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Surrogate-based aerodynamic shape optimization of high-speed train heads: A review of four key technologies

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT 2024年第8期238卷 907-920页

作者： Wang, Hongbo Wang, Shuangbu Zhuang, Dayuan Zhu, Zaiping You, Pengcheng Tang, Zhao Ding, Guofu Southwest Jiaotong Univ Sch Mech Engn Chengdu Peoples R China Southwest Jiaotong Univ Inst Smart City & Intelligent Transportat 999 Xian Rd Chengdu 611756 Peoples R China Southwest Jiaotong Univ State Key Lab Rail Transit Vehicle Syst Chengdu Peoples R China Bournemouth Univ Natl Ctr Comp Animat Poole England

With the increase in running speed, the aerodynamic characteristics of high-speed trains have a significant impact on running stability, energy consumption and passenger comfort. Since the shape of the high-speed train head can directly influence the surrounding airflow, optimizing the head shape is the primary way to improve the aerodynamic performance of the train. This paper reviews current research studies on the surrogate-based aerodynamic shape optimization of high-speed train heads, aiming to provide a comprehensive reference for designers to enhance design efficiency and optimization performance. The entire optimization process is divided into four essential steps, and the key optimization technologies in each step are discussed, including parametric modeling, computational fluid dynamics (CFD) simulation, surrogate model and optimization algorithm. By introducing the practical applications of these technologies, we summarize their advantages and disadvantages and suggest four potential research directions for the future.

关键词： High-speed train shape optimization parametric modeling computational fluid dynamics simulation surrogate model optimization algorithm

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An Improved Hybrid optimization algorithm based on Iteration for Solving Aeroengine Model

An Improved Hybrid Optimization Algorithm based on Iteration...

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2015 International Conference on Artificial Intelligence and Industrial Engineering(AIIE 2015)

作者： D.W.Yin R.Y.Lv B.Chang Naval Academy of Armament

ISBN: (纸本)9781510806450

The solution algorithm of the aeroengine nonlinear model is a classic problem, which is relatively mature in theory. But this question is still studied today, because the mathematical character of the aeroengine nonlinear model is so complex, that it is difficult to be convergent using the traditional iteration algorithm. So an idea is proposed to solve this problem, which is conversing the model solution to an optimization problem, and using optimization algorithms to solve the difficulties. In order to ensure the calculation speed, the iteration optimization method is chosen, and a new improved hybrid iteration optimization methods is design. In order to verify the improved algorithm, the simulation experiment was carried out taking an given turbofan engine as an example. The simulation results shows that, the solution precision is improved in some degree, when the new algorithm is used.

关键词： Aeroengine nonlinear equations iteration optimization algorithm

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CCHP-Type Micro-Grid Scheduling optimization Based on Improved Multi-Objective Grey Wolf Optimizer

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Energy Engineering 2025年第3期122卷 1137-1151页

作者： Yu Zhang Sheng Wang Fanming Zeng Yijie Lin College of Mechanical and Control Engineering Guilin University of TechnologyGuilin541006China

With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm *** reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy *** proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local *** the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable ***,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and *** analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to ***,it enhances user satisfaction and ensures the stable operation of the micro-grid.

关键词： Multi-objective optimization algorithm hybrid energy storage micro-grid CCHP

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Analysis of Various Visual Cryptographic Techniques and Their Issues Based on optimization algorithms

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INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS 2023年第6期23卷 2350059-2350059页

作者： Sajitha, A. S. Sridevi Sathya Priya, S. Karunya Inst Technol & Sci Elect & Commun Engn Coimbatore 641114 Tamil Nadu India Nehru Coll Engn & Res Ctr Near Lakkidi Rly Stn Thiruvilwamala 680588 Kerala India

