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

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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Quasi-perfect and wideband absorption with gradient non-uniform micro-slit array absorber via a hierarchical optimization method

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APPLIED ACOUSTICS 2023年第1期206卷

作者： Liao, Weiwei Hu, Run Xing, Guanying Luo, Xiaobing Huazhong Univ Sci & Technol Sch Energy & Power Engn Wuhan 430074 Peoples R China

Gradient micro-slit array absorber, a kind of acoustic metamaterial, made of multiple quarter-wavelength resonators, is holding a promising future in industrial utilization due to its flexible adaptation and simple structure. However, designing a perfect and broadband absorber remains a huge challenge because of the larger number of the design parameters and complicated coupling effect between different resonators. In this study, a hierarchical optimization method is developed for gradient micro-slit array absorber. First, a prior test based on two-slit absorber is conducted using transfer matrix method (TMM) to give directions on designing a multi-slit absorber. And then an original absorber model is constructed in the range of 1000-1800 Hz. For the first step, the optimal width of the slit is obtained through the analysis of the qual-ity factor. For the second step, the spacings between slits is optimized by maximizing absorption and minimizing the total length of the waveguide. After optimization, the absorption performance of the opti-mized model increased by 15.6% and the length decreased by 46% compared with the original model. Finally, the gradient micro-slit array absorber is experimentally investigated and achieves a quasi-perfect and flat absorption ranging from 1000 Hz to 1800 Hz.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Transfer matrix method Visco-thermal analysis multi-objective genetic algorithm optimization Quarter-wavelength resonator

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Research on optimization method of stainless steel sawing process parameters based on multi-tooth sawing force prediction model

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第9-10期128卷 4513-4533页

作者： Ni, Pengcheng Wang, Yangyu Tan, Dapeng Zhang, Yongle Chen, Zhenzhen Wang, Zheng Yi, Chunhong Shao, Lu Lu, Yanhui Zhejiang Univ Technol Coll Mech Engn Hangzhou 310014 Zhejiang Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Proc Tech Minist Educ Hangzhou 310014 Zhejiang Peoples R China Zhejiang Sany Equipment Co Ltd Huzhou 313000 Peoples R China Hangzhou Wheeler Gen Machinery Co Ltd Hangzhou 311400 Peoples R China

In this study, a multi-tooth sawing force prediction model is proposed for the stainless steel sawing process, combined with the classical cutting theory of band saw and the introduction of tooth equivalent cutting width. Through the numerical simulation of sawing process and sensitivity analysis method, the influence law of feed speed and cutting speed on cutting force was analyzed. A sawing process parameter optimization design model with sawing force and sawing efficiency as the optimization objectives was established and solved by multi-objective optimization algorithm to determine the optimal combination of coordinated sawing force and sawing efficiency process parameters. The stainless steel sawing test results show that the multi-tooth sawing force prediction model and the experimental results match;the maximum error does not exceed 6%, making it better to achieve the prediction of sawing force in high-frequency strong impact conditions. With the optimized design of process parameters, the sawing force decreased by a maximum 20.43%, and the sawing efficiency increased by a maximum 54.72%. This study provides a reference for metal sawing force prediction and process parameter optimization, and also offers theoretical guidance for developing high-end sawing equipment.

关键词： Sawing force prediction model Numerical simulation of sawing process multi-objective genetic algorithm Optimization of sawing parameters

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Optimal design, intelligent fuzzy logic and model predictive control for high-purity ethyl-methyl carbonate and diethyl carbonate production using reactive dividing wall column

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2023年第1期195卷 691-710页

作者： Liu, Botong Han, Yicheng Liu, Botan Ge, Xiaolong Yuan, Xigang Tsinghua Univ Dept Chem Engn Beijing 100084 Peoples R China Tianjin Univ Sci & Technol Coll Chem Engn & Mat Sci Tianjin Key Lab Brine Chem Engn & Resource Ecoutil Tianjin 300457 Peoples R China Tianjin Univ State Key Lab Chem Engn Tianjin 300350 Peoples R China

Methyl carbonate (EMC) and Diethyl carbonate (DEC), as excellent solvents for lithium-ion electrolytes, are synthesized by transesterification, and consecutive reaction seriously complicate optimization and control issues. Process synthesis, parameters optimization and advanced control are crucial points that should be addressed for this ill-conditioned and highly nonlinear system, which is the motivation and novelty of present work. With single-objective and multi-objective genetic algorithm, intensified processes for EMC and DEC production were optimized respectively with heterogeneous catalyst. And reactive dividing wall column achieved 23% and 13% total annualized cost reductions compared with reactive distillation for two target carbonates. Based on optimal steady-state solution, intelligent fuzzy logic and model predictive control of EMC and DEC production is conducted to clarify their respective strengths in intensified process with consecutive reaction. Sequential optimization for parameters of FLC was carried out with Integral of Squared Error (ISE) as objective. Finally, control performance of FLC and LPMC are compared with that under PID control, and results show that overshoot and transition time under FLC and LMPC are obviously mitigated, along with evident reduction in ISE. & COPY;2023 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Process intensification Reactive dividing wall column multi-objective genetic algorithm Fuzzy logic control Model predictive control

