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2nd International Conference on Sustainable Civil engineering and Architecture, ICSCEA 2021

作者： Kirimoto, Taishi Ogawa, Yuko Kawai, Kenji Civil and Environmental Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University Higashihiroshima City Japan

ISBN: (纸本)9789811933028

The purpose of this study was to clarify the relationship between the internal curing effect of roof-tile waste aggregate and frost damage resistance, and to investigate the effects of the replacement ratio of roof-tile waste aggregate as well as curing conditions on the frost damage resistance of concrete. Five types of concrete using Portland blast-furnace slag cement were prepared with a water-to-cement ratio of 0.50 and different replacement ratios of roof-tile waste coarse aggregate (20% and 50% by volume) and roof-tile waste fine aggregate (23% and 58% by volume). Concrete specimens were cured at 20 °C under sealed condition for 3, 7, or 28 days, and they were subsequently exposed to air at 20 °C and 60%R.H. until the age of 28 days. Then, the tests for resistance of concrete to freezing and thawing were carried out for 300 cycles in water, and the relative dynamic modulus of elasticity as well as the mass loss was assessed at the designated periods. As a result, it was found that sufficient frost damage resistance could be secured when the replacement ratio of roof-tile waste aggregate was approximately 20% by volume, and the improvement in frost damage resistance was observed especially when fine aggregate was replaced. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Slags

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.E.Al-Atroush A.E.Aboelela Ezz El-Din Hemdan Civil and Environmental Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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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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Low-Temperature Methanolysis of Polycarbonate over Solid Base Sodium Aluminate

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Langmuir 2024年第10期40卷 5338-5347页

作者： Krisbiantoro, Philip Anggo Sato, Miyu Lin, Tzu-Ming Chang, Yu-Chia Peng, Tzu-Yun Wu, Yun-Chih Liao, Weisheng Kamiya, Yuichi Otomo, Ryoichi Wu, Kevin C.-W. Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering College of Engineering National Taiwan University Taipei10617 Taiwan Graduate School of Environmental Science Hokkaido University Nishi 5 Kita 10 Sapporo060-0810 Japan Faculty of Environmental Earth Science Hokkaido University Nishi 5 Kita 10 Sapporo060-0810 Japan Center of Atomic Initiative for New Materials National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Taoyuan320 Taiwan

Herein, a low-cost and readily available sodium aluminate (NaAlO2) was used as a solid base catalyst for the depolymerization of polycarbonate (PC) via methanolysis in the presence of tetrahydrofuran (THF) as a solvent. NaAlO2 was highly active for the reaction, and the performance was comparable to that of soluble strong base SrO and much higher than those of MgO and CaO. By the reaction over the catalyst, a highly pure and crystalline bisphenol A (BPA) was obtained. Among tested organic solvents, THF was the best in aiding PC methanolysis over NaAlO2 due to the polarity similar to PC according to Hansen solubility parameters (HSPs). At 60 °C, 98.1% PC conversion and 96.8% BPA yield were achieved within just 2 h. NaAlO2 was reusable without any severe catalyst deactivation in at least four runs. The mechanistic study revealed that the reaction proceeded via the methoxide pathway, with THF aiding the dissolution of PC. The reaction over NaAlO2 possessed a low apparent activation energy (Ea) of 75.1 kJ mol-1, which is the lowest ever reported so far for the reaction over solid catalysts. © 2024 The Authors. Published by American Chemical Society.

关键词： Sodium Aluminate

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比较三种稳定剂对FeS纳米颗粒的稳定效果及对水土中镉的固定与去除性能的影响

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Journal of Central South University 2024年第4期31卷 1064-1075页

作者：田舒婷赵东叶霍丽娟马骏杨睿 Department of Environmental Science School of Environment and ResourcesTaiyuan University of Science and TechnologyTaiyuan 030024China Environmental Engineering Program Department of Civil&Environmental EngineeringAuburn UniversityAuburnAL 36849USA Department of Civil Constructionand Environmental EngineeringSan Diego State UniversitySan DiegoCA 92182USA

