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Application of fluidized-bed homogeneous crystallization technology to carbon sequestration and recovery from flue gas

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Sustainable Environment Research 2024年第1期34卷 1-16页

作者： Huang, Po-Chun Vilando, Anabella C. Ha, Thi-Hanh Lu, Ming-Chun Department of Environmental Engineering National Chung Hsing University Taichung City40227 Taiwan College of Engineering and Architecture Bicol State College of Applied Sciences and Technology Naga City4400 Philippines

The Earth’s energy balance produced by human activity is the main factor in the complex relationship between greenhouse gases and global warming. The Taiwan Environmental Protection Agency reports that carbon dioxide makes up more than 95% of Taiwan’s most recent greenhouse gas emissions. This study used fluidized-bed homogeneous crystallization (FBHC) technology to recover carbonate in a simulated CO2-enriched flue gas. It was specifically designed to determine how carbonate removal and crystallization efficiency were affected by carbonate surface loading, the influence of the source of calcium ions, and interfering substances. Results revealed that the best surface loading at 55 kg m− 2 h− 1 achieved 93% removal and 84% crystallization efficiency. At 50 mg L− 1 of sulfate ions, the presence of more interfering compounds tends to reduce carbonate removal to 97% and 91% crystallization. Regarding X-ray diffraction data, the recovered carbonate crystals resembled calcium carbonate crystals. It has been demonstrated that carbonate can be recovered using FBHC technology as a method of CO2 capture and storage. © The Author(s) 2024.

关键词： Calcium carbonate

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Evolving multi-objective optimization framework for early-stage building design:Improving energy efficiency,daylighting,view quality,and thermal comfort

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Building Simulation 2024年第11期17卷 2097-2123页

作者： Lingrui Li Zongxin Qi Qingsong Ma Weijun Gao Xindong Wei College of Architecture and Urban Planning Qingdao University of TechnologyQingdao266033China iSMART Qingdao University of TechnologyQingdao266033China Department of Architecture The University of KitakyushuKitakyushu808-0135Japan School of Environmental and Municipal Engineering Jilin Jianzhu UniversityChangchun130118China

Computational performance-driven design optimization(CPDDO)informs early building design decisions,enhancing projects’responsiveness to local *** paper reviews recent CPDDO studies,identifies prevalent gaps,and proposes a refined optimization *** framework stands out by:(1)integrating view quality alongside energy,daylight,and thermal comfort considerations,with a vector-simulation-based metric considering content,access and clarity;(2)incorporating users’adaptive behavior patterns in simulations;and(3)employing a hybrid weighting method to accommodate diverse project demands and support robust design *** study applies the framework to optimize the shape and facade variables of a medium-sized office building in Guangzhou,Chongqing,Qingdao,Lanzhou,and Changchun,representing hot,warm,mixed,cool,and cold climates,*** highlight that geometry features(aspect ratio,orientation,window-to-wall ratio(WWR),and shading devices),as well as window and blinds constructions significantly impact energy,daylight,thermal comfort and view *** climatic conditions,objective priorities,and facade orientations necessitate tailored design ***,certain findings challenge conventional recommendations;for instance,buildings in colder climates benefit from increased WWR,due to enhanced potential to harness solar radiation and improved view access,while high-performance envelope thermal settings mitigate heat *** findings underscore the need for detailed,targeted research in early-stage *** developed CPDDO framework proves effective and user-friendly,offering new possibilities for optimizing building performance,thus holds the potential to foster green,comfortable,and sustainable architecture in various practical applications.

