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14th International Conference on Frontier Computing, FC 2024

作者： Chen, Zhanfeng Wang, Shuang Wang, Xiaowei Liao, Xizhou School of Architecture and Civil Engineering Chongqing Metropolitan College of Science and Technology Chongqing China Department of Technical Quality China Construction Eighth Engineering Division Corp. LTD Shanghai China

ISBN: (纸本)9789819627974

In the ecological environment, it is mainly reflected in the service and comprehensive evaluation of the ecosystem. The entire system of the INVEST algorithm model can simulate and predict the quantitative and qualitative ecosystem service value under various land use conditions, which can play a role in the decision-making of environmental management. The INVEST algorithm is mainly used to evaluate the service function and economic value of the ecosystem. For example, eco-tourism, soil and water conservation and protection of pupils, etc., to ensure the overall role and impact of human activities on the ecosystem. This study is based on the InVEST algorithm model in the construction and protection of mountain ecological environment, and provides a reference for the development and decision-making of related industries. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Forest ecology

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Preface to the special issue on driving safety and assurance technology for running vehicles on bridges

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Journal of Central South University 2022年第8期29卷 2431-2433页

作者： ZOU Yun-feng GUO Wei Department of Civil Engineering Central South UniversityChangsha 410075China National Engineering Research Center of High-speed Railway Construction Technology Changsha 410075China

With the bridge construction achieving a huge leap, the dynamic interaction between moving vehicles and bridges is an important factor affecting the structural performance of the bridge and the comfort and safety of t... 详细信息

关键词： bridges driving safety

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Multiscale simulation of the urban wind environment under typhoon weather conditions

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Building Simulation 2023年第9期16卷 1713-1734页

作者： Zihan Zhao Yiqing Xiao Chao Li P.W.Chan Gang Hu Qingfeng Zhou School of Construction Engineering Shenzhen PolytechnicShenzhenChina School of Civil and Environmental Engineering Harbin Institute of Technology ShenzhenShenzhenChina Hong Kong Observatory KowloonHong KongChina Shenzhen Urban Planning&Land Resources Research Center ShenzhenGuangdong 518055China

Accurate simulations of planetary boundary layer(PBL)winds in urban areas require combining meteorological knowledge and fine-grained geometrical *** fluid dynamics(CFD)is widely used to assess pedestrian wind comfort and wind disasters in planning resilient ***,the CFD-predicted PBL is highly affected by the inflow *** profiles under extreme weather conditions,such as tropical cyclones,can hardly be determined,and associated uniform logarithmic or power law expressions have not been *** this study,urban wind flow over mountainous terrain was simulated using a one-way nested simulation approach between mesoscale and microscale *** inflow wind speed,turbulence scalars,and potential temperature in the CFD code are sustained by the numerical weather prediction(NWP)*** considering typhoon weather conditions were examined to improve the numerical accuracy in determining mesoscale typhoon structures and pedestrian-level wind *** numerical errors were quantified in mesoscale and microscale formulations.A new tendency assimilation was proposed by incorporating local-scale observations into the CFD *** approach entailed empirical mode decomposition to quantify the mean wind speed differences between the observations and NWP results,which were then extrapolated to NWP-CFD nested interfaces via multiplication by the spatial correlation *** numerical performance was validated against both on-site observations for meteorological purposes and wind profiles retrieved from the experimental LiDAR of the landfalling typhoon *** simulated wind field exhibited an increased accuracy in the local urban *** specifically,the index of agreement in wind speeds was improved from 0.28 to 0.72,and the mean absolute errors were reduced from 5.46 m/s to 1.89 m/s.

