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simulation and Derivative Analysis of Operation Effect of Electricity Spot Market 3

Simulation and Derivative Analysis of Operation Effect of El...

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2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： Tang, Yao Xiao, Yanwei Wang, Gaoqin Power Automation Department China Electric Power Research Institute China Zhejiang Electric Power Corporation China

Under the background of global power market reform, the construction of China's electricity spot market is a hot spot in China. In order to ensure the safe and stable operation of the power system, it is necessary to carry out detailed simulation before the reform. In this paper, a simulation platform is developed to fit the characteristics of the spot market, and a set of evaluation indexes that can be used to quantify the market operation effect is designed. Based on the data of typical summer and winter load days in an area of East China, the operation of the spot market is simulated. The results show that the index can reasonably evaluate the operation effect of the market in a variety of scenarios. © Published under licence by IOP Publishing Ltd.

关键词： simulation platform

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A Novel Quantitative Adhesion Measurement Method for Thin Polymer and Metal Layers for Microelectronic applications 72

A Novel Quantitative Adhesion Measurement Method for Thin Po...

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72nd IEEE Electronic Components and Technology conference (ECTC)

作者： Woehrmann, Markus Mackowiak, Piotr Schiffer, Michael Lang, Klaus-Dieter Schneider-Ramelow, Martin Fraunhofer Inst Reliabil & Microintegrat Dept WLSI Berlin Germany Tech Univ Berlin Berlin Germany

ISBN: (纸本)9781665479431

Advancements in packaging technologies like Fan-Out demand for a higher integration density with an increased number of RIM. layers as well as novel low-k layers as interlayer dielectric. The adhesion of these layers becomes an important factor for the reliability of the packaging because an enforcement by mechanical bond is limited. This work presents a novel test method (Stripe Lift-Off Test -SLT) for the adhesion characterization of thin film layers used in RDL for Fan-In and Fan-Out. The method is based on a modified edge lift-off test (mELT) concept. A polymer layer under high tensile stress is used to force a delamination of a layer stack. A critical energy release rate (J/m(2)) leading to a delamination can be estimated based on the known biaxial stress in the stressing polymer. The usage of residual stress in a layer stack for driving a delamination avoids any additional clamping, gluing of additional layers or the demand of special adhesion measurement equipment. The quantified adhesion test can he integrated in any RIM, production line since only coating equipment is needed as well as a dicing tool for sample generation. The sample generation complexity can be scaled regarding the purpose of the adhesion measurement - ranging from a quick, rough estimation and adhesion value evaluation in a production process to a precise prediction of the energy release rate that can he used as a basis for packaging simulation. The established mELT for the quantification of the interface's fracture toughness is limited by the fact that it is running at negative temperatures. The novelty of the SLT is a stress polymer layer with a modifiable stress state which allows the adhesion measurement at room temperature. The stress state can be tailored to investigate the delamination at a certain temperature related to the application. FE-modeling of the SLT in ANSYS is presented and these results are compared to the analytical energy release rate estimation of the SLT. These veri

关键词： fracture toughness adhesion measurement RDL reliability strain energy energy release rate mELT FEM SLT

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Towards Quantum simulations of Lithium Diffusion in Solid State Electrolytes for Battery applications

Towards Quantum Simulations of Lithium Diffusion in Solid St...

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Quantum Computing and Engineering (QCE), IEEE international conference on

作者： Dario Rocca Matthias Loipersberger Jérôme F. Gonthier Robert M. Parrish Jisook Hong Byeol Kang Chanshin Park Hong Woo Lee QC Ware Corporation Palo Alto California USA POSCO Holdings Pohang Republic of Korea