Visual Cryptography (VC) is a process employed for the maintenance of secret information by hiding the secret messages that are embedded within the images. Typically, an image is partitioned into a number of shares that are stacked over one another in order to reconstruct back the original image accurately. The major limitation that existed in the traditional VC techniques is pixel expansion, in which pixel expansion is replaced with a number of sub-pixels in individual share, which causes a considerable impact on the contrast and resolution of the image that further gradually decreases the quality of the image. VC is named for its essential characteristics, such as transmitting the images with two or more shares with an equal number of black pixels and color pixel distribution. The secret message can be decrypted using Human Visual System (HVS). In this paper, 50 research papers are reviewed based on various classification algorithms, which are effectively used for the VC technique. The classification algorithms are categorized into three types, namely, meta-heuristic, heuristic, and evolutionary, and the research issues and challenges confronted by the existing techniques are reported in this survey. Moreover, the analysis is done based on the existing research works by considering the classification algorithms, tools, and evaluation metrics.

关键词： Visual cryptography encryption decryption secret image share optimization algorithm

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Low-Thrust Trajectory optimization with Averaged Dynamics Using Analytical Switching Detection

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第6期47卷 1135-1149页

作者： Wu, Di Cheng, Lin Gong, Shengping Baoyin, Hexi Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China Beihang Univ Sch Astronaut Beihang 102206 Peoples R China

This paper presents an efficient indirect optimization method for the time- and fuel-optimal low-thrust many-revolution transfers with averaged dynamics. Compared with the previous indirect method, the proposed method involves a new set of variables and several near-optimal control laws to formulate the two-point boundary value problem based on three practical assumptions. Then, the costate transformations between two reference frames are first derived with respect to the the corresponding Eulerian angles, such that the switching function can be expressed with a six-degree polynomial function and the number of parameters used to determine the energy-optimal solutions is reduced to 6. Finally, a neural network is trained to generated the initial guesses, and the solution algorithms for solving the time- and fuel-optimal problem are formulated. Numerical simulations demonstrate that the convergence ratio of initial guesses is higher than 98%, the proposed assumptions are reasonable for guaranteeing the near optimality, and the presented method can obtain convergent solutions within tenths of a second for the Earth- and moon-centered external/interior transfers considering the shadow J2 and third-body perturbations.

关键词： Pontryagin's Maximum Principle Solar System Moons Planets algorithms and Data Structures Artificial Neural Network Boundary Element Method Numerical Simulation optimization algorithm Propellant Geostationary Transfer Orbit

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Designing radiative cooling metamaterials for passive thermal management by particle swarm optimization

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Chinese Physics B 2023年第5期32卷 37-42页

作者：闫申申刘岩王子兰晓华汪毅任捷 Center for Phononics and Thermal Energy Science China-EU Joint Laboratory on NanophononicsShanghai Key Laboratory of Special Artificial Microstructure Materials and TechnologySchool of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China

The passive radiative cooling technology shows a great potential application on reducing the enormous global energy *** multilayer metamaterials could enhance the radiative cooling ***,it is a challenge to design the radiative *** this work,based on the particle swarm optimization(PSO)evolutionary algorithm,we develop an intelligent workflow in designing photonic radiative cooling ***,we design two 10-layer SiO_(2) radiative coolers doped by cylindrical MgF_(2) or air impurities,possessing high emissivity within the selective(8–13μm)and broadband(8–25μm)atmospheric transparency windows,*** two kinds of coolers demonstrate power density as high as 119 W/m^(2) and 132 W/m^(2) at the room temperature(300 K).Our scheme does not rely on the usage of special materials,forming high-performing metamaterials with conventional poor-performing *** significant improvement of the emission spectra proves the effectiveness of our inverse design algorithm in boosting the discovery of high-performing functional metamaterials.

