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Scalable Solutions for Security-Constrained Optimal Power Flow with Multiple Time Steps

IEEE Transactions on Industry Applications 2025年第3期61卷 4812-4821页

作者： Sharadga, Hussein Mohammadi, Javad Crozier, Constance Baker, Kyri Texas A and M International University Systems Engineering LaredoTX United States The University of Texas Department of Civil Architectural and Environmental Engineering AustinTX United States The University of Texas at Austin Civil Architectural and Environmental Engineering AustinTX United States Georgia Institute of Technology Industrial and Systems Engineering Georgia United States University of Colorado Civil Environmental and Architectural Engineering BoulderCO United States

This work introduces an innovative approach to scaling security-constrained optimal power flow problems to large power grids with multi-timestep, addressing the significant challenges associated with managing millions of continuous and integer optimization variables as well as nonlinear and nonconvex constraints. Through a strategic combination of problem reformulation, linearization methods, constraint-relaxation techniques, and sequential optimization, the complexities inherent to large power grid optimization are effectively navigated. The proposed methodology enables the resolution of complex power grid models with strict time constraints while attaining high-quality solutions. Demonstrating remarkable robustness, the novel approach consistently surpasses established benchmark methods. © 1972-2012 IEEE.

关键词： Load flow optimization

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Topology, Size, and Shape Optimization in civil engineering Structures: A Review

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Computer Modeling in engineering & Sciences 2025年第2期142卷 933-971页

作者： Ahmed Manguri Hogr Hassan Najmadeen Saeed Robert Jankowski Faculty of Civil and Environmental Engineering Gdansk University of TechnologyGdansk80-223Poland Department of Computer Science ModelingElectronics and Systems EngineeringUniversity of CalabriaCosenza87036Italy Civil Engineering Department University of RaparinRania46012Iraq Civil Engineering Department Tishk International UniversityErbil44001Iraq

The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering *** optimization approaches seek to determine the optimal design,by considering material performance,cost,and structural *** design approaches aim to reduce the built environment’s energy use and carbon *** comprehensive review examines optimization techniques,including size,shape,topology,and multi-objective approaches,by integrating these *** trends and advancements that contribute to developing more efficient,cost-effective,and reliable structural designs were *** review also discusses emerging technologies,such as machine learning applications with different optimization *** of truss,frame,tensegrity,reinforced concrete,origami,pantographic,and adaptive structures are covered and *** techniques are explained,including metaheuristics,genetic algorithm,particle swarm,ant-colony,harmony search algorithm,and their applications with mentioned structure *** and non-linear structures,including geometric and material nonlinearity,are *** role of optimization in active structures,structural design,seismic design,form-finding,and structural control is taken into account,and the most recent techniques and advancements are mentioned.

关键词： Structural optimization topology optimization size optimization shape optimization multi-objective optimization

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Cooperative CAV mandatory lane-change control enabled by V2I

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Communications in Transportation Research 2024年第1期4卷 148-162页

作者： Ran Yi Yifan Yao Fan Pu Yang Zhou Xin Wang Department of Civil and Environmental Engineering University of Wisconsin-MadisonMadisonWI53706USA Zachry Department of Civil and Environmental EngineeringTexas A&M UniversityCollege StationTX77840USA Department of Industrial and Systems EngineeringUniversity of Wisconsin-MadisonMadisonWI53706USA

This paper presents a spatially formulated cooperative dynamic mandatory connected automated vehicle(CAV)lane-changing and car-following approach on curved highways with the assistance of vehicle-to-infrastructure(V2I)and vehicle-to-vehicle(V2V)*** work proposes mandatory lane-changing control in a spatial domain to accomplish car-following and lane-changing efficiency in a systematic *** control technique initially creates a virtual CAV car-following lane by assigning CAVs sequential numbers based on their spatial *** this basis,a multi-objective model predictive control(MPC)strategy in the spatial domain is designed to optimize the trajectories in a rolling horizon fashion in order to maintain the inter-vehicle spacing and speed difference while simultaneously satisfying collision avoidances,traffic regulations,and vehicle kinematics ***-scenario numerical simulations are conducted to validate the control efficacy of our technique.

