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Sustainable Water Optimization Tool (SUWO): An Optimization Framework for the Water-Energy-Food-Ecosystem Nexus

WATER 2025年第9期17卷 1280-1280页

作者： Yaykiran, Salim Ekdal, Alpaslan Istanbul Tech Univ Environm Engn Dept TR-34469 Maslak Turkiye

Sustainable water management requires integrated approaches balancing competing demands and environmental sustainability. This study introduces the Sustainable Water Optimization Tool (SUWO), an open-source, Python-based simulation-optimization framework for basin-scale surface-water-resources management. SUWO employs the water-energy-food-ecosystem (WEF-E) nexus approach, utilizing a multi-objective genetic algorithm (MOGA) to generate Pareto-optimal solutions and facilitate a trade-off analysis among water uses through simulations of reservoir operations, hydro-energy production, irrigation, and flow regulation. SUWO integrates scenario analysis with multi-criteria decision making (MCDM), enabling the evaluation of various management, climate, and environmental scenarios. The framework was applied to the Sakarya River Basin (SRB) in T & uuml;rkiye, a rapidly developing region pressured by water infrastructure development, hydroelectric power plants (HEPPs), and irrigation expansion. The SUWO-SRB model showed that while Non-dominated Sorting genetic algorithm II (NSGA-II) generally exhibited superior performance, NSGA-III presented a competitive alternative. The optimization results were analyzed across four management scenarios under varying hydrological conditions and environmental management classes (EMCs) for the near future. The model results highlight WEF-E nexus trade-offs. Maximizing energy production often impacts irrigation and the ecosystem, while prioritizing sustainable irrigation can reduce energy output. Dry conditions reduce hydropower and irrigation capacity, emphasizing water scarcity vulnerabilities. Ecological deviation negatively correlates with anthropogenic factors.

关键词： water resources management multi-objective optimization multi-objective genetic algorithm WEF-E nexus trade-off analysis environmental flows reservoir operation irrigation Sakarya Basin Python

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An Acceleration Feedback-Based Active Control Method for High-Speed Elevator Horizontal Vibration

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JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES 2024年第2期12卷 1943-1956页

作者： Zhao, Mengmeng Qin, Chengjin Tang, Rui Tao, Jianfeng Xu, Shuang Liu, Chengliang Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

PurposeDue to the influence of uneven guide rail, rope swing and unbalanced shaft wind pressure, the high-speed elevator car may experience violent horizontal vibration, which seriously affects the comfort and safety of elevator passengers. Hence, it is vital to suppress horizontal vibration for high-speed elevator car (HSEC).MethodsThis paper proposes a horizontal vibration active control method for high-speed elevators via acceleration feedback. First, based on passive vibration reduction, the active control is used to establish a four-degree of freedom (4-DOF) horizontal vibration model for elevator car. Then, we design an acceleration feedback-based controller for horizontal vibration response induced by guide rail excitation. The control objective functions in the multi-objective genetic algorithm are the system performance and control cost. The Pareto optimal solution set of the optimal controller parameters can be obtained only through one optimization *** use the comprehensive control simulation analysis through MATLAB/Simulink to validate the vibration suppression effect for the proposed active control strategy. For the system performance, by comparing the time domain responses of no controller and using controllers C1/C2/C3, the horizontal vibration acceleration is reduced to a certain extent. The offset of the high-speed elevator car high-speed elevator car frame relative to the center of the hoistway and relative displacements between the HSEC and the HSEC frame are also reduced in a certain proportion. The control cost is employed to evaluate the control force and represents the energy consumption to a certain extent. Combining system performance and control costs, we choose C2 among the 3 sets of controller parameters, the horizontal vibration acceleration of the HSEC can be reduced by about 80%, while the power consumption is between C2 and *** proposed optimal controller could effectively suppress elevator car horizont

关键词： High-speed elevator Vibration suppression Acceleration feedback active control multi-objective genetic algorithm

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multi-objective Optimization of Activation Time and Discharge Time of Thermal Battery Using a genetic algorithm Approach

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ENERGIES 2020年第24期13卷 6477页

作者： Li, Qing Shao, Yu-Qiang Liu, Huan-Ling Shao, Xiao-Dong Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China China Elect Technol Grp Corp 18th Res Inst Tianjin 300384 Peoples R China

Activation time and discharge time are important criteria for the performance of thermal batteries. In this work a heat transfer analysis is carried out on the working process of thermal batteries. The effects of the thicknesses of heat pellets which are divided into three groups and that of the thickness of insulation layers on activation time and discharge time of thermal batteries are numerically studied using Fluent 15.0 when the sum of the thickness of heating plates and insulation layers remain unchanged. According to the numerical results, the optimal geometric parameters are obtained by using multi-objective genetic algorithm. The results show that the activation time is mainly determined by the thickness of the bottom heat pellet, while the discharge time is determined by the thickness of the heat pellets and that of the insulation layers. The discharge time of the optimized thermal battery is increased by 4.08%, and the activation time is increased by 1.23%.