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Recent Advancements in the Optimization Capacity Configuration and Coordination Operation Strategy of Wind-Solar Hybrid Storage System

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Energy Engineering 2025年第1期122卷 285-306页

作者： Hongliang Hao Caifeng Wen Feifei Xue Hao Qiu Ning Yang Yuwen Zhang Chaoyu Wang Edwin E.Nyakilla Department of New Energy Storage Peking University Ordos Research Institute of EnergyOrdos017010China School of Energy and Power Engineering Inner Mongolia University of TechnologyHohhot010080China Key Laboratory of Wind Energy and Solar Energy Utilization Technology Inner Mongolia University of TechnologyHohhot010051China

Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy *** paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,***/Simulink was used for simulation *** optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 ***,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations *** proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.

关键词： Electric-thermal hybrid storage modal decomposition multi-objective genetic algorithm capacity optimization allocation operation strategy

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Optimal composition of biomass pellet for enhancing calorific value using MOGA-ANN: a mixture of paddy straw, sawdust, cow dung, and paper pulp

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BIOMASS CONVERSION AND BIOREFINERY 2023年 1-17页

作者： Ali, Arshad Kumari, Meena Laura, Jitender Singh Rizwanullah, Mohammad Manisha Chhabra, Deepak Sahdev, Ravinder Kumar Maharshi Dayanand Univ Univ Inst Engn & Technol Dept Mech Engn Rohtak 124001 Haryana India Maharshi Dayanand Univ Univ Inst Engn & Technol Dept Elect Engn Rohtak 124001 Haryana India Maharshi Dayanand Univ Dept Environm Sci Rohtak 124001 Haryana India Manipal Univ Dept Math & Stat Jaipur 302001 Rajasthan India

Agro-residues (paddy straw, wheat straw, stems, corncobs, etc.) and solid wastes (paper boards, municipal solid wastes, food wastes, etc.) were identified as the primary sources of biomass in remote and rural areas. It has the potential to contribute to energy needs for direct heating and power generation applications in a sustainable manner through the manufacturing of biomass-based pellets. In this work, biomass pellets were fabricated using paddy straw, cow dung, and paper pulp binder. A total number of twenty-six pellets were produced with input variables as paddy straw (P), sawdust (S), and cow dung (C) using a face-centered central composite design (FCCCD) to evaluate the calorific value (CV) and ash content (AC). A bomb calorimeter was used to investigate the calorific value and ash content of pellets. Furthermore, an artificial neural network (ANN) integrated with the multi-objective genetic algorithm (MOGA) and response surface methodology ( RSM) model was developed to maximize the CV and AC. The optimal composition of biomass pellets, as recorded by the MOGA-ANN hybrid technique, was 37.71, 20.00, and 41.29 g for paddy straw, sawdust, and binder, respectively, yielding a CV of 3745 Cal/g and AC of 0.0619 g, resulting in an increase of 3.2%, 2.6%, and 7% CV and a 40% reduction in AC. The optimal results obtained with MOGA-ANN tools were experimentally validated. The MOGA-ANN approach of pellet fabrication has the potential to enhance the CV and probable application of biomass-based pellet as an alternative source of fuel.

关键词： Pellets Biomass Artificial neural network multi-objective genetic algorithm Calorific value

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Pareto Optimal Design of a Fuzzy Adaptive Hierarchical Sliding-mode Controller for an X-Z Inverted Pendulum System

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IETE JOURNAL OF RESEARCH 2023年第5期69卷 3052-3069页

作者： Abedzadeh Maafi, R. Etemadi Haghighi, S. Mahmoodabadi, M. J. Islamic Azad Univ Dept Mech Engn Sci & Res Branch Tehran Iran Sirjan Univ Technol Dept Mech Engn Sirjan Iran

The control problem of a three-degree-of-freedom (3-DOF) X-Z inverted pendulum as an unstable, multi-input-multi-output, under-actuated and high-order nonlinear system is facing many challenges. In this paper, a Fuzzy Adaptive Hierarchical Sliding-Mode Controller (FAHSMC) is optimally designed for the X-Z inverted pendulum system utilizing the multi-objective genetic algorithm (MOGA). To this end, at first, the state variables of this system are converted to the new state variables via five steps of a forward transformation process. In this transformation, the dynamical equations of the X-Z inverted pendulum system are reorganized to an appropriate form for control implementations. Then, the novel FAHSMC is designed for stabilization and tracking control of the system, and the stability analysis of the controller is proved via the Lyapunov stability theory. After that, the state and control variables of the X-Z inverted pendulum are computed through six steps of a backward transformation process. Ultimately, the MOGA is exerted for Pareto optimal design of the proposed control approach applied on the regarded X-Z inverted pendulum system. The tracking error of the cart position in the X-direction, the tracking error of the cart position in the Z-direction and the angle error of the pendulum are selected as three inconsistent objective functions for multi-objective optimization operations. Numerical results and diagrams illustrate that the proposed approaches can accurately converge the system states to the desirable trajectories in a short time and yield superior Pareto optimal fronts in comparison with the Hierarchical Sliding-Mode Controller (HSMC) and the Adaptive Hierarchical Sliding-Mode Controller (AHSMC).

