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Figure Correction of a Quartz Sub-Mirror for a Transmissive Diffractive Segmented Telescope by Reactive Ion Figuring

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IEEE PHOTONICS TECHNOLOGY LETTERS 2022年第21期34卷 1143-1146页

作者： Luo, Qian Li, Zhiwei Wu, Xiang Shao, Junming Fan, Bin Wu, Shibin Du, Junfeng Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Peoples R China

A quartz sub-mirror was figure-corrected in a parallel removal process for the first time. An Reactive Ion Figuring (RIF) process with a simple and universal masking method was demonstrated, and the 350-mm quartz sub-mirror was figure-corrected from the initial figure error of similar to 23 nm RMS to the final figure error of similar to 8 nm RMS in total effective figuring time of similar to 52 minutes after 4 iterations, which exhibited the actual potential of RIF on the figure-correction of quartz optical elements and the possibility on applying RIF to meet the requirement of mass production for sub-mirrors of transmissive diffractive segmented telescopes.

关键词： Reactive ion figuring transmissive diffractive lens figure correction semiconductor industry removal function optimization algorithm

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Machine Learning Surrogates for Optimal 2D Spatial Packaging of Interconnected Systems with Physics Interactions (SPI2)

Machine Learning Surrogates for Optimal 2D Spatial Packaging...

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AIAA Aviation Forum

作者： Parrott, Corey M. Peddadat, Satya R. T. Allison, James T. James, Kai A. Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA Georgia Inst Technol Sch Aerosp Engn Atlanta GA 30332 USA

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

This work proposes new methods and applications of neural networks in automated design optimization for spatial packaging of interconnected systems with physics interactions (SPI2). The experiments are demonstrated on 2D electrothermal systems with heat-generating components connected via fluid-based cooling pipes. We seek to minimize the bounding box area of the system, while accounting for multiple physics and geometric constraints. We train a multilayer perceptron (MLP) on data generated through state-of-the-art physics-based optimization models, constructed with a finite element method (FEM)-based 2D steady state thermal conduction model and a lumped parameter pipe flow model. With the physics-based optimal designs as the ground truth, the model is tasked with mapping various configuration data, including design starting points, and boundary conditions of the physics model to the optimal system layout. Through training the model for this task, the network effectively acts as a surrogate for both physics-driven simulations and numerical optimization. Capable of real-time design synthesis, the MLP exhibits good generalization performance by generating designs that closely match those attained with the iterative physics-based optimization techniques. Relative to the ground truth physics-based designs, our trained surrogate achieves similar to 91% accuracy while performing the same design tasks orders of magnitude faster. Further, we impose loss functions with respect to the geometric constraints of the physics-based model to more consistently produce feasible designs and match the characteristics of the physics data.

关键词： Reinforcement Learning Generative Adversarial Network Design optimization Finite Element Method Steady State Thermal Conduction Pipe Flow Surrogate Model Topology optimization Stochastic Gradient Descent optimization algorithm

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Optimal Energy Storage System Sizing for Peak Shaving in a NU Dormitory Building 15

Optimal Energy Storage System Sizing for Peak Shaving in a N...

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15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Mohamed, Naseef Thanarak, Prapita Ketjoy, Nipon Prasatsap, Unchittha Naresuan Univ Sch Renewable Energy & Smart Grid Technol Phitanulok Thailand

ISBN: (纸本)9798350318104;9798350318098

An optimal battery energy storage system (BESS) capacity was determined using the modified particle swarm optimization (PSO) algorithm for the NU dormitory Building 13. The BESS management strategy uses peak shaving of the electric load profile in the NU dormitory building. As well, the time-of-use tariff (TOU) was considered, and a mathematical model of BESS management was developed. The optimal BESS sizing and the efficient BESS management strategy can efficiently shave the peak load and reduce the overall electricity cost because the peak load power and the energy cost in the on-peak period are diminished. By using peak shaving in the NU dormitory building, the optimal BESS sizing of 26.68 kWh for the increased load factor criteria was determined. When the BESS was operated, the Load factor was improved by 20%, and the peak power consumption was reduced to 25.70 kW.