关键词： NWP-CFD urban wind flow data assimilation typhoon disaster resilient cities

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Deep Reinforcement Learning for automated scheduling of mining earthwork equipment with spatio-temporal safety constraints

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Frontiers of engineering Management 2025年第1期12卷 39-58页

作者： Yanan LU Ke YOU Yuxiang WANG Ying LIU Cheng ZHOU Yutian JIANG Zhangang WU National Center of Technology Innovation for Digital Construction Huazhong University of Science and TechnologyWuhan 430074China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China Institute of Artificial Intelligence Huazhong University of Science and TechnologyWuhan 430074China Shantui Construction Machinery Co. LtdJining 272000China

Large-scale machinery operated in a coordinat-ed manner in earthworks for mining constitutes high safety *** scheduling of such machinery,factoring in safety constraints,could save time and significantly improve the overall *** paper develops a model of automated equipment scheduling in mining earthworks and presents a scheduling algorithm based on deep rein-forcement learning with spatio-temporal safety *** algorithm not only performed well on safety parame-ters,but also outperformed randomized instances of various sizes set against real mining ***,the study reveals that responsiveness to spatio-temporal safety constraints noticeably increases as the scheduling size *** method provides important noticeable improvements to safe automated scheduling in mining.

关键词： deep reinforcement learning mining earthwork automated scheduling spatio-temporal safety constraints

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ANALYSIS OF THE OPERATION STATES OF INTERNAL COMBUSTION ENGINE IN THE REAL DRIVING EMISSIONS TEST

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Archives of Transport 2022年第1期61卷 71-88页

作者： Andrych-Zalewska, Monika Chlopek, Zdzislaw Merkisz, Jerzy Pielecha, Jacek Wroclaw University of Science and Technology Faculty of Mechanical Engineering Wroclaw Poland Warsaw University of Technology Faculty of Automotive and Construction Machinery Engineering Warsaw Poland Poznan University of Technology Faculty of Civil and Transport Engineering Poznan Poland

Internal combustion engines represent the largest share of motor vehicle propulsion types. Despite the introduction of alternative drives (hybrid and electric), combustion engines will continue to be the main factor in the development of transport. Therefore, work related to their technological development and reduction of their harmful effects on human health and the environment is required. The development of internal combustion engines can be seen in two directions: Technological changes resulting in increased efficiency of such engines and the second direction connected with limitation of exhaust gas emission. The present work is included in the second direction of research interests and concerns the analysis of various operating conditions of internal combustion engines. The operating states, both static and dynamic, determine the operational properties of internal combustion engines, such as fuel and energy consumption as well as pollutant emis-sions. So far, such operating conditions have only been mapped on a chassis dynamometer in various homologation tests. The course of the type approval test was known and the conditions of measurement were also known, which made it impos-sible to introduce a random factor into such tests. Currently, these properties are determined in tests performed in real vehicle operating conditions - RDE (Real Driving Emissions). Such tests are representing real operating conditions of motor vehicles. Limitations for performing tests in real traffic conditions are, apart from formal requirements concerning the duration and distance of individual parts, the dynamic conditions of vehicles determined by the speed and acceleration of the vehicle. The study analyzed the properties of vehicle speed processes and engine operating states in the RDE test, taking into account its individual phases - driving in urban, rural and motorway conditions. Engine operation states are the processes of the engine rotational speed and its relative torque.

关键词： Internal combustion engines

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Operation Risk Analysis of Industrial Heritage Park Reconstruction Project based on ISM-FBN 11

Operation Risk Analysis of Industrial Heritage Park Reconstr...

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11th International Symposium on Project Management, ISPM 2023

作者： Duan, Zhen Hao, Shao-Jin Lian, Le-Kun China Construction Seventh Bureau International Engineering Construction Co. Ltd Guangzhou510540 China School of Civil Engineering and Architecture Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781713877134

In order to reduce the risk of the project operator's participation in the operation of urban renewal projects and to improve the overall effectiveness of urban renewal project operation, this paper proposes a risk assessment and inference method for urban renewal project operations combining the interpreted structural model (ISM) and fuzzy Bayesian network (FBN). Firstly, based on the WSR theory, the coupling relationship of risk factors is analyzed by the explanatory structure model, and the output of ISM model can be transformed into the network structure of Bayesian network;then, the expert evaluation results are processed by the fuzzy set theory to obtain the Bayesian network parameters;secondly, the forward risk assessment, sensitivity analysis and post hoc reverse diagnosis reasoning are conducted based on the constructed Bayesian network model;finally, an industrial park Finally, an industrial park expansion project is taken as an example for empirical analysis to verify the validity of the model. © (2023) by Aussino Academic Publishing House All rights reserved.