关键词： photonic devices passive radiative cooling metamaterial optimization algorithm

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Reliability-based design optimization: a state-of-the-art review of its methodologies, applications, and challenges

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STRUCTURAL AND MULTIDISCIPLINARY optimization 2024年第9期67卷 168页

作者： Hu, Weifei Cheng, Sichuang Yan, Jiquan Cheng, Jin Peng, Xiang Cho, Hyunkyoo Lee, Ikjin Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310058 Peoples R China Zhejiang Univ Innovat Ctr Yangtze River Delta Jiaxing 314100 Peoples R China Zhejiang Univ Sch Mech Engn Hangzhou 310058 Peoples R China Zhejiang Univ Technol Coll Mech Engn Hangzhou 310023 Peoples R China Mokpo Natl Univ Dept Mech Engn Muan Gun 58554 Jeollanam Do South Korea Korea Adv Inst Sci & Technol Mech Engn Dept Daejeon 34141 South Korea

Reliability-based design optimization (RBDO) integrates various uncertainties into the design optimization process, offering a more realistic and robust approach compared to traditional deterministic design optimization methods. Thus, RBDO has emerged as a highly compelling and vital research direction within the design field. However, there is currently a dearth of comprehensive reviews on RBDO methodologies presented in a clear and concise manner. This paper aims to address this gap by providing a state-of-the-art review of RBDO methodologies across four key aspects: performance function evaluation, reliability analysis, optimization strategies and algorithms, and RBDO applications in five typical engineering fields. The paper commences by presenting basic RBDO formulations and providing an overall picture of various RBDO methodologies. Subsequently, performance function evaluation methodologies are explained and then categorized into three groups: physics-based performance function evaluation, data-driven performance function evaluation, and physics-informed performance function evaluation. Following this, two types of reliability analysis methodologies are introduced: time-independent reliability analysis and time-dependent reliability analysis. The review also delves into the realm of optimization strategies, with a comprehensive examination of three types: double-loop strategy, single-loop strategy, and decoupling strategy. Moreover, two types of optimization algorithms, the gradient-based algorithm and the meta-heuristic algorithm, are extensively surveyed. Each is scrutinized in terms of their specific methods, advantages, and disadvantages. In addition to methodological exploration, the paper scrutinizes RBDO applications in five engineering fields: wind engineering, aeronautical engineering, ocean engineering, bridge engineering, and vehicle engineering. These applications are carefully surveyed regarding the various uncertainties encountered, the methods

关键词： Reliability-based design optimization Uncertainty Performance function evaluation Reliability analysis optimization algorithm optimization strategy Engineering applications

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optimization algorithms for energy storage integrated microgrid performance enhancement

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JOURNAL OF ENERGY STORAGE 2021年 43卷

作者： Roslan, M. F. Hannan, M. A. Ker, P. J. Muttaqi, K. M. Mahlia, T. M., I Univ Tenaga Nas Dept Elect Power Engn Kajang 43000 Malaysia Univ Tenaga Nas Inst Sustainable Energy Kajang 43000 Malaysia Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia Univ Technol Sydney Sch Informat Syst & Modelling Ultimo NSW 2007 Australia

Distributed energy resource (DER) in microgrid has emerged significant challenges in the existing centralized energy management systems. This is due to the stochastic energy sources integrated into microgrid and dynamic power demand that has brought difficulties in controlling the optimal output power. An inefficient and without optimally controlled DERs and charge/discharge of energy storage system results in high operating cost to consumers as well as decrease a lifetime of energy storage based microgrid. Therefore, to solve the issues, a dayahead optimized scheduling controller-based novel lightning search algorithm (LSA) technique is introduced to provide an optimum power delivery with minimum cost including optimum use of energy storage. The main objective of the proposed controller is to develop an optimized controller for the microgrid to minimize the operating cost of DER and optimal operation of charge/discharge of the energy storage system. The optimized controller's effectiveness is executed in a 14-bus test system based on a real load varying conditions recorded in Perlis, Malaysia for 24-hours' operation. The obtained results show that the performance of the optimized controller for energy storage-based microgrid successfully reduced the amount of power consumption which in turn saving the energy and cost of 62.5%. The proposed day-ahead optimized scheduling controller outperforms the backtracking search algorithm and particle swarm optimization techniques in terms of iteration (53.56) and time consumption (2915.2 min) which in turn validate the controller performance. Thus, the developed optimized controller can realize the effectiveness of energy storage integrated MG energy management with the optimum operation of DER units.