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Advancing battery materials is crucial for sustainable infrastructure, EVs and renewable energy storage. By achieving polynomial scaling for exact electronic structure simulations of materials, quantum computing could emerge as an invaluable tool in this field. In this work, we address two fundamental aspects related to the application of quantum algorithms to lithium diffusion in solid state electrolytes, which have the potential to significantly improve safety and performance of current battery technologies. First of all, we discuss the need for the higher level of accuracy provided by quantum computing. Classical computational methods routinely applied to compute the properties of solid state electrolytes are based on semi-local approximations of density functional theory (DFT). Considering cluster models representative of the properties of the bulk Li 10 GeP 2 S 12 (LGPS) electrolyte, we benchmark several functionals, including state-of-the-art hybrid approximations and compare the results to high-level wavefunction methods. The classical results for lithium diffusion barriers exhibit a variability exceeding the chemical accuracy threshold required for experimentally relevant precision, underscoring the necessity for exact quantum solutions as a reference. Secondly, we perform quantum simulations for lithium diffusion barriers using small active spaces of the cluster models and use those results to extrapolate the minimal resources required for a full simulation of bulk LGPS. Specifically, the variational quantum eigensolver (VQE) with a quantum number preserving ansatz and the quantum Krylov (qK) method are considered. The resource estimations for VQE show that a few hundred qubits and less than one million two-qubit gates could be sufficient to simulate LGPS. For qK the number of required two-qubit gates increases by orders of magnitude. However, for large models it should also be considered that qK avoids the complex non-linear optimization problem inv

关键词： Solid modeling Accuracy Quantum algorithm Computational modeling Discrete Fourier transforms Logic gates Lithium Electrolytes Optimization Quantum simulation

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Model-Free Predictive Control for PMSM Incorporating Flux-weakening

Model-Free Predictive Control for PMSM Incorporating Flux-we...

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international (EPE-PEMC) Power Electronics and Motion Control conference

作者： Masoumeh Ahrabi Subarni Pradhan Babak Nahid-Mobarakeh McMaster Automotive Resource Centre McMaster University Hamilton Canada

ISBN: (数字)9798350385236

ISBN: (纸本)9798350385243

In recent years, permanent magnet synchronous motors (PMSMs) have gained significant attention across various industrial sectors, particularly in transportation, owing to their distinct advantages over alternative motor technologies. Notably, PMSMs exhibit higher power density and possess the potential for wide flux weakening operation, thereby extending the speed range of operation—a critical attribute in electric vehicle applications. However, the sensitivity of PMSM control approaches to variations in machine parameters presents a notable challenge, as it can lead to degradation in controller performance when discrepancies arise between modeled parameters and real-world conditions. Addressing this concern, this study introduces a model-free adaptation of finite control set (FCS) predictive control (FCS-MFPC) tailored for flux weakening (FW) operation. Through simulation analysis conducted over the US Environmental Protection Agency Urban Dynamometer Driving Schedule, the performance of this controller is examined. Additionally, the performance of the controller is compared to conventional FCS-MPC. To facilitate a comprehensive comparison, criteria such as reference tracking error and drive efficiency are considered.

关键词： Adaptation models Schedules Torque Sensitivity Predictive models Electric vehicles Dynamometers Vehicle dynamics Predictive control Context modeling

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modeling and Control for Spacecraft Hovering Considering J2∼j4Perturbation 3

Modeling and Control for Spacecraft Hovering Considering J2...

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2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： Zhang, Liang Ge, Peiqi School of Mechanical Engineering Shandong University Jinan China Key Laboratory of High Efficiency and Clean Mechanical Manufacture Shandong University Ministry of Education Jinan China

In this paper, the required control with the J 2∼J 4 perturbation is derived for the spacecraft hovering. The J 2∼J 4 perturbation is introduced into spacecraft relative motion model by Gauss's variation equations, and the orbit elements affected by the J 2∼J 4 perturbation are obtained. Combining the nonlinear relative motion model of the spacecraft with the obtained orbit elements, the analytic expression of the hovering control is completely derived. The numerical verification results indicate that the derived control considering the J 2∼J 4 perturbation can ensure the high accuracy for the spacecraft hovering. © Published under licence by IOP Publishing Ltd.

关键词： Spacecraft

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Machine learning for reduced-order modeling of composites processing

Machine learning for reduced-order modeling of composites pr...