关键词： multi-objective optimization building performance simulation window view quality occupants’adaptive behavior hybrid weighting method

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Numerical Study on the Pulsation Characteristics of An Attached Air Bubble Under A Nearby Oscillating Bubble

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China Ocean engineering 2023年第2期37卷 299-311页

作者： JIANG Ming-zuo LIU Kun WANG Jia-xia WEN Xiao-hu College of Automation Jiangsu University of Science and TechnologyZhenjiang 212003China School of Naval Architecture and Ocean Engineering Jiangsu University of Science and TechnologyZhenjiang 212003China

Numerical simulations of the non-spherical evolution of a pulsating bubble interacting with a stationary air bubble attached to a fixed structure were performed using a three-dimensional boundary integral method by implementing the mirror image method to simplify the processing of the numerical model. Code validation was accomplished by comparing the numerical results with the laboratory experimental data obtained in our previous study. Complex phenomena were observed, including three types of bubble jet forms, which depended strongly on the distance parameter with respect to the initial location of the bubble from the plate, the bubble strength parameter and the initial air bubble radius parameters. The results of the simulations provide detail insight into interesting bubble jetting phenomena,such as bubble splitting, jets moving away from the plate, and bubble shedding. The dimensionless distance parameter and the initial air bubble radius parameter play a major role in determining the shapes of two bubbles and the jetting direction. The air bubble strength parameter did not change the bubble jet direction but influenced the bubble *** detachment of the attached air bubble under oscillating bubble suction was easily observed for a small initial air bubble. These results showed that bubble jetting toward the plate was manipulated through the effect of attached air bubble, and that cavitation-based applications and underwater explosion bubble may benefit from this erosion mitigation approach.

关键词： bubble dynamics attached air bubble bubble collapse liquid jet

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Landslide Deformation Uncertainty Quantification using Conformalized Graph Neural Networks: A Case Study in Sichuan Province, China

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IEEE Access 2025年 13卷 86719-86731页

作者： Ren, Xiaopeng Liu, Wei Yang, Weiqi Mao, Lixuan Li, Huajin Sichuan College of Architectural Technology Department of Civil Engineering Deyang618000 China Sichuan College of Architectural Technology Department of Architecture Deyang618000 China Meta Platforms Inc Menlo ParkCA94025 United States Chengdu University School of Architecture and Civil Engineering Chengdu610106 China Chengdu University Sichuan Engineering Research Center for Mechanical Properties and Engineering Technology of Unsaturated Soils Chengdu610106 China

Landslide deformation prediction plays a crucial role in geohazard risk management, yet existing methods often struggle to quantify prediction uncertainties effectively. This paper presents GNN-CF, a novel framework that integrates Graph Neural Networks (GNN) with Conformal Prediction for reliable interval forecasting of landslide deformation. The proposed approach addresses two significant challenges: ensuring valid marginal coverage despite dependencies between calibration (training) and test data, and reducing prediction interval inefficiency while maintaining coverage guarantees. The framework incorporates a topology-aware correction model and employs graph-based regularization terms to enhance prediction accuracy. The methodology is validated using field monitoring data from the Wutong Village landslide in Sichuan Province, China, where six GNSS monitoring points track surface deformation patterns. Experimental results demonstrate that GNN-CF consistently outperforms state-of-the-art methods, including GRU-LUBE, DNLSSM, and SA-DeepAR, achieving superior Prediction Interval Coverage Probability (PICP) while maintaining smaller Prediction Interval Normalized Average Width (PINAW). The framework’s effectiveness in balancing coverage and computational complexity makes it a feasible solution for landslide monitoring applications requiring reliable uncertainty quantification. © 2013 IEEE.