关键词： CAV control V2I-Enabled control Lane-change control Spatial domain formulation

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An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2873-2897页

作者： Yingui Qiu Shuai Huang Danial Jahed Armaghani Biswajeet Pradhan Annan Zhou Jian Zhou School of Resources and Safety Engineering Central South UniversityChangsha410083China School of Civil and Environmental Engineering University of Technology SydneyNew South WalesAustralia Centre for Advanced Modelling and Geospatial Information Systems School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNew SouthWalesAustralia Civil and Infrastructure Engineering Discipline School of EngineeringRoyal Melbourne Institute of Technology(RMIT)MelbourneVictoria3001Australia

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and *** the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction *** performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine *** previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of ***,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF *** the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,*** examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM *** of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied *** newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed ***,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHA

关键词： Tunnel boring machine random forest GOGHS optimization PSO optimization GA optimization ABC optimization SHAP

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Continuous flow pyrolysis of virgin and waste polyolefins:a comparative study,process optimization and product characterization

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Frontiers of Chemical Science and engineering 2024年第6期18卷 133-149页

作者： Ecrin Ekici Güray Yildiz Magdalena Joka Yildiz Monika Kalinowska ErolŞeker Jiawei Wang Karlsruhe Institute of Technology Institute of Catalysis Research and TechnologyEggenstein-Leopoldshafen 76344Germany Izmir Institute of Technology Faculty of EngineeringDepartment of Energy Systems EngineeringIzmir 35430Türkiye Department of Materials Engineering and Production Faculty of Mechanical EngineeringBialystok University of TechnologyBialystok 15-351Poland Department of Agricultural and Food Engineering and Environmental Development Institute of Civil Engineering and EnergeticsFaculty of Civil Engineering and Environmental SciencesBialystok University of Technology15-351 BialystokPoland Department of Chemistry Biology and BiotechnologyInstitute of Civil Engineering and EnergeticsFaculty of Civil Engineering and Environmental SciencesBialystok University of TechnologyBialystok 15-351Poland Izmir Institute of Technology Faculty of EngineeringDepartment of Chemical EngineeringIzmir 35430Türkiye Energy and Bioproducts Research Institute(EBRI) Aston UniversityBirmingham B47ETUnited Kingdom

Under optimal process conditions,pyrolysis of polyolefins can yield ca.90 wt%of liquid product,i.e.,combination of light oil fraction and heavier *** this work,the experimental findings reported in a selected group of publications concerning the non-catalytic pyrolysis of polyolefins were collected,reviewed,and compared with the ones obtained in a continuously operated bench-scale pyrolysis *** process parameters were used for the pyrolysis of waste and virgin counterparts of high-density polyethylene,low-density polyethylene,polypropylene and a defined mixture of those(i.e.,25:25:50 wt%,respectively).To mitigate temperature drops and enhance heat transfer,an increased feed intake is employed to create a hot melt plastic *** 1.5 g·min^(-1) feed intake,1.1 L·min^(-1) nitrogen flow rate,and a moderate pyrolysis temperature of 450℃,the formation of light hydrocarbons was favored,while wax formation was limited for polypropylene-rich *** of virgin plastics yielded more liquid(maximum 73.3 wt%)than that of waste plastics(maximum 66 wt%).Blending polyethylenes with polypropylene favored the production of liquids and increased the formation of gasoline-range *** products were mainly composed of C3 hydrocarbons,and no hydrogen production was detected due to moderate pyrolysis temperature.