本研究评估了三种多糖稳定剂(羧甲基纤维素钠(CMC)、羧甲基淀粉钠(CMS)和一种水溶性淀粉)用于稳定FeS纳米颗粒的有效性,并测试了相应稳定化纳米颗粒在水和土壤中固定Cd^(2+)的性能。使用0.010 wt%CMC、0.025 wt%CMS或0.065 wt%淀粉可获... 详细信息

本研究评估了三种多糖稳定剂(羧甲基纤维素钠(CMC)、羧甲基淀粉钠(CMS)和一种水溶性淀粉)用于稳定FeS纳米颗粒的有效性,并测试了相应稳定化纳米颗粒在水和土壤中固定Cd^(2+)的性能。使用0.010 wt%CMC、0.025 wt%CMS或0.065 wt%淀粉可获得完全稳定的FeS纳米颗粒(100 mg/L FeS)。CMC-FeS表现出较高的zeta负电位,淀粉-FeS保持中性,而CMS-FeS则表现出中等负电位。CMCFeS对Cd^(2+)的吸附速率最快,吸附容量也最高。当用100 mg/L CMC-FeS或CMS-FeS处理一种含Cd土壤(58.3 mg/kg Cd)后,Cd的TCLP浸出率分别降低了88.4%和68.0%。CMC-FeS和CMS-FeS均可在模型土壤中运移,显示出其在土壤中原位固定Cd^(2+)方面的潜力。土壤穿透曲线实验表明,CMC-FeS在4.5个孔体积,CMS-FeS在约25个孔体积处几乎完全穿透。柱实验结果表明,当用55个孔体积的CMC-FeS或CMS-FeS悬浮液(100 mg/L)处理该含Cd土壤后,Cd的水浸出率分别降低了98.2%和98.0%。根据目标污染物、材料在土壤中的传输特性和材料成本,可找到这三种稳定剂在土壤修复中的最佳应用。

关键词：硫化铁纳米颗粒稳定剂重金属污染物固定土壤修复地下水污染

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Comparison on Efficiency of Iron and Aluminum Nanoparticles for Methylene Blue Removal from Aqueous Solutions

Comparison on Efficiency of Iron and Aluminum Nanoparticles ...

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2023 AIChE Annual Meeting

作者： Mostafa, Mohamed K. Sadek, Ahmed H. Cairo Egypt Environmental Engineering Program Zewail City of Science Technology and Innovation Giza Egypt Giza Egypt

This review demonstrates a comparative study of methylene blue (MB) dye removal from aqueous solutions using zero-valent iron (nZVI) and zero-valent aluminum (nZVAl) nanoparticles. The results indicated that at pH 6, nZVI dosage 10 g/L, initial MB concentration 10 mg/L, temperature 30 °C, and stirring rate 150 rpm, the equilibrium time was 30 min achieving a removal efficiency of approximately 100% for nZVI. While for nZVAl, the results indicated that at an initial MB concentration of 10 mg/L, pH 10, nZVAl dosage 1.0 g/L, stirring rate 200 rpm, and temperature 30 °C, the removal efficiency of approximately 99.0% was achieved within an equilibrium time of 90 min. Moreover, the adsorption data of MB fitted well to the Freundlich isotherm model (R2: 0.9358) and pseudo-second-order kinetic model (R2: 0.9976) for adsorption by nZVI. Also, the isotherm adsorption data were best fitted by the Freundlich isotherm model (R2: 0.9569), while the kinetic data were well described by the pseudo-second-order model (R2: 0.9999) for adsorption by nZVAl. From the aforementioned results, it is clear that both nZVI and nZVAl showed very high efficiency in removing methylene blue from aqueous solutions with a slight difference in favor of nZVI. © 2023 American Institute of Chemical Engineers. All rights reserved.

关键词： Aluminum

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Applicability of Electrical Resistance Method to Moisture Transfer Measurement in Paste Using Mineral Admixture 2nd

Applicability of Electrical Resistance Method to Moisture Tr...