关键词： Bayesian networks

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A modified back analysis method for deep excavation with multi-objective optimization procedure

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Journal of Rock Mechanics and Geotechnical engineering 2024年第4期16卷 1373-1387页

作者： Chenyang Zhao Le Chen Pengpeng Ni Wenjun Xia Bin Wang State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China Guangdong Research Center for Underground Space Exploitation Technology School of Civil EngineeringSun Yat-sen UniversityGuangzhou510275China Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai519000China Jiangsu Provincial Transportation Engineering Construction Bureau Nanjing210004China

Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction *** paper proposes a modified back analysis method with multi-objective optimization procedure,which enables a real-time prediction of horizontal displacement of retaining pile during *** opposed to the traditional stage-by-stage back analysis,time series monitoring data till the current excavation stage are utilized to form a multi-objective ***,the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter *** optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction *** achieve efficient parameter optimization and real-time prediction of system behavior,the back propagation neural network (BPNN) is established to substitute the finite element model,which is further implemented together with MOPSO for automatic *** proposed approach is applied in the Taihu tunnel excavation project,where the effectiveness of the method is demonstrated via the comparisons with the site monitoring *** method is reliable with a prediction accuracy of more than 90%.Moreover,different optimization algorithms,including non-dominated sorting genetic algorithm (NSGA-II),Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO,are compared,and their influences on the prediction accuracy at different excavation stages are *** results show that MOPSO has the best performance for high dimensional optimization task.

关键词： Multi-objective optimization Back analysis Surrogate model Multi-objective particle swarm optimization(MOPSO) Deep excavation

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An Agent-Based Cellular Automaton Simulation Model to Study Worker Safety Behavior on construction Sites: The Impacts of Different Social Influence Rules

An Agent-Based Cellular Automaton Simulation Model to Study ...

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ASCE International Conference on Computing in civil engineering 2023: Resilience, Safety, and Sustainability, i3CE 2023

作者： Assaad, Rayan H. Abdul Nabi, Mohamad Assaf, Ghiwa El-Adaway, Islam H. Smart Construction and Intelligent Infrastructure Systems Lab Dept. of Civil and Environmental Engineering New Jersey Institute of Technology NewarkNJ United States Dept. of Civil Architectural and Environmental Engineering Missouri Univ. of Science and Technology RollaMO United States John A. Reif Jr. Dept. of Civil and Environmental Engineering New Jersey Institute of Technology NewarkNJ United States Missouri Consortium of Construction Innovation Dept. of Civil Architectural and Environmental Engineering Dept. of Engineering Management and Systems Engineering Missouri Univ. of Science and Technology RollaMO United States

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

The unsafe behavior of the construction workforce is one of the leading causes of accidents in the construction industry. It has been shown that construction laborers perceive the safety behavior of their co-workers and adjust their personal safety attitudes accordingly. Thus, there has been an increasing attention to studying the impacts of the social influence and norms on the safety behavior of construction workers. While existing studies examined the factors that influence the safety behavior of the construction workforce, there is little-to-no research that specifically focused on modeling the role of social influence on the safety behavior of the workers. This paper addresses this knowledge gap by modeling construction sites as a social interaction environment, where the construction workers often adopt the prevailing behavior of their neighbors. More specifically, this paper used agent-based modeling to simulate the safety behavior of the construction workforce based on a two-dimensional, two-state cellular automaton. Four different social influence rules that could impact the safety behavior of construction workers were considered and compared in the developed simulation model. The results showed that modeling the process of conforming to the safety behavior of the neighboring workers could lead to the formation of clusters of construction laborers having identical safety behavior. The paper also identified the most representative social rule that influences the safety behavior of construction workers. This paper adds to the body of knowledge by enabling contractors better understand the safety behavior of their workers and ultimately improve the safety performance in projects. © ASCE *** rights reserved.