关键词： waste plastics polyolefins chemical recycling pyrolysis alternative fuels waste-to-energy

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Influence of MnO_(x)deposition on TiO_(2)nanotube arrays for electrooxidation

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Green Energy & Environment 2023年第2期8卷 612-618页

作者： Kaihang Zhang Yuanzheng Zhang Su Liu Xin Tong Junfeng Niu Dong Wang Junchen Yan Zhaoyang Xiong John Crittenden Brook Byers Institute of Sustainable Systems and School of Civil and Environmental Engineering Georgia Institute of TechnologyAtlantaGA 30332USA College of Environmental Science and Engineering North China Electric Power UniversityBeijing102206China

TiO_(2)has demonstrated outstanding performance in electrochemical advanced oxidation processes(EAOPs)due to its structural stability and high oxygen ***,there is still much room for improving its electrochemical ***,narrow bandgap manganese oxide(MnO_(x))was composited with TiO_(2)nanotube arrays(TiO_(2)NTAs)that in-situ oxidized on porous Ti sponge,forming the MnO_(x)-TiO_(2)NTAs *** and XPS analysis further proved that the composition of MnO_(x)is *** characterizations revealed that increasing the composited concentration of MnO_(x)can improve the conductivity and reduce oxygen evolution potential so as to improve the electrochemical activity of the composited MnO_(x)-TiO_(2)NTAs ***,the optimal degradation rate of benzoic acid(BA)was achieved using MnO_(x)-TiO_(2)NTAs with a MnO_(x)concentration of 0.1 mmol L^(-1),and the role of MnO_(x)was proposed based on DFT ***,the required electrical energy(EE/O)to destroy BA was optimized by varying the composited concentration of MnO_(x)and the degradation *** quantitative results are of great significance for the design and application of high-performance materials for EAOPs.

关键词： TiO_(2)nanotube arrays Oxidation mechanism Energy efficiency assessment MnO_(x)band structure Electrochemical advanced oxidation processes

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Insight into the mechanisms of trichloronitromethane formation by vacuum ultraviolet: QSAR model and FTICR-MS analysis

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Journal of environmental Sciences 2023年第3期125卷 215-222页

作者： Xiaojun Chen Yangtao Wu Weiqiu Zhang Lingjun Bu Shumin Zhu Da Sheng Shiqing Zhou John C.Crittenden Key Laboratory of Building Safety and Energy Efficiency Ministry of EducationDepartment of Water Engineering and ScienceCollege of Civil EngineeringHunan UniversityChangsha 410082China School of Civil and Environmental Engineering and the Brook Byers Institute for Sustainable Systems Georgia Institute of TechnologyGeorgia 30332USA

Vacuum ultraviolet(VUV) photolysis is recognized as an environmental-friendly treatment process. Nitrate(NO-3) and natural organic matter(NOM) are widely present in water *** investigated trichloronitromethane(TCNM) formation during chlorination after VUV photolysis, because TCNM is an unregulated highly toxic disinfection byproduct. In this study:(1) we found reactive nitrogen species that is generated under VUV photolysis of NO-3react with organic matter to form nitrogen-containing compounds and subsequently form TCNM during chlorination;(2) we found the mere presence of 0.1 mmol/L NO-3can result in the formation of up to 63.96 μg/L TCNM;(3) we found the changes in pH(6.0-8.0), chloride(1-4 mmol/L), and bicarbonate(1-4 mmol/L) cannot effectively diminish TCNM formation;and,(4) we established the quantitative structure-activity relationship(QSAR) model,which indicated a linear relationship between TCNM formation and the Hammett constant(σ) of model compounds;and,(5) we characterized TCNM precursors in water matrix after VUV photolysis and found 1161 much more nitrogen-containing compounds with higher aromaticity were generated. Overall, this study indicates more attention should be paid to reducing the formation risk of TCNM when applying VUV photolysis process at scale.

关键词： Vacuum ultraviolet Natural organic matter Hammett constant FTICR-MS Trichloronitromethane

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On the Efficacy of Sparse Representation Approaches for Determining Nonlinear Structural System Equations of Motion

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ASCE-ASME Journal of Risk and Uncertainty in engineering systems, Part B: Mechanical engineering 2025年第3期11卷 031207页

作者： Pasparakis, George D. Fragkoulis, Vasileios C. Kougioumtzoglou, Ioannis A. Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Civil and Environmental Engineering University of Liverpool LiverpoolL69 3GH United Kingdom Department of Civil Engineering and Engineering Mechanics Columbia University 500 W 120th Street New YorkNY10027 United States