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SAMPE 2021 conference and Exhibition

作者： Kim, Min Zobeiry, Navid Materials Science & Engineering University of Washington SeattleWA United States

ISBN: (纸本)9781934551394

Machine learning concepts have made their way into industry practice and can offer quick and accurate solutions for various design and in-service applications including process simulation of composites. High-fidelity finite element simulation tools are currently used for thermo-chemical analysis of parts during processing. This research investigates reduced-order modeling of complex composite parts using machine learning methods to speed-up the simulation. At first, process simulations of representative 2-D stringer geometries were conducted using finite element analysis to extract leading and lagging responses. Equivalency of exothermic responses of 2-D simulations to 1-D finite element analysis was established using an in-house developed machine learning framework at the University of Washington (CompML). It is demonstrated that for a given 2-D geometry, a trained NN can identify an equivalent 1-D thermal stack to yield similar exothermic responses. The results and methods developed in this study can significantly reduce the computational cost of finite element simulation by successfully establishing reduced-order models of complex geometries. © 2021 Soc. for the Advancement of Material and Process Engineering. All rights reserved.

关键词： Finite element method

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Morphogenesis of Images using Neural Cellular Automata

Morphogenesis of Images using Neural Cellular Automata

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international conference on Computing and Networking Technology (ICCNT)

作者： Samarth Tumdi Dev Patel Daksh Dholakia Aaditya Patel Pradnya Saval Department of Computer Science & Engineering (Data Science) Dwarkadas J. Sanghvi College of Engineering Mumbai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The examination of image morphogenesis, an intricate phenomenon characterized by the gradual metamorphosis of visual representations, stands as the central focus of this scholarly investigation. Within this context, the research endeavor delves deeply into the complex interplay between Neural Cellular Automata (NCA) and Deep Neural Networks (CRNN). An integral component of this inquiry revolves around the enhancement of the training procedure by incorporating a composite loss function, notably the Huber Loss. Moreover, the study is enriched by the extensive utilization of the Noto Color Emoji collection, which encompasses a vast array of over 2500 emojis meticulously classified into various geometrical forms such as “Circular,” “Bilateral,” and “Asymmetrical.” These diverse emojis function as stand-in for in-real-life images with a more complex color palette. At the core of this research lies the fundamental NCA system with the integrated loss modification, showcasing a remarkable ability to initiate developmental processes from a given seed pixel as compared to the original system. Through thorough experimentation and systematic analysis, the effects of both balanced and unbalanced stimuli on the regenerative capacity of the system were meticulously scrutinized. In the pursuit of broadening the horizons of image manipulation methodologies, a comprehensive evaluation framework was adopted to rigorously assess the performance of the modified model. This framework places emphasis on key metrics, particularly growth and regeneration, with the goal of surpassing the initial outcomes and establishing new standards in the realm of image morphogenesis research. By establishing interdisciplinary connections between developmental biology and computer science, this research not only advances the comprehension of image morphogenesis but also unlocks novel avenues for practical applications. These discoveries carry significant implications across various domains, spanning from

关键词： Training Visualization Systematics Satellites Image color analysis Self-organizing networks Security modeling Standards Emojis

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Design and simulation of an Efficient Memristor Based Multiplier Using Hybird Logic

Design and Simulation of an Efficient Memristor Based Multip...

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Smart technologies, Communication and Robotics (STCR)

作者： K.Paramasivam K. Paramasivam R.Nithya A.Jayashree S.Aneesh R. Vijay Department of Electrical and Electronics Engineering Kumaraguru College of Technology Tamilnadu India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350357530

ISBN: (纸本)9798350357547

The scalability and power inefficiency concerns related to conventional CMOS technology are taken up in this work, which improves the design for high-performance memristor-based digital circuits. This research proposes alternative arithmetic circuit implementations, including half adders, full adders, 2-bit multipliers, and 3-bit multipliers, using the HP memristor's nanosecond-scale switching speeds, non-volatility, and CMOS compatibility. These circuits, containing experimentally verified HP memristor models with exact current-voltage (I-V) characteristics, were developed and simulated using MATLAB and LTspice. Considering the memristor's sudden resistive switching and low-energy state transitions, the results show significant increases in power efficiency (up to 45% reduction) and operational speed (30% faster switching) compared to CMOS equivalents. The HP memristor's more accurate Ron/Roff ratios and endurance are highlighted in a comparative analysis, demonstrating its suitability for hybrid memristor-CMOS designs [1]. Stable hysteresis curves are shown by transient simulations under different bias conditions and dielectric thicknesses, and resilience against process variations and thermal impacts is confirmed. This study gives vital insights into hybrid system optimization by bridging the gap between theoretical models and real-world implementation with the addition of experimental I-V data from constructed HP memristors. The outcomes depend on the groundwork for memory systems and flexible, energy-efficient arithmetic logic units (ALUs), with implications for beyond-CMOS applications and neuromorphic computing.

