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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Baker, Robert M. Polmateer, Thomas L. Marcellin, Megan C. Chen, T. Donna Riggs, Robert J. Iqbal, Tariq Hendrickson, Daniel C. Slutzky, David L. Lambert, James H. University of Virginia United States Coast Guard Dept. of Systems and Information Engineering CharlottesvilleVA United States University of Virginia CharlottesvilleVA United States University of Virginia Dept. of Systems and Information Engineering CharlottesvilleVA United States University of Virginia Dept. of Civil and Environmental Engineering CharlottesvilleVA United States Asset Management & Special Projects Port of Virginia NorfolkVA United States Fermata Llc and University of Virginia United States

ISBN: (纸本)9781665430654

There is urgency for electrifying fleet vehicles as a means to reach net-zero emissions and promote sustainability, including at maritime container ports. Ports are exploring the incorporation of electric terminal tractors and supporting infras-tructure in an effort to minimize the environmental effects of their operations while simultaneously improving service performance. The challenges include planning of investments in infrastructure that will meet charging requirements of these terminal tractors while maintaining operational efficiencies. This paper develops an optimization and associated risk register for strategic capacity expansion of electric vehicle fleets at maritime container ports. The approach includes multi-criteria decision analysis (MCDA) and a characterization of enterprise risk as a disruption of system order. A demonstration of schedule optimization uses linear program-ming models for thirty-two combinations of plug-in, wireless, and wireless dynamic charging infrastructure configurations to determine optimal charger locations. In a robust ensemble model, the optimization accompanies a comprehensive risk analysis that disrupts importance orders across seven scenarios: (1) Environ-mental Change, (2) Policy Revision, (3) Technology Innovation, (4) Cyber Attack, (5) Market Shift, (6) Electrical Grid Stress, and (7) Workforce Interruption. The results support the decisions and enterprise risk management for a 1.5 billion strategic plan for port infrastructure. The plan involves selecting charging station locations, determining charging schedules, and selecting charger models while considering multiple performance criteria such as safety, operational efficiency, cost-effectiveness, and reliability. The approach is generally applicable for a variety of complex systems to mitigate schedule and cost risks while improving sustainability. The audience of the paper includes owners and operators of transportation and energy infrastructures, asset managers, l

关键词： electric vehicles linear programming multi-criteria analysis order disruption scenario- based preferences scheduling systems analysis

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Predicting calcium carbonate yield from wet carbonation of recycled cement paste using interpretable ensemble machine learning

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Journal of Cleaner Production 2025年 514卷

作者： Li, Yining del Rio Chanona, Ehecatl Antonio Wong, Hong S. Myers, Rupert J. Department of Civil and Environmental Engineering Imperial College London LondonSW7 2AZ United Kingdom Sargent Centre for Process Systems Engineering Department of Chemical Engineering Imperial College London LondonSW7 2AZ United Kingdom

Wet carbonation is a promising method for enhancing the performance of recycled cement paste as a low carbon supplementary cementitious material, however, its optimisation for yield is hindered by an incomplete understanding of its mechanisms and uncertainty about the relative importance of various influencing factors. This study applies advanced machine learning techniques to optimise the wet carbonation of recycled cement paste to maximise calcium carbonate yield, utilising a dataset of 227 experimental records covering diverse process conditions. Six machine learning models—support vector regression, decision tree, random forest, gradient boosting regressor, extreme gradient boosting, and stacking—were trained and evaluated using R2, MAE, and RMSE as performance metrics. Model evaluation was performed using 10-fold cross-validation to enhance robustness and ensure generalisation across different data subsets. The stacking ensemble model achieved the highest predictive accuracy, with R2 values of 0.997 (training) and 0.948 (testing), improving prediction accuracy by 19.85 % compared to the least accurate model (decision tree testing). Additionally, the stacking model achieved MAE values of 0.0101 (training) and 0.0393 (testing), and RMSE values of 0.0125 (training) and 0.0536 (testing), demonstrating its superior predictive capability. This model effectively addressed the challenge of limited data, a common issue in applying machine learning in materials science. Shapley additive explanations identified the fineness of cement paste particles and carbonation time as critical factors affecting the calcium carbonate yield variability, contributing 0.14 and 0.11, respectively. Therefore, these results show that finer particle size, extended carbonation time, and the addition of extra OH- ions in the reactor can be applied to develop more efficient wet carbonation processes, enhancing the production of CaCO3 and CO2 uptake. This research highlights the potential of ens