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2nd International Conference on Sustainable Civil engineering and Architecture, ICSCEA 2021

作者： Aoki, Takahiro Ogawa, Yuko Kawai, Kenji Civil and Environmental Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashihiroshima Japan

ISBN: (纸本)9789811933028

Concrete is a porous material which has the ability to hold moisture stably inside. Since moisture is closely related to the deterioration of concrete structures, it is important to understand the moisture transfer in concrete in order to maintain the concrete structure appropriately. The electrical resistance method is one of non-destructive methods to investigate the moisture in concrete and the moisture transfer can be assessed with time by using one specimen. However, the electrical resistance may be affected by mineral admixtures in concrete. Although previous studies on the effects of mineral admixtures on the electrical resistance have been conducted, there are still many unclear points. Therefore, the purpose of this study is to assess the applicability of the electrical resistance method to moisture transfer measurement in paste containing mineral admixtures by focusing on the moisture transfer in the drying process. The moisture transfer in the hardened cement paste using fly ash and blast furnace slag with water-to-binder ratios of 0.35 and 0.55 was investigated by the electrical resistance method. Stainless steel rods of 0.9 mm in diameter were placed at an interval of 4 mm in the specimen. The calibration test was also conducted to obtain the relationship between the electrical resistivity and the internal relative humidity of the specimen. The result showed that the specific resistance of the specimen containing mineral admixtures was higher than that of the specimen without mineral admixtures. It was observed that at the drying period of 70 days, the internal relative humidity at a depth of 4 mm from the exposed surface was almost the same as the surrounding relative humidity. It is possible to know the change in the internal relative humidity distribution in the cement paste using mineral admixtures during the drying process by performing the calibration test appropriately. © 2023, The Author(s), under exclusive license to Springer Nature Singapore P

关键词： Concretes

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Direct Multi-group Cross-sections via NJOY+OJOYU for PWR and FLiBe-MSR Reactor Systems

Direct Multi-group Cross-sections via NJOY+OJOYU for PWR and...

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2023 Transactions of the American Nuclear Society Annual Meeting and Technology Expo, ANS 2023

作者： Wang, Meng-Jen Simpson, Michael Sjoden, Glenn E. Nuclear Engineering Program Department of Civil and Environmental Engineering University of Utah United States Department of Material Science and Engineering University of Utah United States

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Sulfur-doped hard carbon hybrid anodes with dual lithium-ion/metal storage bifunctionality for high-energy-density lithium-ion batteries

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Carbon Energy 2023年第1期5卷 71-81页

作者： Sungmin Cho Jong Chan Hyun Son Ha Yeonhua Choi Honggyu Seong Jaewon Choi Hyoung-Joon Jin Young Soo Yun Program in Environmental and Polymer Engineering Inha UniversityIncheonSouth Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoulSouth Korea Departmant of Chemistry and Research Institute of Natural Science Gyeongsang National UniversityJinjuSouth Korea Department of Polymer Science and Engineering Inha UniversityIncheonSouth Korea Division of Energy Engineering Kangwon National UniversityGangwon-doSouth Korea

Bifunctional hybrid anodes(BHAs),which are both a high-performance active host material for lithium-ion storage as well as a guiding agent for homogeneous lithium metal nucleation and growth,exhibit significant potential as anodes for next-generation high-energy-density lithium-ion batteries(LIBs).In this study,sulfur-doped hard carbon nanosphere assemblies(S-HCNAs)were prepared through a hydrothermal treatment of a liquid organic precursor,followed by high-temperature thermal annealing with elemental sulfur for application as BHAs for *** a carbonate-based electrolyte containing fluoroethylene carbonate additive,the S-HCNAs showed high lithium-ion storage capacities in sloping as well as plateau voltage sections,good rate capabilities,and stable *** addition,high average Coulombic efficiencies(CEs)of~96.9%were achieved for dual lithium-ion and lithium metal storage *** the LIB full-cell tests with typical NCM811 cathodes,the S-HCNA-based BHAs containing~400 mA h g^(−1) of excess lithium led to high energy and power densities of~500Wh kg^(−1) and~1695Wkg^(−1),respectively,and a stable cycling performance with~100%CEs was achieved.

关键词： hard carbon hybrid anode lithium-ion batteries lithium metal anode lithium metal batteries sulfur-doped carbon

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