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Multi-population particle swarm optimization algorithm for automatic design of steel frames

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Frontiers of Structural and Civil Engineering 2024年第1期18卷 89-103页

作者： Wenchen SHAN Jiepeng LIU Yao DING Y.Frank CHEN Junwen ZHOU institute of Smart City and Intelligent transportation Southwest Jiaotong UniversityChengdu 610000China School of Civil Engineering Chongqing UniversityChongqing 400045China Department of Civil Engineering the Pennsylvania State UniversityMiddletownPA 17057USA

Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost ***,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design *** are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative *** proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design *** related parameter influences on optimization results are *** the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65% and can obtain frame with the weight for at least 2.4%lighter.A similar trend can also be observed in cases subjected to Chinese design *** addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO *** purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design *** aims to provide a reference for automatic structural optimization design problems even with dimensional *** proposed method can be easily generalized to the optimization problem of other structural systems.

关键词： steel frame multi-population particle swarm optimization automatic structural optimization design

An extended micromechanical-based plastic damage model for understanding water effects on quasi-brittle rocks

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International Journal of Mining Science and Technology 2024年第3期34卷 289-304页

作者： Qiaojuan Yu Shigui Du Qizhi Zhu Zhanyou Luo Sili Liu Lunyang Zhao institute of Rock Mechanics Ningbo UniversityNingbo 315211China Ningbo Key Laboratory of Energy Geostructure Ningbo UniversityNingbo 315211China College of Civil and transportation Engineering Hohai UniversityNanjing 210098China College of Civil Engineering Jiangsu Open UniversityNanjing 210036China South China Institution of Geotechnical Engineering School of Civil Engineering and TransportationSouth China University of TechnologyGuangzhou 510641China

Water effects on the mechanical properties of rocks have been extensively investigated through experiments and numerical ***,few studies have established a comprehensive link between the microscopic mechanisms of water-related micro-crack and the constitutive behaviors of *** this work,we shall propose an extended micromechanical-based plastic damage model for understanding weakening effect induced by the presence of water between micro-crack’s surfaces on quasi-brittle rocks,based on the Mori-Tanaka homogenization and irreversible thermodynamics *** the physical mechanism,water strengthens micro-crack propagation,which induces damage evolution during the pre-and post-stage,and weakens the elastic effective properties of rock *** proposing a special calibration procedure for the determination of model parameters based on the laboratory compression tests,the proposed micromechanical-based model is verified by comparing the model predictions to the experimental *** model effectively captures the mechanical behaviors of quasibrittle rocks subjected to the weakening effects of water.

关键词： Water Micro-crack Damage Micro-mechanics Constitutive model Cohesive force

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang Yang Nian-Tian Lin Kai Zhang Yan Cui Chao Fu Dong Zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology transportation institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

Research on intelligent search-and-secure technology in accelerator hazardous areas based on machine vision

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Nuclear Science and Techniques 2024年第4期35卷 96-107页

作者： Ying-Lin Ma Yao Wang Hong-Mei Shi Hui-Jie Zhang School of Traffic and transportation Beijing Jiaotong UniversityBeijing 100044China School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China

Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to ***,manual sweep methods are ***,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale *** leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and *** the criticality of personal safety for stranded individuals,search and security processes must be sufficiently *** ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring *** YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the ***,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive *** strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall ***,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,*** there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software *** tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.

关键词： Search and secure Machine vision Camera Human body parts recognition Particle accelerator Hazardous area

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2627-2647页

作者： Tarek Sheltami Gamil Ahmed Ansar Yasar Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia transportation Research institute(IMOB) Hasselt UniversityHasselt3500Belgium

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread ***,deploying IoD for area coverage poses numerous limitations and *** include interference between neighboring drones,the need for directional antennas,and altitude restrictions for *** challenges necessitate the development of efficient *** research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges *** primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring *** deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of *** the other hand,deploying a few drones cannot satisfy the coverage *** accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is *** objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground *** is assumed that each drone is equipped with a directional antenna to optimize coverage in a given *** simulations are conducted to assess the effectiveness of the proposed *** demonstrate that the proposed method achieves maximum coverage with minimum transmission ***,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence *** simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage an