关键词： Risk management

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Quantifying Uncertainty in Dielectric Solids’ Mechanical Properties Using Isogeometric Analysis and Conditional Generative Adversarial Networks

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2587-2611页

作者： Shuai Li Xiaodong Zhao Jinghu Zhou Xiyue Wang College of Civil Engineering&Architecture Dalian UniversityDalian116622China Research Center for Geotechnical and Structural Engineering Technology of Liaoning Province Dalian UniversityDalian116622China

Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains,necessitating the development of robust com-putational *** paper introduces a Conditional Generation Adversarial Network Isogeometric Analysis(CGAN-IGA)to assess the uncertainty of dielectric solids’mechanical *** is utilized for the precise computation of electric potentials in dielectric,piezoelectric,and flexoelectric materials,leveraging its advantage of integrating seamlessly with Computer-Aided Design(CAD)models to maintain exact geometrical *** CGAN method is highly efficient in generating models for piezoelectric and flexoelectric materials,specifically adapting to targeted design requirements and ***,the CGAN-IGA is adopted to calculate the electric potential of optimum models with different parameters to accelerate uncertainty quantification *** accuracy and feasibility of this method are verified through numerical experiments presented herein.

关键词： Dielectric solid isogeometric finite element method surrogate model generative adversarial

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Prediction of building HVAC energy consumption based on least squares support vector machines

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Energy Informatics 2024年第1期7卷 113页

作者： Wan, Xin Cai, Xiaoling Dai, Lele School of Architecture and Environmental Engineering Wuxi City College of Vocational Technology Wuxi Jiangsu214153 China School of Energy and Power Engineering Nanjing University of Science and Technology Nanjing210094 China

Air conditioning, as an essential appliance in daily life, has the function of ensuring comfortable room temperature, but it is also accompanied by a large amount of power consumption. Consequently, the study suggests an energy consumption prediction model based on improved genetic algorithm—least squares support vector machine—to accurately predict the energy consumption of building heating, ventilation, and air conditioning. This model uses the improved genetic algorithm for regularization parameter and kernel parameter optimization to prevent overfitting and underfitting issues. According to the testing results, the least squares support vector machine, an upgraded genetic algorithm, may accomplish convergence faster than other algorithms, taking only 0.2 milliseconds to finish. In addition, the average relative error of the improved genetic algorithm- least squares support vector machine did not exceed 0.6%. In the energy consumption prediction for the whole year of 2022, the average error of the improved genetic algorithm-least squares support vector machine was only 2.0 × 106 kWh, and the prediction accuracy could reach up to 97.2%. The above outcomes revealed that the energy consumption prediction model can accurately predict the air conditioning energy consumption, which provides a strong support for the control and optimization of the air conditioning system. © The Author(s) 2024.

关键词： Prediction models

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Back Propagation Neural Network Model for Railway Risk Warning 6

Back Propagation Neural Network Model for Railway Risk Warni...

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6th International Conference on Electronics and Communication, Network and Computer technology, ECNCT 2024

作者： Duan, Baofu Yang, Yunqian Jing, Zhe Wei, Yuguan Chu, Anni Bu, Liankai College of Civil Engineering and Architecture Shandong University of Science and Technology Huangdao Shandong Qingdao China College of Civil Engineering and Architecture Shandong University of Science and Technology Shandong Qingdao China

ISBN: (纸本)9798350366143

To effectively warn of railway risk accidents, a railway safety risk warning model based on neural network theory and the characteristics of railway safety risks was established. Taking the current situation of railway construction in a certain province as an example, the neural network model was trained and applied using expert evaluation data. By comparing with the measured values, it is found that the predicted results of the neural network model are close to the measured values. © 2024 IEEE.

关键词： Neural network models

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Generalized nth-Order Perturbation Method Based on Loop Subdivision Surface Boundary Element Method for Three-Dimensional Broadband Structural Acoustic Uncertainty Analysis

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Computer Modeling in engineering & Sciences 2024年第8期140卷 2053-2077页

作者： Ruijin Huo Qingxiang Pei Xiaohui Yuan Yanming Xu College of Architecture and Civil Engineering Xinyang Normal UniversityXinyang464000China Henan Unsaturated Soil and Special Soil Engineering Technology Research Center Xinyang Normal UniversityXinyang464000China Henan International Joint Laboratory of Structural Mechanics and Computational Simulation College of Architecture and Civil EngineeringHuanghuai UniversityZhumadian463000China

In this paper,a generalized nth-order perturbation method based on the isogeometric boundary element method is proposed for the uncertainty analysis of broadband structural acoustic scattering *** Burton-Miller method is employed to solve the problem of non-unique solutions that may be encountered in the external acoustic field,and the nth-order discretization formulation of the boundary integral equation is *** addition,the computation of loop subdivision surfaces and the subdivision rules are *** order to confirm the effectiveness of the algorithm,the computed results are contrasted and analyzed with the results under Monte Carlo simulations(MCs)through several numerical examples.