关键词： Cements

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MULTI-OBJECTIVE BAYESIAN OPTIMIZATION FOR LIKELIHOOD-FREE INFERENCE IN SEQUENTIAL SAMPLING MODELS OF DECISION MAKING

arXiv

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arXiv 2024年

作者： Chen, David Li, Xinwei Kim, Eui-Jin Bansal, Prateek Nott, David Department of Statistics and Data Science National University of Singapore Singapore Department of Civil and Environmental Engineering National University of Singapore Singapore Department of Transportation Systems Engineering Ajou University Korea Republic of

Scientifically motivated statistical models can sometimes be defined by a generative process for simulating synthetic data. Models specified this way can have likelihoods which are intractable, and this is the case for many sequential sampling models (SSMs) widely used in psychology and consumer behavior modelling. Researchers have developed likelihood-free inference (LFI) methods to make Bayesian inferences on parameters in models with intractable likelihood. Extending a popular approach to simulation efficient LFI for single-source data, we propose Multi-objective Bayesian Optimization for Likelihood-Free Inference (MOBOLFI) to estimate the parameters of SSMs calibrated using multi-source data, such as those based on response times and choice outcomes. MOBOLFI models a multi-dimensional discrepancy between observed and simulated data, using a discrepancy for each data source. Multi-objective Bayesian Optimization is then used to ensure simulation efficient approximation of the SSM likelihood. The use of a multivariate discrepancy allows for approximations to individual data source likelihoods in addition to the joint likelihood, enabling both the detection of conflicting information and a deeper understanding of the importance of different data sources in estimating individual SSM parameters. We illustrate the advantages of our approach in comparison with the use of a single discrepancy in a simple synthetic data example and an SSM example with real-world data assessing preferences of ride-hailing drivers in Singapore to rent electric vehicles. Although we focus on applications to SSMs, our approach applies to the likelihood-free calibration of other models using multi-source data. © 2024, CC BY.

关键词： Markov processes

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Analytical Optimized Traffic Flow Recovery for Large-scale Urban Transportation Network

arXiv

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arXiv 2024年

作者： Fu, Sicheng Shi, Haotian Liang, Shixiao Wang, Xin Ran, Bin Department of Civil and Environmental Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Industrial and Systems Engineering University of Wisconsin-Madison MadisonWI53706 United States

The implementation of intelligent transportation systems (ITS) has enhanced data collection in urban transportation through advanced traffic sensing devices. However, the high costs associated with installation and maintenance result in sparse traffic data coverage. To obtain complete, accurate, and high-resolution network-wide traffic flow data, this study introduces the Analytical Optimized Recovery (AOR) approach that leverages abundant GPS speed data alongside sparse flow data to estimate traffic flow in large-scale urban networks. The method formulates a constrained optimization framework that utilizes a quadratic objective function with l2 norm regularization terms to address the traffic flow recovery problem effectively and incorporates a Lagrangian relaxation technique to maintain non-negativity constraints. The effectiveness of this approach was validated in a large urban network in Shenzhen's Futian District using the Simulation of Urban MObility (SUMO) platform. Analytical results indicate that the method achieves low estimation errors, affirming its suitability for comprehensive traffic analysis in urban settings with limited sensor deployment. Copyright © 2024, The Authors. All rights reserved.

关键词： Constrained optimization

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Impact Analysis of environmental Policies on Shipping Fleet Planning Under Demand Uncertainty

SSRN

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SSRN 2023年

作者： Yonzheng, Jerry Chua Soudagar, Irfan Ng, Szu Hui Meng, Qiang Department of Industrial Systems Engineering and Management National University of Singapore 117576 Singapore Department of Civil and Environmental Engineering National University of Singapore 117576 Singapore

Considerations to decarbonize maritime shipping by implementing the Emissions Trading System (ETS) are underway at the International Maritime Organization (IMO). This study seeks to investigate the impact of various ETS implementations on short-term fleet deployment decisions of liner shipping companies. To this end, a fleet planning model accounting for carbon emissions is proposed to evaluate the decision-making nuances of a liner shipping company. Numerical experiments are conducted to analyze global and regional ETS implementations with varying policy design parameters, for their efficacy in mitigating emissions and potential impact on shipping stakeholders. Policy design implications are provided based on the insights generated. For industries such as liner shipping which are cross-regional by nature, we discover that a regional ETS implementation is insufficient in mitigating global carbon emissions due to carbon leakage. We find that strict carbon purchase caps integrated with robust carbon price-setting mechanisms are critical to designing an effective ETS. © 2023, The Authors. All rights reserved.