关键词： Cellular automata

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Method for evaluation of geological strength index of carbonate cliff rocks:Coupled hyperspectral-digital borehole image technique

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Journal of Rock Mechanics and Geotechnical engineering 2024年第10期16卷 4204-4215页

作者： Haiqing Yang Guizhong Huang Chiwei Chen Yong Yang Qi Wang Xionghui Dai Key Laboratory of New Technology for Construction of Cities in Mountain Area School of Civil EngineeringChongqing UniversityChongqing400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing400045China Technology Innovation Center of Geohazards Automatic Monitoring Ministry of Natural Resources(Chongqing Institute of Geology and Mineral Resources)Chongqing Engineering Research Center of Automatic Monitoring for Geological HazardsChongqing401120China

The deterioration of unstable rock mass raised interest in evaluating rock mass ***,the traditional evaluation method for the geological strength index(GSI)primarily emphasizes the rock structure and characteristics of *** ignores the influence of mineral composition and shows a deficiency in assessing the integrity *** this context,hyperspectral imaging and digital panoramic borehole camera technologies are applied to analyze the mineral content and integrity of rock *** on the carbonate mineral content and fissure area ratio,the strength reduction factor and integrity coefficient are calculated to improve the GSI evaluation *** to the results of mineral classification and fissure identification,the strength reduction factor and integrity coefficient increase with the depth of rock *** rock mass GSI calculated by the improved method is mainly concentrated between 40 and 60,which is close to the calculation results of the traditional *** GSI error rates obtained by the two methods are mostly less than 10%,indicating the rationality of the hyperspectral-digital borehole image coupled evaluation ***,the sensitivity of the fissure area ratio(Sr)to GSI is greater than that of the strength reduction factor(a),which means the proposed GSI is suitable for rocks with significant fissure *** improved method reduces the influence of subjective factors and provides a reliable index for the deterioration evaluation of rock mass.

关键词： Hyperspectral image Digital panoramic borehole image Geological strength index Carbonate rock mass Quantitative evaluation

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Assessing Random Forest and SARIMA Models for Wet Period Rainfall Prediction in Northern Territory, Australia

Assessing Random Forest and SARIMA Models for Wet Period Rai...

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2024 IEEE Conference on engineering Informatics, ICEI 2024

作者： Farooq, Rashid Imteaz, Monzur Alam Hlavcoa, Kamila Kohnova, Silvia Swinburne University of Technology Department of Civil and Construction Engineeirng MelbourneVIC3122 Australia Slovak University of Technology Faculty of Civil Engineering Department of Land and Water Resources Management Bratislava Slovakia

ISBN: (纸本)9798331505776

The present study investigates the simultaneous effect of climate indices on wet rainfall in the Northern Territory (NT). To achieve this, a comprehensive set of input variables was employed, including lagged indices of the Indian Ocean Dipole (IOD), El Niño-Southern Oscillation (ENSO), and MaddenJulian Oscillation (MJO). These climatic predictors were utilized to calibrate and validate the Random Forest (RF) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA) models, ensuring robust model performance and accurate rainfall forecasting. To evaluate the model's performance, three statistical measures were used: mean absolute error (MAE), correlation coefficient (r), and root mean square error (RMSE). Among the large-scale climate factors considered, MJO, SOI, and NINO 3.4 were identified as having a significant impact on the Northern Territory's wet period rainfall forecast. For NT forecasts at one selected station, the RF model demonstrated the most favorable outcomes. Similarly, the SARIMA model displayed a root-mean-square error (RMSE) that ranged from 8.64 mm to 60.65 mm across the selected site. In contrast, the RF model demonstrated better performance, exhibiting an RMSE range of 5.24 mm to 49.33 mm. © 2024 IEEE.

关键词： Mean square error

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