关键词： thermal batteries activation time discharge time multi-objective genetic algorithm

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Optimization and Modeling of a Spatial CAM Mechanism for a Two-Dimensional Plunger Electro-Hydraulic Pump

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IEEE ACCESS 2023年 11卷 128354-128368页

作者： Qiu, Xinguo Wang, Fucheng Li, Changlong Yi, Bida Ruan, Jian Jiang, Wei Zhejiang Univ Technol Coll Mech Engn Hangzhou 310023 Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Proc Techn Minist Educ & Zhejiang Prov Hangzhou 310023 Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Mfg Techno Minist Educ & Zhejiang Prov Hangzhou 310014 Peoples R China

Traditional cam movements in piston pumps follow a non-stopping motion law, resulting in insufficient smoothness in plunger stroke changes. Consequently, this directly impacts the theoretical flow rate of the pump. To address this issue, describes the transition curve of the non-stopping motion law is constructed in this study by using a fivefold B-spline curve. The maximum uncaused velocity and acceleration are considered optimization parameters. multi-objective optimization of the motion law is conducted using a genetic algorithm, resulting in the generation of a Pareto solution set. Compared to the modified equivalent acceleration (MEA) motion law, the B-spline combined motion law leads to a reduction of 1.39% and 0.86% in the maximum velocity and acceleration characteristic values, respectively. Furthermore, by employing the principle of a single-parameter surface envelope, a mathematical model of the cam surface is developed. The obtained data points are then solved using the double-three times B-spline cam surface interpolation algorithm. Subsequently, the interpolation result is translated into a cam surface model file based on the data structure of the IGES *** optimization results demonstrate that compared to equal acceleration and deceleration motion laws, the B-spline optimization curve achieves a seamless transition. Specifically, the maximum pressure angle decreases from 27.98(degrees) to 19.92(degrees), and the minimum radius of curvature decreases from 9.94 mm to 7.44 mm, validating the accuracy of the theoretical analysis. Experimental displacement tests are conducted on the spatial cam mechanism, revealing that the cam design process has been streamlined, and the designed spatial cam exhibits enhanced fitting performance.

关键词： Splines (mathematics) Shafts Pistons Mathematical models Couplers Motion segmentation Hydraulic systems Electrohydraulics genetic algorithms Space CAM mechanism two-dimensional plunger electro-hydraulic pump B-spline curve multi-objective genetic algorithm envelope principle of a single-parameter surface

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Fuzzy Logic Enhanced Second-Order Sliding Mode Controller Design for an Experimental Twin Rotor System Under External Disturbances

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JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES 2024年第SUPPL 1期12卷 1103-1117页

作者： Ozer, Hasan Omur Hacioglu, Yuksel Yagiz, Nurkan Istanbul Univ Cerrahpasa Vocat Sch Tech Sci Dept Elect & Energy Istanbul Turkiye Istanbul Univ Cerrahpasa Fac Engn Dept Mech Engn Istanbul Turkiye

BackgroundThe twin rotor model is frequently studied by researchers because although it has a basic structure the coupled pitch and yaw motions are adequately represented. However, it is quite difficult to obtain an efficient controller due to external disturbances. Classical sliding mode controller (SMC), which is of first order, is recognized to be robust in case of parameter changes and external disturbances especially when the sliding motion takes place, but it possesses chattering in the control input which may damage the mechanical parts of the *** this study it was aimed to design a robust controller without chattering effect which will be used for the control of the twin rotor system in real time *** remedy the chattering issue, a novel fuzzy logic enhanced second-order sliding mode controller (FSOSMC) based on super twisting algorithm is proposed. This controller suppresses chattering while enhancing the robustness of the controller where the sliding surface slope parameter is updated online via a fuzzy logic unit. Then the proposed controller is implemented on an experimental twin-rotor system which has highly nonlinear and coupled *** time experiments were performed on the twin rotor system using the proposed FSOSMC. For comparison purpose the SMC and second-order sliding mode controller (SOSMC) were also applied to the same system. The results have shown that the proposed controller increased the tracking performance without increasing the control effort while reducing the *** experimental results verified the success of the designed FSOSMC, therefore it may be recommended for the robust and precise control of aerial vehicles.