关键词： IoD line of sight optimal deployment IPSO RF model

Deformation and stability of the seawall,considering the strength uncertainty of cement mixing piles

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2024年第6期25卷 483-501页

作者： Yuansheng YU Lingling LI Xiangmiao KONG Chengyuan LI Zhen GUO Key Laboratory of Offshore Geotechnics and Material of Zhejiang Province College of Civil Engineering and ArchitectureZhejiang UniversityHangzhou310058China Hainan institute Zhejiang UniversitySanya572000China Ninghai Highway and transportation Management Center Ningbo315600China Ninghai Traffic Engineering Construction Management institute Ningbo315600China

The cement mixing (CM) pile is a common method of improving soft offshore ground. The strength growth of CM piles under complex conditions is affected by many factors, especially the cement and moisture contents, and shows significant uncertainty. To investigate the stochasticity of the early strength of CM piles and its impact on the displacement and stability of a seawall, a series of laboratory tests and numerical analyses were carried out in this study. Vane shear tests were conducted on the cement-solidified soil to determine the relationships between the undrained shear strength s_(u) of the cement soil curing in the seawater and the cement content a_(c), as well as the in situ soil moisture content w. It can be inferred that the 24 h undrained shear strength follows a normal distribution. A numerical model considering the random CM pile strength was established to investigate the deformation of the seawall. Due to the uncertainty of CM pile strength, the displacement of the seawall demonstrates a certain discreteness. The decrease of the mean undrained shear strength of CM piles causes a corresponding increase in the average displacement of the seawall. When the mean strength of CM piles is lower than a certain threshold, there is a risk of instability. Furthermore, the heterogeneity of the strength within an individual CM pile also has an impact on seawall displacement. Attention should be paid to the uncertainty of CM pile strength to control displacement and stability.

关键词： Construction uncertainty Cement mixing(CM)pile Strength of cement soil Seawall stability Random finite element method(RFEM) Monte Carlo simulation(MCS)

Study of interfacial transition zones between magnesium phosphate cement and Portland cement concrete pavement

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Journal of Traffic and transportation Engineering(English Edition) 2024年第3期11卷 523-537页

作者： Fei Liu Baofeng Pan Changjun Zhou Ge Li Xiaocun Wang Jiaquan Li Faculty of Infrastructure Engineering Dalian University of TechnologyDalian 116024China Tongren City transportation Bureau Tongren 554300China Beijing Civil Aviation Design and Research institute of China Design Group Beijing 101318China

The Portland cement concrete pavement(PCCP)often suffers from different environmental distresses and vehicle load failure,resulting in slab corner fractures,potholes,and other *** repair has become one of the effective ways to open traffic *** this study,a novel type of rapid repair material,basalt fiber reinforced polymer modified magnesium phosphate cement(BFPMPC),is used to rapidly repair ***,the mechanical properties and characteristics of the repair interfaces which are named interfacial transition zones(ITZs)formed by BFPMPC and cement concrete are focused on as a decisive factor for the performance of the rapid *** changing trend of the elastic moduli was studied by nanoindentation experiments in the ITZs with the deconvolution analysis that the elastic moduli of certain kinds of substances can be *** experimental results show that the elastic modulus of ITZ-1 with a width of about20μm can be regarded as 0.098 times of the aggregate,and 0.51 times of the ordinary Portland cement(OPC)*** BFPMPC-OPC mortar ITZ has roughly the same mechanical properties as the ITZ between aggregate and BFPMPC.A multi-scale representative two-dimensional model was established by random aggregate and a two-dimensional extended finite element method(XFEM)to study the mechanical properties of the repair *** simulation results show that the ITZ formed by the interface of BFPMPC and OPC mortar and basalt aggregate is the most vulnerable to failure,which is consistent with the nano-indentation experimental results.