关键词： Microgrids optimization algorithm Energy management Scheduling controller Distributed energy resources

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Hierarchical Framework for Space Exploration Campaign Schedule optimization

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JOURNAL OF SPACECRAFT AND ROCKETS 2024年第5期61卷 1146-1164页

作者： Gollins, Nicholas Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

Space exploration plans are becoming increasingly complex as public agencies and private companies target deep-space locations, such as cislunar space and beyond, which require long-duration missions and many supporting systems and payloads. Optimizing multimission exploration campaigns is challenging due to the large number of required launches as well as their sequencing and compatibility requirements, making conventional space logistics formulations unscalable. To tackle this challenge, this paper proposes an alternative approach that leverages a two-level hierarchical optimization algorithm: an evolutionary algorithm is used to explore the campaign scheduling solution space, and each of the solutions is then evaluated using a time-expanded multicommodity flow mixed-integer linear program. A number of case studies, focusing on the Artemis lunar exploration program, demonstrate how the method can be used to analyze potential campaign architectures. The method enables a potential mission planner to study the sensitivity of a campaign to program-level parameters such as logistics vehicle availability and performance, payload launch windows, and in situ resource utilization infrastructure efficiency.

关键词： Space Exploration and Technology optimization algorithm Space Logistics Models Lunar Exploration Mixed Integer Linear Programming Evolutionary algorithm Propellant Mass Fraction Multi Objective Genetic algorithm

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Comparison of two optimization algorithms (VOLO™, SEQU) for CyberKnife® treatment of acoustic neuromas, lung metastases, and liver metastases

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JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS 2023年第12期24卷 e14144页

作者： Thiele, Martin Galonske, Kirsten Ernst, Iris German CyberKnife Ctr Soest Germany German Ctr Stereotaxy & Precis Irradiat Soest Germany German CyberKnife Ctr Senator Schwartz Ring 8 D-59494 Soest Germany

Introduction: Two optimization algorithms VOLO (TM) and sequential optimization algorithm (SEQU) are compared in the Precision (R) treatment planning system from Accuray (R) for stereotactic radiosurgery and stereotactic body radiotherapy (SBRT) treatment plans. The aim is to compare the two algorithms to assess if VOLO (TM) is better of SEQU in certain treatment site. Materials and Methods: Sixty clinical treatment cases were compared. Entities include Acoustic neuroma (AN), lung metastases, and liver metastases. In each entity, 10 SEQU and 10 VOLO (TM) T treatment plans were optimized. The Ray-Tracing calculation algorithm was used for all treatment plans and the treatments were planned exclusively with fixed cones (5-50 mm). The number of nodes, beams, total MU, and treatment time were compared. Conformity index (CI), new conformity index (nCI), homogeneity index (HI), gradient index (GI), and target coverage were examined for agreement. D-min, D-mean, D-max, D100%, D98%, and D2% dose in the target volume as well as exposure to organs at risk was checked. To determine peripheral doses, the isodose volumes from V10% to V98% were evaluated. Results: AN treatment plans showed significant differences for the number of nodes, beams, total MU, treatment time, D98%, D100% for the target volume, and the doses for all organs at risk. VOLO (TM) achieved better results on average. TotalMU, treatment time, coverage, and D98% are significantly better for VOLO (TM) for lung metastases. For liver metastases, a significant reduction in number of nodes, total MU, and treatment time was observed for VOLO (TM) plans. The mean target coverage increased slightly with VOLO (TM), while the mean CI deteriorated slightly. The averages of Dmin, Dmean, D98%, D100%, and V80% resulted in a significant increase for VOLO (TM). Conclusion: The results of the present study indicate that VOLO (TM) should be used in place of SEQU as a standard for AN cases moving forward. Despite the lack of signi

关键词： CyberKnife & REG SRS SBRT optimization algorithm

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