关键词： Fuzzy second order sliding mode control Twin rotor model Experimental results multi-objective genetic algorithm

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multi-objective optimisation design of stator slot parameters for bearingless induction motors

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INTERNATIONAL JOURNAL OF ELECTRONICS 2025年

作者： Shen, Zijun Yang, Zebin Sun, Xiaodong Pan, Wei Jiangsu Univ Sch Elect Informat Engn Zhenjiang 212013 Peoples R China Jiangsu Univ Automot Engn Res Inst Zhenjiang Peoples R China

In bearingless induction motors (BIM), the performance is significantly influenced by two sets of windings embedded in the stator slots for suspension and torque. To enhance the suspension and torque performance of BIMs, a multi-objective optimisation design method for BIM stator slot parameters was proposed in this paper. Firstly, based on the analysis of the mechanism for generating suspension force in BIMs and the identification of optimisation parameters for the motor's stator slots, high-sensitivity optimisation parameters had been determined through experiments using the Taguchi method and sensitivity analysis. Secondly, the BIM stator slots were modelled using the response surface methodology, combined with an enhanced multi-objective non-dominated sorting genetic algorithm (NSGA-II). A comprehensive optimisation was conducted for the high-sensitivity parameters, namely slot width Hs0, slot opening depth Hs1, and slot depth Bs0, to identify the optimal parameter combination that maximises both suspension and torque performance. The effectiveness of stator parameter optimisation was verified by comparing the motor's torque and suspension force performance before and after optimisation. Finally, a physical prototype of the optimised motor was constructed, and an experimental platform was established to test the performance of the optimised motor. Both simulation and experimental results indicated that the optimised motor experienced an increase in average suspension force, with reductions in both torque and suspension force ripple, leading to a significant enhancement in BIM performance.

关键词： Bearingless induction motor response surface modelling multi-objective genetic algorithm optimization design Taguchi method

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Novel adaptive cyberattack prediction model using an enhanced genetic algorithm and deep learning (AdacDeep)

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INFORMATION SECURITY JOURNAL 2022年第1期31卷 105-124页

作者： Ibor, Ayei E. Oladeji, Florence A. Okunoye, Olusoji B. Uwadia, Charles O. Univ Calabar Dept Comp Sci Calabar Nigeria Univ Lagos Dept Comp Sci Lagos Nigeria

Some of the problems of extant cyberattack prediction approaches are low prediction accuracy, high false positive rate, very long training time, and the choice of hyperparameters to overcome overfitting or under fitting the model on the training data. These problems have culminated in the escalation of cyberattacks in recent times and as such significant improvement to the performance of extant models is crucial. Some deep learning architectures such as Recurrent Neural Networks (RNN) have been applied to cyberattack prediction. However, Recurrent Neural Networks (RNN) suffer from the vanishing and exploding gradient problem, and are difficult to train. Also, determining the different states and hyperparameters of the network for optimal prediction performance is difficult. Therefore, this paper proposes a novel approach called AdacDeep that uses an Enhanced genetic algorithm (EGA), Deep Autoencoder and a Deep Feedforward Neural Network (DFFNN) with backpropagation learning to accurately predict different attack types. The performance of AdacDeep is evaluated using two well-known datasets, namely, the CICIDS2017 and UNSW_NB15 datasets as the benchmark. The experimental results show that AdacDeep outperforms other state-of-the-art comparative models in terms of prediction accuracy with 0.22-35% improvement, F-Score with 0.1-34.7% improvement and very low false positive rate.

关键词： Deep learning multi-objective genetic algorithm cyberattack prediction information security network traffic

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Optimizing the Geometrical Dimensions of the Seat Suspension Equipped with a Negative Stiffness Structure Based on a genetic algorithm

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SAE INTERNATIONAL JOURNAL OF VEHICLE DYNAMICS STABILITY AND NVH 2022年第2期6卷 147-158页

作者： Zha, Jili Nguyen, Vanliem Ni, Dengke Su, Beibei Hubei Polytech Univ Sch Mech & Elect Engn Huangshi Hubei Peoples R China Hubei Polytech Univ Hubei Key Lab Intelligent Conveying Technol & Dev Huangshi Hubei Peoples R China