关键词： Portland cement concrete pavement Interfacial transition zone Magnesium phosphate cement Repair interface Nanoindentation Mechanical properties and characteristics

Study on Spray and Combustion Characteristics of F-T Diesel Blending Oxygenated Fuel Based on Constant Volume Combustion Chamber

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Journal of Traffic and transportation Engineering(English Edition) 2024年

作者： Limin Geng Yang Zhao Fujia Liu Shiyu Shan Nan Gao Zhao Liu Hao Chen Shaanxi Key Laboratory of New transportation Energy and Automotive Energy Saving， Chang'an University Research institute of Highway Ministry of Transport

In this work， 20% of PODE and n-butanol are blended with F-T diesel by volume， respectively，referred to as FFP20 and FBU20. Based on the constant volume combustion chamber (CVCC)， the spray characteristics and combustion characteristics of diesel， F-T diesel， FP20 and FBU20 under high ambient temperature and pressure are studied by using high-speed photography combined with MATLAB image processing technology. Results show that the steady-state liquid spray tip penetration and spray projection area of FP20 and FBU20 are smaller than those of F-T diesel due to their good evaporation. Combustion characteristics studies show that compared to D100， the ignition delay and flame lift-off length of FT100 decrease by 22.9% and 43.6%， respectively. Compared to FT100， the flame lift-off length of FP20 and FBU20 increases by 36.8% and 44.1%， respectively. Due to the addition of high cetane number and high oxygen content PODE， the ignition delay of FP20 is shortened by 3.7%， and the ignition delay of FBU20 is prolonged by 40.1% due to the effect of high latent heat of vaporization and low cetane number of n-butanol. Compared to D100， the peak flame area of FT100 increases by 8.5%， while the peak flame luminosity decreases by 18.2%. Because PODE and n-butanol can improve evaporation and increase the oxygen content of fuel and then reduce the formation of soot， compared to FT100， the peak of flame area and flame luminosity of FP20 and FBU20 are decreased. The results of two-color method show that after adding PODE and n-butanol into F-T diesel fuel， the generation of soot and combustion temperature of the mixed fuel are reduced. Moreover， FP20 has higher oxygen content and better atomization characteristics， so the effect of reducing soot is better than that of FBU20.

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Identification and hazard analysis of landslides triggered by earthquakes and rainfall

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Earthquake Research Advances 2024年第3期4卷 42-54页

作者： Lei Li Yu Zhang Yunlong Hou Bingbing Han Ning An Hui Zhang Ying Ma School of Traffic and transportation Lanzhou Jiaotong UniversityLanzhou730070China Key Laboratory of Railway Industry on Plateau Railway transportation Intelligent Management and Control Lanzhou Jiaotong UniversityLanzhou730070China Gansu institute of Engineering Geology Lanzhou730030China School of Civil Engineering Lanzhou Jiaotong UniversityLanzhou730070China

This study aims to utilize the Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-In SAR)technique and Google Earth optical remote sensing images to analyze the area within 20 km around the epicenter of a M 3.9, earthquake that occurred in Tanchang County, Gansu Province, on December 28, 2020. The objective is to identify potential earthquake-induced landslides, assess their scale, and determine their impact range. The study results reveal the successful identification of two potential landslides in the 20 km radius around the epicenter. Through time-series deformation analysis, it was observed that these potential landslides were significantly influenced by both the earthquake and rainfall. Further estimation of these potential landslides indicates maximum depths of 7.4 m and 14.1 m for the failure surfaces, with volumes of 9.02 × 10~4m~3and 25.5 ×10~4m~3, respectively. Finally, based on the simulation analysis of Massflow software, the maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Shangyaai is 12 m, the area of the final accumulation area is 1.75 × 10~4m~2, and the farthest movement distance is 1124 m. The maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Wangshancun is 8 m, the area of the final accumulation area is 7.89 × 10~4m~2, and the farthest movement distance is 742 m.

关键词： SBAS-InSAR technology Earthquake Deformation monitoring Landslide Massflow Hazard analysis