关键词： Battery energy storage system optimization algorithm BESS Management Peak shaving

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A New Dynamic Optimal M2M RF Interface Setting in Relay Selection algorithm (DORSA) for IoT Applications

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IEEE ACCESS 2022年 10卷 5327-5342页

作者： Ghasri, Monireh Allah Gholi Hemmatyar, Ali Mohammad Afshin Sharif Univ Technol Dept Comp Engn Tehran *** Iran

Machine-to-Machine (M2M) communication is an important type of communication in the Internet-of-Things (IoT). How to send data in these high-density communications using relay selection can help improve the performance of this type of communication in various applications. In addition, the possibility of simultaneous use of different Radio Frequency (RF) interfaces helps to use the spectrum more efficiently. In this work, we try to further use machine communication RF equipment and improve the average data rate of networks in some applications such as the IoT, which have their own bandwidth requirements. Therefore, we provide an optimization algorithm for relay selection as well as the simultaneous and dynamic multiple M2M RF interface setting that is called Dynamic Optimal Relay Selection and RF interfaces Setting algorithm (DORSA). The simulation results show that the average data rate of DORSA with three interfaces (DORSA_W-B-Z) can be improved up to 10% compared to the existing methods such as optimal direct transmission and relay selection algorithms with static RF interface setting.

关键词： Radio frequency Relays Heuristic algorithms Machine-to-machine communications Standards Internet of Things Bipartite graph Machine-to-machine (M2M) communications the Internet of Things (IoT) relay selection dynamic RF interface setting multiple RF interfaces optimization algorithm

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Application of optimization Techniques for Searching Optimal Reservoir Rule Curves: A Review

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WATER 2023年第9期15卷 1669-1669页

作者： Kangrang, Anongrit Prasanchum, Haris Sriworamas, Krit Ashrafi, Seyed Mohammad Hormwichian, Rattana Techarungruengsakul, Rapeepat Ngamsert, Ratsuda Mahasarakham Univ Fac Engn Maha Sarakham 44150 Thailand Rajamangala Univ Technol Isan Fac Engn Khon Kaen Campus Khon Kaen 40000 Thailand Ubon Ratchathani Univ Fac Engn Ubon Ratchathani 34190 Thailand Shahid Chamran Univ Ahvaz Fac Civil Engn & Architecture Dept Civil Engn Ahvaz 61355 Iran

This paper reviews applications of optimization techniques connected with reservoir simulation models to search for optimal rule curves. The literature reporting the search for suitable reservoir rule curves is discussed and examined. The development of optimization techniques for searching processes are investigated by focusing on fitness function and constraints. There are five groups of optimization algorithms that have been applied to find the optimal reservoir rule curves: the trial and error technique with the reservoir simulation model, dynamic programing, heuristic algorithm, swarm algorithm, and evolutionary algorithm. The application of an optimization algorithm with the considered reservoirs is presented by focusing on its efficiency to alleviate downstream flood reduction and drought mitigation, which can be explored by researchers in wider studies. Finally, the appropriate future rule curves that are useful for future conditions are presented by focusing on climate and land use changes as well as the participation of stakeholders. In conclusion, this paper presents the suitable conditions for applying optimization techniques to search for optimal reservoir rule curves to be effectively applied in future reservoir operations.

关键词： optimal reservoir rule curves optimization algorithm climate change reservoir model stakeholder participation

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Coverage Maximization for Heterogeneous Aerial Networks

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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年第1期11卷 91-95页

作者： Zhai, Daosen Shi, Qiqi Zhang, Ruonan Tang, Xiao Cao, Haotong Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Shaanxi Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China

In this letter, we investigate the network planning of the heterogeneous aerial networks to maximize the network coverage. Specifically, a joint high-altitude aerial base station (HABS) trajectory and low-altitude aerial base station (LABS) position optimization problem is formulated with the objective to maximize the number of covered users. Based on the feature of the air-to-ground channel, we first obtain the optimal altitude of the LABSs through the bisection method. Then, we propose a joint particle-and-fish swarm algorithm to optimize the horizontal position of the LABS. For the uncovered users, we model the user coverage probability in the HABS and devise a random interval contraction based algorithm to optimize the flying radius of the HABS. Simulation results indicate that our algorithms can fully exploit the mobility of the heterogeneous aerial networks to cover more users.

关键词： optimization Unmanned aerial vehicles Base stations Wireless networks Particle swarm optimization NOMA High frequency Aerial networks unmanned aerial vehicle network coverage optimization algorithm

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Research on Comprehensive Evaluation Method of New Energy Consumption Capability and Design of Simulation Computing Architecture 3rd

Research on Comprehensive Evaluation Method of New Energy Co...

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3rd International Symposium on New Energy and Electrical Technology (ISNEET)

作者： Geng, Hongbin Zhang, Yingjie Wei, Yanfei Mao, Chenxu Xing, Zhitong State Grid Dezhou Power Supply Co Dezhou 253000 Shandong Peoples R China

ISBN: (纸本)9789819905553;9789819905539;9789819905522

With the construction of a new power system and the implementation of China's clean energy strategic goals, the installed capacity of domestic new energy has grown rapidly. This will lead to the increasingly prominent problem of new energy consumption in regional power grids. Therefore, it is urgent to carry out a comprehensive assessment of the new energy consumption capacity in combination with the actual characteristics of the regional power grid, and to establish a simulation computing architecture. To this end, this paper firstly affects the key factors of new energy power generation and consumption capacity, and establishes optimization objectives and constraints. On this basis, this paper proposes a simulation computing architecture design scheme, and finally carries out a comprehensive analysis of the factors affecting the cost of new energy consumption in combination with a certain regional power grid. The numerical example verifies the effectiveness of the scheme, and can provide a basis for the evaluation and optimization of the new energy consumption capacity under the new situation.