关键词： X-Z inverted pendulum forward transformation backward transformation fuzzy adaptive hierarchical sliding-mode controller multi-objective genetic algorithm Pareto optimal design

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Method of improving the soil compactor's ride quality based on the optimal negative stiffness structure

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INTERNATIONAL JOURNAL OF VEHICLE DESIGN 2023年第1-3期91卷 181-207页

作者： Liem, Nguyen Van Ni, Dengke Hubei Polytech Univ Sch Mech & Elect Engn Huangshi 435003 Peoples R China

A new driver's seat suspension designed by the negative-stiffness-structure (NSS) and cab's isolation used by the hydraulic mounts are proposed to enhance the soil compactor's ride quality. A nonlinear vehicle dynamics model that considers the interaction between the wheel/drum and deformable terrains is established to evaluate the NSS's performance. Based on the genetic algorithm, NSS's parameters are optimised to further improve ride quality. The ride quality is evaluated through the displacement and acceleration of the seat and cab in the frequency and time domains. The research results are also verified via the experiment. The results show that the root-mean-square (RMS) and power-spectral-density of the seat and cab accelerations with the optimal NSS are strongly reduced in comparison without NSS. Especially, the RMS seat's acceleration is markedly attenuated by 67.54% under the vehicle working condition. Therefore, the optimal NSS applied on off-road vehicle's seat suspension could enhance the ride quality.

关键词： soil compactors seat suspension system NSS negative stiffness structure ride quality MOGA multi-objective genetic algorithm off-road terrains

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Design of Axial Flux Permanent Magnet Machine for Miniaturized Integrated Starter–Generator System Applications

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2023年第5期29卷 3265页

作者： Li, Gensheng Xu, Yanliang Zhang, Yun Xu, Fenghui Shandong Univ Sch Elect Engn Jinan 250061 Shandong Peoples R China Shandong Jiaotong Univ Jinan 250357 Shandong Peoples R China Jinan Jimeile Power Technol Co Ltd Jinan 250101 Shandong Peoples R China

This article proposes the design of a miniaturized integrated starter-generator (ISG) system applied to a portable mobile power plant. The system utilizes a single-stator and single-rotor axial flux permanent magnet (PM) machine to meet the demands of light weighting and compaction. The stator adopts fractional slot concentrated winding to save space. The rotor is constructed in segmented PMs, resulting in an 83% reduction in eddy current loss. A quasi-3D magnetic equivalent circuit model is proposed for fast and accurate electromagnetic analysis. By optimizing the initial design using a multi-objective genetic algorithm, the power density of the optimized design reaches 1.23 kW/kg. To handle the axial attraction force, a fixing solution with stepped-shape PMs and aluminum alloy rings is introduced. In addition, the external heat of the engine and the anisotropic heat transfer coefficient of silicon steel are fully considered in computational fluid dynamics. The results show the efficient performance of the designed air-cooled structure. Finally, a prototype is manufactured and tested in the modes of starter and generator. The experimental results validate the prediction of the analytical method and the high performance of the ISG machine.

关键词： Axial flux permanent magnet (AFPM) machine computational fluid dynamics (CFD) integrated starter-generator (ISG) multi-objective genetic algorithm quasi-3D magnetic equivalent circuit (MEC) model

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An Interactive Evaluation Method of Decentralized Procurement Plan by multi-objective genetic algorithm 10

An Interactive Evaluation Method of Decentralized Procuremen...

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10th International Conference on E-Business (ICE-B)

作者： Kobayashi, Ryoji Mori, Masakatsu Samejima, Masaki Komoda, Norihisa Osaka Univ Grad Sch Informat Sci & Technol 2-1 Yamadaoka Suita Osaka Japan Hitachi Ltd Yokohama Res Lab Totsuka Ku Yokohama Kanagawa 2440817 Japan

ISBN: (纸本)9789897581281

This paper addresses evaluation of a decentralized procurement plan for the support of the discussion among decision-makers with considering a catastrophic disaster. For the evaluation of the decentralized procurement plan, we have formulated the decentralized procurement planning problem as 3-objective optimization problem. However, multiple-objective genetic algorithms (MOGA) to solve the problem take several minutes and display many Pareto solutions. We propose the interactive evaluation method of the decentralized procurement plan that is an expanded interactive MOGA (iMOGA) with loss evaluation simulator and solution selection by characteristics of the decentralized procurement plan. Experimental results show that the proposed method can allow the decision-makers to find their preference solutions with 38% fewer interactions than the basic iMOGA can.

关键词： Supply Chain Decentralized Procurement Plan multi-objective genetic algorithm Interactive Evaluation

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