Ayah Betoush, Nour Sawalha, Ansam Alhassan, Mohammad Abdalla, Khairedin Department of Civil Engineering American University of Madaba Madaba Jordan Department of Civil Engineering Jordan University of Science and Technology Irbid Jordan Civil Engineering Program Al Ain University Al Ain United Arab Emirates

ISBN: (纸本)9783031577994

The sustainable built environment concept has recently gained enormous attention from academic and industrial organizations. The growth in climate-related disasters and pandemics, continuing difficulties in the energy sector, and consumer awareness regarding resources’ conservation and sustainability are considered the driving factors influencing participants toward supporting sustainable engineering applications. Furthermore, numerous professional standards and requirements for implementing and rating sustainable practices have been generated, such as life cycle assessment (LCA), cost analysis, project development (i.e., from planning through construction up to demolition), recycling, material preservation, and utilizing reusable materials. The LCA is a great method for examining and integrating a wide variety of environmental elements to provide a comprehensive picture of system sustainability. The research presented in this study covered significant environmental elements that are essential to deciding between two or more choices and improving the system. This research compared the OPC and AABC based on CO2 emissions. The results showed that the AABC produces positive sustainability outcomes in terms of CO2 emissions. The AABC emits substantially less CO2 than the OPC, indicating that it is preferable for greenhouse buildings. © The Author(s) 2024.

关键词： Life cycle

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Analysing the Diurnal Evolution of Land Surface Temperature During Heat Wave Event at High Spatial Resolution 3

Analysing the Diurnal Evolution of Land Surface Temperature ...

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3rd IEEE India Geoscience and Remote Sensing Symposium, InGARSS 2023

作者： Sara, Kukku Rajasekaran, Eswar Indian Institute of Technology Bombay Department of Civil Engineering Mumbai India Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay Department of Civil Engineering Mumbai India

ISBN: (纸本)9798350325591

In recent decades, frequently reported heat waves attributed to climate change have profoundly affected human health and food production and posed challenges to the sustainable development goals of a densely populated country like India. This study investigates the spatial and temporal trends of Land Surface Temperature (LST) during heat wave period, utilizing high spatio-temporal resolution LST data across two distinct geographical regions of India where instances of heat events have been reported. The high spatiotemporal LST was derived using a hybrid approach combining multi-variate spatial disaggregation and diurnal temperature cycle modelling. The diurnal parameters derived using the proposed methodology were compared during the heat wave year and a normal year. The results show that these diurnal parameters of LST can offer valuable insights into extreme temperature events and have the potential to aid in the mitigation of vegetative stress and consequences on human population during such extreme events. © 2023 IEEE.

关键词： Surface measurement

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