关键词： Carbon

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environmental impact of microplastic emissions from wastewater treatment plant through life cycle assessment

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Science of the Total Environment 2025年 962卷 178378页

作者： Alibekov, Alisher Meirambayeva, Mira Yengsebek, Shugyla Aldyngurova, Firyuza Lee, Woojin Department of Civil and Environmental Engineering School of Digital Sciences and Engineering Nazarbayev University Astana010000 Kazakhstan Department of Mining Engineering School of Mining and Geosciences Nazarbayev University Astana010000 Kazakhstan Municipal State Enterprise "Astana Su Arnasy" Astana020000 Kazakhstan Laboratory of Environmental Systems National Laboratory Astana Nazarbayev University Astana010000 Kazakhstan

This study aimed to quantify the environmental impact of microplastic (MP) emissions from wastewater treatment plants (WWTPs) using life cycle assessment (LCA). The investigation comprehensively evaluated the contribution of MPs to overall WWTP midpoint and endpoint impacts, with a detailed analysis of the influence of particle size, shape, polymer type, and the environmental costs and benefits of individual wastewater treatment processes on MP removal. The LCA model was developed using SimaPro software, with impact assessments conducted via the USEtox framework and the IMPACT World+ methodology. Results showed that at the midpoint level, MPs accounted for 1.24E+05 CTUe (94 % of the total plant impact), representing the potential harm to aquatic species per cubic meter of discharged wastewater—surpassing the impacts of other contaminants (e.g., heavy metals, nutrients) by at least two orders of magnitude. At the endpoint level, the damage of 8.39E-02 PDF·m2·yr (1.7 % of the total) indicated the potential loss of species diversity, comparable to other pollutant contributions. Polyethylene, polystyrene, and polypropylene were identified as the most impactful polymer types. In terms of environmental costs and benefits, secondary, tertiary, and primary treatments demonstrated decreasing environmental benefits, directly correlated with their respective MP removal efficiencies. These findings underscore the critical role of MP emissions in WWTP life cycle inventories and highlight the urgent need for targeted environmental policies and advanced treatment technologies to address MP contamination in both natural and engineered aquatic systems. © 2025 The Authors

关键词： Life cycle assessment

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Superwetting polyethersulfone membrane functionalized with ZrO_(2) nanoparticles for polycyclic aromatic hydrocarbon removal

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Journal of Materials Science & Technology 2022年第3期98卷 14-25页

作者： Xiujuan Chen Guohe Huang Chunjiang An Renfei Feng Yinghui Wu Charley Huang Department of Environmental Systems Engineering University of ReginaReginaSaskatchewanS4S 0A2Canada China-Canada Center for Energy Environment and Ecology ResearchUofR-BNUBeijing Normal UniversityBeijing 100875China Department of Building Civil and Environmental EngineeringConcordia UniversityMontrealQuebecH3G 1M8Canada Canadian Light Source SaskatoonS7N 2V3Canada Department of Chemical and Materials Engineering University of AlbertaEdmontonAlbertaT6G 1H9Canada

Polycyclic aromatic hydrocarbons(PAHs)are persistent and widespread in the aquatic environment,causing potential hazards for human *** this study,a superwetting and robust PES-PAA-ZrO_(2)nanofiltration membrane was proposed through surface modification for PAH removal with high efficiency.A ZrO_(2)coating was formed on polyethersulfone(PES)membrane surface through chemical bonding,thus the PES-PAA-ZrO_(2)membrane exhibited super-hydrophilicity,under-water oleophobicity,and excellent *** comparison with the original PES membrane,the water contact angle of the modified membrane was significantly decreased from about 50°to less than 10°,and quickly dropped to 0°within *** provided a much lower energy barrier for water permeation due to its super-high water *** wastewater treatment efficiency was increased by about 4 times after modification with more than 90%of PAH rejection *** excellent robustness of PES-PAA-ZrO_(2)membrane was verified under various conditions,which gave the membrane practical potential for long-term operation.

关键词： Superwetting nanofiltration membrane Nano-ZrO_(2)self-assembly Synchrotron-based analyses PAH removal

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Context-aware Nonlinear MPC for Automated Vehicles Embedding Newell's Car-Following Model

Context-aware Nonlinear MPC for Automated Vehicles Embedding...