关键词： Perturbation method loop subdivision surface isogeometric boundary element method uncertainty analysis

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Seismic performance evaluation of steel and GFRP reinforced concrete shear walls at high temperature

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Journal of engineering and Applied Science 2023年第1期70卷 4页

作者： Belay, Asfaw Wondimu, Temesgen Department of Civil Engineering College of Architecture and Civil Engineering Addis Ababa Science and Technology University Addis Ababa16417 Ethiopia

Fire-induced structural damage to the seismic performance of reinforced concrete shear walls is critical in the event of a fire-earthquake scenario. However, only few researchers have studied the seismic performance of reinforced concrete shear walls at high temperatures. This study focuses on the seismic performance of fiber reinforced concrete shear walls at high temperatures by using finite element (FE) software, ABAQUS. The experimental test available in a literature on seismic behavior of shear walls exposed to fire and thermal properties of glass fiber reinforced polymer (GFRP) bars were used to validate the FE model and showed good agreement and thus used in the simulation. The FE results showed that exposure of RC shear wall to fire reduced the strength of the wall. The strength of walls at the maximum applied drift of 3.2% with concrete cover thicknesses of 20 mm, 25 mm, and 30 mm was dropped by about 70%, 76%, and 85% of the reference shear wall, respectively. Similarly, the strength of RC walls was reduced by about 80%, 75%, and 68% of the reference shear wall for the duration of fire exposure of 30 min, 60 min, and 120 min, respectively. Additionally, the strength of walls due to one side, two sides, or all sides’ exposure to fire was decreased by about 68%, 56%, and 50% of the reference shear wall, respectively. It can generally be concluded that the fire exposure sides has largely affected the strength of the shear wall compared to the other parameters and GFRP bars were more sensitive to temperature than steel bars. © 2023, The Author(s).

关键词： Shear walls

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Spatially distributed damage in sandstone under stress-freeze-thaw coupling conditions

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Journal of Rock Mechanics and Geotechnical engineering 2022年第6期14卷 1910-1922页

作者： Lifeng Fan Yiding Fan Yan Xi Jingwei Gao College of Architecture and Civil Engineering Beijing University of TechnologyBeijing100124China

In the present study,we tried to understand the spatially distributed damage in sandstone samples under the coupled stress-freeze-thaw(SFT)***,uniaxial compressive stresses(i.e.0 MPa,10 MPa,20 MPa,and 25 MPa)were applied to the samples,and then freeze-thaw(FT)cycles(0,8,16,and 24)were performed on the uniaxially stressed samples to realize the SFT ***,real-time CT scanning was conducted to observe the induced *** total porosity was introduced to quantitatively evaluate the damage *** local porosity variation,with the distance from the center of the sandstone sample,was analyzed to understand the spatial distribution of ***,the coupling effects of SFT on the damage gradient were *** results indicate that the porosity rises with FT cycles,and the applied stresses can accelerate the increase in *** damage increases exponentially with the distance from the center of the *** damage presents a spatial gradient distribution,not the commonly used uniform distribution in various *** damage gradient increases with FT cycles,and the increasing rate in damage gradient decreases at uniaxial stress of 0 MPa and 10 MPa first,but the increasing rate in damage gradient increases with FT cycles then at stress increasing to 20 MPa.

关键词： Rock damage Freeze-thaw(FT)cycles Uniaxial stress oupling effects

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