Based on the negative stiffness structure (NSS) designed on the seat suspension and the effect of the geometrical parameters of the designed NSS on improving the driver's ride comfort, a new optimal method of the multi-objective genetic algorithm (MOGA) is then researched and applied for optimizing the stiffness ratio beta of the seat suspension and the geometrical parameters alpha(1) and alpha(2) of the NSS to further improve the driver's ride comfort and health. The reduction of the root-mean-square (RMS) displacement of the driver's seat (X-RMSs), the weighted RMS acceleration of the driver's seat (a(RMSs)), and the seat effective amplitude transmissibility (SEAT) of the seat suspension are chosen as the objective functions. The study results show that with the optimal parameters of alpha(1) = 1.355, alpha(2) = 1.001, and beta = 0.511, the seat suspension using the optimized NSS has a good effect on isolating low-frequency vibration under various excitation sources of the random, harmonic, and bumpy functions. Particularly, the results of X-RMSs, a(RMSs), and SEAT with the optimized NSS are remarkably reduced by 13.35%, 22.51%, and 22.47%, respectively, compared to the designed NSS, and by 44.65%, 69.45%, and 69.44% in comparison without the NSS under a random excitation of the floor of the cab or vehicle. Therefore, this research results not only contribute to the existing body of knowledge on the seat suspensions equipped with the NSS but also can provide an important reference for optimal design or control of the seat suspension to further improve its isolating efficiency.

关键词： Seat dynamic model Negative stiffness structure Ride comfort multi-objective genetic algorithm

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Optimization of Triangular Airfoils for Martian Helicopters Using Direct Numerical Simulations

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AIAA JOURNAL 2023年第11期61卷 4935-4945页

作者： Caros, Lidia Buxton, Oliver Vincent, Peter Imperial Coll London Dept Aeronaut London SW7 2AZ England

Mars has a lower atmospheric density than Earth, and the speed of sound is lower due to its atmospheric composition and lower surface temperature. Consequently, Martian rotor blades operate in a low-Reynolds-number compressible regime that is atypical for terrestrial helicopters. Nonconventional airfoils with sharp edges and flat surfaces have shown improved performance under such conditions, and second-order-accurate Reynolds-averaged Navier-Stokes (RANS) and unsteady RANS (URANS) solvers have been combined with genetic algorithms to optimize them. However, flow over such airfoils is characterized by unsteady roll-up of coherent vortices that subsequently break down/transition. Accordingly, RANS/URANS solvers have limited predictive capability, especially at higher angles of attack where the aforementioned physics are more acute. To overcome this limitation, we undertake optimization using high-order direct numerical simulations (DNSs). Specifically, a triangular airfoil is optimized using DNSs. multi-objective optimization is performed to maximize lift and minimize drag, yielding a Pareto front. Various quantities, including lift spectra and pressure distributions, are analyzed for airfoils on the Pareto front to elucidate flow physics that yield optimal performance. The optimized airfoils that form the Pareto front achieve up to a 48% increase in lift or a 28% reduction in drag compared to a reference triangular airfoil studied in the Mars Wind Tunnel at Tohoku University. The work constitutes the first use of DNSs for aerodynamic shape optimization.

关键词： Computational Fluid Dynamics Low Reynolds Number Martian Aerodynamics Direct Numerical Simulation multi-objective genetic algorithm Aerodynamic Shape Optimization

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Designing Satellite Constellations to Observe Earth's Time-Varying Gravity from Clock Frequency Comparisons

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JOURNAL OF SPACECRAFT AND ROCKETS 2023年第3期60卷 848-858页

作者： Lee, Kwonhee A. Gunter, Brian C. Georgia Inst Technol Atlanta GA 30332 USA Daniel Guggenheim Sch Aerosp Engn Atlanta GA USA

The nondominated sorting genetic algorithm III (NSGA-III) is used to design nonsymmetric satellite constellations to observe large-scale high-frequency gravity variations that would serve as complementary systems to other dedicated gravity field mapping missions such as the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On missions. The functionality of the NSGA-III method is validated by reproducing optimal surface-coverage satellite constellations from the literature. Then, NSGA-III is used to generate nondominated constellations tuned to detect short-term long-wavelength gravity field variations. The constellations are used to generate subweekly gravity field solutions from clock frequency comparison measurements. The effectiveness of NSGA-III for optimizing nonsymmetric constellations was demonstrated because the constellations obtained from NSGA-III were consistently superior in performance than traditional symmetric constellations. Furthermore, the results showed that the time-varying signals of interest (that is, gravity coefficients through the spherical harmonic degree and order of seven at daily intervals) can be unambiguously resolved by assuming an optical clock with a 4.8x10-18 fractional frequency uncertainty representative of current technology. The ability to monitor these short-term long-wavelength signals on a global scale would observe a spectrum of the gravity field inherently undetectable by GRACE-like missions, and it would provide new insight to the understanding of global mass redistribution processes.

关键词： multi objective genetic algorithm Gravity Recovery and Climate Experiment Geophysics Satellite Geodesy Satellite Constellations Spherical Harmonics multi-objective genetic algorithm Satellite Remote Sensing

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