关键词： Semiconductor device modeling Resistance Computational modeling Memristors Voltage CMOS technology Logic Adders Switching circuits Arithmetic

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RobotDrlSim: A Real Time Robot simulation Platform for Reinforcement Learning and Human Interactive Demonstration Learning 3

RobotDrlSim: A Real Time Robot Simulation Platform for Reinf...

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2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： Sun, Te Gong, Liang Li, Xvdong Xie, Shenghan Chen, Zhaorun Hu, Qizi Filliat, David School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China Computer Science and System Engineering Department and Inria Flowers Team Ensta Institut Polytechnique Paris Palaiseau France

Deep reinforcement learning (DRL) techniques give robotics research an AI boost in many applications. In order to simultaneously accommodate the complex robotic behaviour simulation and DRL algorithm verification, a new simulation platform, namely the RobotDrlSim, is proposed. First, we design a standardized API interfacing mechanism for coordinating diverse environments on RobotDrlSim platform, where PyBullet simulator is equipped with an API to form a physical engine for robotics simulation. Second, benchmark DRL models are included in the baseline library for evaluation. Third, real-Time human-robot interactions can be captured and imported to drive the RobotDrlSim tasks, which provide big data-stream for reinforcement learning. Experimentations show that cutting-edge DRL algorithms developed in python can be seamlessly deployed to the robots, and human interactions can be availed in training the robots. RobotDrlSim is valid for efficiently developing DRL algorithms for artificial intelligence models of robots, and it is especially suitable for the robot educational purposes. © Published under licence by IOP Publishing Ltd.

关键词： simulation platform

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Enhanced LDA with SVM and Ensemble Learning for Advanced ADL Classification Using Smartwatch Data

Enhanced LDA with SVM and Ensemble Learning for Advanced ADL...

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international conference on Automation and Computing (ICAC)

作者： Mustafa Elhadi Ahmed Hongnian Yu Michael Vassallo Pelagia Koufaki Center for Health Activiy and Rehabilitation Research Queen Margaret University Edinburgh UK School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK Department of Medicine for Older People Royal Bournemouth Hospital Bournemouth UK

ISBN: (数字)9798350360882

ISBN: (纸本)9798350360899

The demographic shift towards an older population introduces significant challenges for healthcare, necessitating advancements in predictive, dynamic care models. Central to this transformation are Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs), which are crucial for evaluating an individual's functional status. This study leverages Machine Learning (ML) with smartwatch technology for continuous, non-intrusive monitoring of ADLs /IADLs. By integrating Support Vector Machine (SVM) and Ensemble Learning (EL) with enhanced Linear Discriminant Analysis (LDA), we aim to accurately classify a broad spectrum of daily activities. Data from 30 participants, captured through a smartwatch, underwent analysis to assess these methodologies' efficacy in real-life applications. Results indicate that LDA enhanced classification accuracy, with EL models demonstrating superior performance in recognizing complex activities—achieving over 90% accuracy. The study also examines the hardware performance of these models, noting variations in RAM usage, inference times, CPU usage, and network sizes. EL models, especially when coupled with LDA, offer an optimal balance between computational demands and classification precision. This investigation underlines the potential of integrating sophisticated data processing techniques with wearable technologies for health monitoring, presenting a viable approach to overcoming real-life deployment challenges and advancing personalized healthcare for the aging demographic.

关键词： Support vector machines Wearable Health Monitoring Systems Accuracy Computational modeling Random access memory Medical services Predictive models Linear discriminant analysis Ensemble learning Monitoring

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