A sparsity-based optimization approach is presented for determining the equations of motion of stochastically excited nonlinear structural systems. This is done by utilizing measured excitation-response realizations in the formulation of the related optimization problem, and by considering a library of candidate functions for representing the system governing dynamics. Note that a novel aspect of the approach relates to treating, also, systems endowed with fractional derivative elements. Clearly, this is of significant importance to a multitude of diverse applications in engineering mechanics taking into account the enhanced modeling capabilities of fractional calculus. Further, the fundamental theoretical and computational aspects of various representative, state-of-the-art, numerical schemes for solving the derived sparsity-based optimization problem are reviewed and discussed. A Bayesian compressive sampling approach that exhibits the additional advantage of quantifying the uncertainty of the estimates is considered as well. Furthermore, comparisons and a critical assessment of the employed numerical schemes are provided with respect to their efficacy in determining the nonlinear structural system equations of motion. In this regard, two illustrative numerical examples are considered pertaining to a nonlinear tuned mass-damper–inerter vibration control system and to a nonlinear electromechanical energy harvester, both endowed with fractional derivative elements. Copyright © 2025 by ASME.

关键词： Nonlinear equations

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A hybrid machine-learning model for solar irradiance forecasting

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Clean Energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf Tarek H.M.El-Fouly Vasileios E.Katzourakis Mohamed S.El Moursi Constantinos V.Chrysikopoulos Department of Industrial and Systems Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE Electrical Engineering and Computer Science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE School of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and Medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

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Sub-zero soil CO2 respiration in biostimulated hydrocarbon-contaminated cold-climate soil can be linked to the soil-freezing characteristic curve

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environmental Science and Pollution Research 2025年第4期32卷 1783-1804页

作者： Nayeema, Tasnim Lee, Aslan Hwanhwi Richter, Amy Ng, Kelvin Tsun Wai Chang, Wonjae Department of Civil Geological and Environmental Engineering College of Engineering University of Saskatchewan 57 Campus Drive Engineering Building SaskatoonSKS7N 5A9 Canada Faculty of Engineering and Applied Science Environmental Systems Engineering University of Regina 3737 Wascana Parkway ReginaSKS4S 0A2 Canada

Extending unfrozen water availability is critical for stress-tolerant bioremediation of contaminated soils in cold climates. This study employs the soil-freezing characteristic curves (SFCCs) of biostimulated, hydrocarbon-contaminated cold-climate soils to efficiently address the coupled effects of unfrozen water retention and freezing soil temperature on sub-zero soil respiration activity. Freezing-induced soil respiration experiments were conducted under the site-relevant freezing regime, programmed from 4 to − 10 °C at a seasonal soil-freezing rate of − 1 °C/day. The effects of unfrozen water retention on extending soil respiration activity emerged at the onset of soil-freezing. The unfrozen water effect became significant below 0 °C (correlation r = 0.83–0.94) and comparable to the temperature effect (correlation r = 0.82–0.90), successfully demonstrating the coupled effects on sub-zero respiration activity. Soil CO2 respiration modelling based on the temperature dependency only (Arrhenius and Q10 models) did not accurately describe sub-zero respiration activity associated with increased unfrozen water retention in treated contaminated soils. The shifted SFCCs of the treated soils, expressed as a function of soil temperature (T) and unfrozen water content (θ), served as a key framework for efficiently developing the sub-zero respiration model (SFCC-RESP). The developed SFCC-RESP model closely approximated the changes in soil respiration rates influenced by T and θ in the treated soils (R2 = 0.94–0.98) and described the abrupt decrease and subsequent stabilization in CO2 production during the transition to the deeply frozen soil phase. The SFCC-RESP model integrated with soil thermal models (TEMP/W) can be used to produce spatial distributions of T, θ, and CO2 production in the treated soil matrix, providing a tool to approximate the abundance of unfrozen habitable niches when developing cold-tolerant bioremediation strategies. © The Author(s), under exclusive li

关键词： Soil pollution

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