引用

International Conference on Intelligent Transportation

作者： Angelo Coppola Roberta Di Pace Facundo Storani Stefano de Luca Stefania Santini Department of Civil Architectural and Environmental Engineering University of Naples “Federico II” Naples Italy Depart. of Civil Engineering Sustainable Transportation Systems Engineering and Mobility Laboratory (ISTMoS) University of Salerno Fisciano SA Italy Department of Electrical Engineering and Information Technology University of Napoli Federico II Naples Italy

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Automated Driving systems equipping Connected and Automated Vehicles (CAVs) require a meticulous design to maximize the advantages of connectivity and automation. However, even the most widespread systems are not free from problems; for instance, the effectiveness of current Adaptive Cruise Control implementations in improving safety, traffic stability and energy consumption is questionable. Therefore, there is the need to develop solutions that avoid inadequate driving behaviours. To this end, in this work we design a Nonlinear Model Predictive Control (NMPC) strategy that resemble an ACC, embedding the Newell non-linear car-following model. The Newell model computes a reference speed profile over the prediction horizon, ensure string stability and anticipate speed oscillations. Then, using this speed as reference, the NMPC controller computes an optimal acceleration profile to drive the vehicle as fast as possible while ensuring comfort and safety. The proposed NMPC strategy is evaluated across various simulation scenarios, with several Key Performance Indicators (KPIs) related to safety, driving volatility and consumption. A conventional ACC system is employed for comparison. Through observation and comparison of the KPIs, the effectiveness of the proposed approach is demonstrated.

关键词： Computational modeling Key performance indicator Stochastic processes Computer architecture Predictive models Stability analysis Safety Oscillators Time-varying systems Predictive control

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The effect of ride experience on changing opinions toward autonomous vehicle safety

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Communications in Transportation Research 2021年第1期1卷 7-15页

作者： Xiaowei Shi Zhen Wang Xiaopeng Li Mingyang Pei Department of Civil and Environmental Engineering University of South FloridaTampaFL33620USA School of Information Engineering Chang'an UniversityShaanxiChina Automatic Control Group and Urban Mobility Systems Group Chalmers University of TechnologyGothenburgSE-41296Sweden

Autonomous vehicles(AVs)are a promising emerging technology that is likely to be widely deployed in the near ***'s perception on AV safety is critical to the pace and success of deploying the AV *** studies found that people's perceptions on emerging technologies might change as additional information was *** investigate this phenomenon in the AV technology context,this paper conducted real-world AV experiments and collected factors that may associate with people's initial opinions without any AV riding experience and opinion change after a successful AV ride.A number of ordered probit and binary probit models considering data heterogeneity were employed to estimate the impact of these factors on people's initial opinions and opinion *** study found that people's initial opinions toward AV safety are significantly associated with people's age,personal income,monthly fuel cost,education experience,and previous AV ***,the factors dominating people's opinion change after a successful AV ride include people's age,personal income,monthly fuel cost,daily commute time,driving alone indicator,willingness to pay for AV technology,and previous AV *** results provide important references for future implementations of the AV ***,based on the inconsistent effects for variables across different models,suggestions for future transportation survey designs are provided.

关键词： Autonomous vehicle Technology acceptance Safety Ordered probit model Binary probit model

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Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

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Frontiers of environmental Science & engineering 2022年第12期16卷 43-54页

作者： Xiujuan Chen Yunqiu Liu Gordon Huang Chunjiang An Renfei Feng Yao Yao Wendy Huang Shuqing Weng Department of Civil Engineering University of CalgaryCalgaryAlbertaT2N 1N4Canada Institute for Energy Environment and Sustainable CommunitiesUniversity of ReginaReginaSaskatchewanS4S 0A2Canada Environmental Systems Engineering University of ReginaReginaSaskatchewanS4S 0A2Canada Department of Building Civil and Environmental EngineeringConcordia UniversityMontrealQuebecH3G 1M8Canada Canadian Light Source SaskatoonSKS7N 2V3Canada McElhanney Inc CranbrookBritish ColumbiaV1C 7H9Canada

The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human *** to this challenge,a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this *** developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite *** as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV *** hydrophobicity could be easily recovered through being stored in dark environment for several *** optimize the performance of the PAA-ZnO-HDTMS flax fiber,the effects of ZnO and HDTMS concentrations on its switchable wettability were *** optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle(∼130°)in air and an extremely small oil contact angle(∼0°)underwater *** UV treatment,the water contact angle was decreased to 30°,while the underwater oil contact angle was increased to more than 150°.Based on this UV-induced switchable wettability,the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple ***,the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation,which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.

关键词： Flax fiber Switchable wettability ZnO-HDTMS coating Oil-water separation

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