关键词： New energy consumption capacity Comprehensive evaluation optimization algorithm Simulation modeling Cost estimation

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Instance segmentation based precise object detection in UAV Images using Mask R-CNN

International Journal of Systematic Innovation

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International Journal of Systematic Innovation 2023年第6期7卷 12-19页

作者： Kumar, R. Senthil Barnwal, Rajesh P. Department of Computer Science with Cognitive Systems Dr. N.G.P. Arts and Science College Coimbatore India Information Technology Group CSIR-Central Mechanical Engineering Research Institute Durgapur India

Object detection plays a vital role in remote-sensing datasets which trains the image or things and helps in classifying the images into their classes. Instance segmentation is the avant-garde technique used for object detection in Deep Learning. There are many instance segmentation models which can produce significant results. Object detection, segmentation, and RGB analysis in images taken from Unmanned Aerial Vehicles (UAV) are difficult with the desired level of performance. Instance segmentation is a powerful method that extracts each object and its location with the predicted label for pixels in the input image. In this paper, a study has been carried out on the implementation of Mask R-CNN for instance segmentation with different optimization algorithms to obtain a more accurate result for UAV images. The training has been carried out with Mask R-CNN for object detection using ResNet50 and ResNet101 as the backbone. After extensive experiments, it has been observed that the optimization algorithm plays a vital role in the overall computational process and can improve the accuracy level with a reduction in the training/validation loss. The experiment has been conducted on publicly available UAV datasets. The paper further presents the results in terms of different performance parameters © 2023, International Journal of Systematic Innovation. All Rights Reserved.

关键词： Deep learning Instance Segmentation Mask R-CNN optimization algorithm UAV Images

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Optimal Control of Active Suspension Considering Mitigating Motion Sickness in Automated Vehicles 62

Optimal Control of Active Suspension Considering Mitigating ...

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62nd Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE)

作者： Zhao, Haohan Kang, Mingxin Zhang, Yahui Yanshan Univ Dept Mech Engn Qinhuangdao Hebei Peoples R China Ningbo Univ Technol Ningbo Peoples R China

ISBN: (纸本)9784907764807

The safety and comfort of autonomous vehicles are currently important research directions. As an evaluation indicator of vehicle comfort during driving, how to reduce the probability of motion sickness among passengers inside the vehicle has become a key research topic in the field of autonomous vehicles. This article proposes a novel method that considers the vertical stability of the vehicle and reduces the incidence of carsickness based on the active suspension of the vehicle. Active suspension, as a core part of the vehicle chassis-by-wire, plays a role in reducing ground roughness excitation and enhancing vehicle handling stability. Firstly, a dynamic model of the vehicle's active suspension was established based on the actual vehicle, and then an adaptive fuzzy PID algorithm was designed to optimize the performance indicators of the active suspension, such as body acceleration and suspension dynamic deflection. A quantitative model of the motion sickness mechanism was also established. By comparing different algorithms, it is shown that the proposed method can more effectively reduce the incidence of motion sickness among passengers in the vehicle. This control method can effectively improve vehicle comfort and contribute to the promotion and application of autonomous vehicles.

关键词： Active suspension Motion sickness Fuzzy PID control optimization algorithm Road excitation

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Reusing Cardboard for Packaging Boxes with a Computational Design System 36

Reusing Cardboard for Packaging Boxes with a Computational D...

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36th Annual ACM Symposium on User Interface Software and Technology (UIST)

作者： Koyama, Kazuki Narumi, Koya Takaki, Ken Kawase, Yasushi Hautasaari, Ari Kawahara, Yoshihiro Univ Tokyo Tokyo Japan

ISBN: (纸本)9798400700965

We propose a computational design system for packaging boxes, which enables reconstruction of cardboard into packaging structures that precisely fit the size of the objects to be shipped. Given a 3D model of the object and the structure of the cardboard to be reused, our system suggests the optimal net of a new box, which only requires minimum cuts and folds for fabrication by leveraging the edges of the input cardboard. To achieve this, we implemented a GUI visualizing the input models and the optimal net computed by our optimization algorithm. As a demonstration, we showed three design examples, with evaluation results of our method for reducing the length of cuts and folds.

关键词： personal fabrication daily object reuse optimization algorithm sustainable fabrication sharing economy

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