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In-memory Parallel Anisotropic Mesh Adaptation for Hypersonic Problems with Evolving Geometry

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In-memory Parallel Anisotropic Mesh Adaptation for Hypersoni...

AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Gica, Mikiel Woodruff, Aiden Brown, Cameron S. Salazar, Giovanni Sahni, Onkar Department of Mechanical Aerospace and Nuclear Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Department of Computer Science Rensselaer Polytechnic Institute TroyNY12180 United States Corvid Technologies MooresvilleNC28117 United States

ISBN: (纸本)9781624107238

In this paper, we present an automated workflow for in-memory parallel anisotropic mesh adaptation for hypersonic problems with evolving geometry. Our workflow develops and combines three simulation components to target such problems. Namely, a hypersonic flow solver;a library for geometry and mesh modification/adaptation;and an adaptation controller. Our approach is component based, in which different simulation components are combined and plugged in a flexible and modular fashion. Specifically, adaptation controller abstracts the data exchange between the geometry and mesh library and the flow solver, and defines a set of functional interfaces to carry out the necessary logic and data exchange. This paper builds on our previous studies and includes a flexible approach for evolving geometry problems to allow geometry and mesh motion to be applied in the flow solver (without any change in mesh connectivity). Updated coordinates are communicated from the flow solver to the geometry and mesh library, only when mesh modification/adaptation is triggered. A mesh size field (based on mesh metric tensors) is computed and used to drive anisotropic mesh adaptation. For demonstration of the current approach, two hypersonic flow cases with rigid body motion are considered: (i) a pitching HIFiRE-I case, and (ii) a pitching crew exploration vehicle case without and with the wake region. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Mesh generation

Latte++: Spatial-Temporal Voxel-based Test-Time Adaptation for Multi-Modal Segmentation

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arXiv 2024年

作者： Cao, Haozhi Xu, Yuecong Yin, Pengyu Ji, Xingyu Yuan, Shenghai Yang, Jianfei Xie, Lihua Nanyang Technological University Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore School of Electrical and Electronic Engineering School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore

Multi-modal test-time adaptation (MM-TTA) is proposed to adapt models to an unlabeled target domain by leveraging the complementary multi-modal inputs in an online manner. Previous MM-TTA methods for 3D segmentation rely on predictions of cross-modal information in each input frame, while they ignore the fact that predictions of geometric neighborhoods within consecutive frames are highly correlated, leading to unstable predictions across time. To fulfill this gap, we propose ReLiable Spatial-temporal Voxels (Latte), an MM-TTA method that leverages reliable cross-modal spatial-temporal correspondences for multi-modal 3D segmentation. Motivated by the fact that reliable predictions should be consistent with their spatial-temporal correspondences, Latte aggregates consecutive frames in a sliding-window manner and constructs Spatial-Temporal (ST) voxels to capture temporally local prediction consistency for each modality. After filtering out ST voxels with high ST entropy, Latte conducts cross-modal learning for each point and pixel by attending to those with reliable and consistent predictions among both spatial and temporal neighborhoods. Considering the prediction consistency might vary under different sliding windows, we further propose Latte++ which leverages ST voxels generated under various sliding windows to more thoroughly evaluate intra-modal prediction consistency before the cross-modal fusion. Experimental results show that both Latte and Latte++ achieve state-of-the-art performance on five MM-TTA benchmarks compared to previous MM-TTA or TTA methods. Code will be available at https://***/AronCao49/Latte-plusplus. © 2024, CC BY-SA.

关键词： Semantic Segmentation

DIFFUSOLVE: DIFFUSION-BASED SOLVER FOR NON-CONVEX TRAJECTORY OPTIMIZATION

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arXiv 2024年

作者： Li, Anjian Ding, Zihan Dieng, Adji Bousso Beeson, Ryne Department of Electrical and Computer Engineering Princeton University United States Department of Computer Science Princeton University United States Vertaix United States Department of Mechanical and Aerospace Engineering Princeton University United States

Optimal trajectory design is computationally expensive for nonlinear and high-dimensional dynamical systems. The challenge arises from the non-convex nature of the optimization problem with multiple local optima, which usually requires a global search. Traditional numerical solvers struggle to find diverse solutions efficiently without appropriate initial guesses. In this paper, we introduce DiffuSolve, a general diffusion model-based solver for non-convex trajectory optimization. An expressive diffusion model is trained on pre-collected locally optimal solutions and efficiently samples initial guesses, which then warm-starts numerical solvers to fine-tune the feasibility and optimality. We also present DiffuSolve+, a novel constrained diffusion model with an additional loss in training that further reduces the problem constraint violations of diffusion samples. Experimental evaluations on three tasks verify the improved robustness, diversity, and a 2× to 11× increase in computational efficiency with our proposed method, which generalizes well to trajectory optimization problems of varying challenges. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

Adaptive-Sliding Mode Trajectory Control of Robot Manipulators with Uncertainties

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arXiv 2024年

作者： Mustafa, Mustafa M. Crane, Carl D. Hamarash, Ibrahim Department of Electrical Engineering College of Engineering Salahaddin University-Erbil Kurdistan Region Iraq Department of Computer Science and Engineering University of Kurdistan Hewler Iraq Department of Mechanical and Aerospace Engineering University of Florida FL United States

In this paper, we propose and demonstrate an adaptive-sliding mode control for trajectory tracking control of robot manipulators subjected to uncertain dynamics, vibration disturbance, and payload variation disturbance. Throughout this work we seek a controller that is, robust to the uncertainty and disturbance, accurate, and implementable. To perform these requirements, we use a nonlinear Lyapunov-based approach for designing the controller and guaranteeing its stability. MATLAB-SIMULINK software is used to validate the approach and demonstrate the performance of the controller. Simulation results show that the derived controller is stable, robust to the disturbance and uncertainties, accurate, and implementable. Copyright © 2024, The Authors. All rights reserved.

关键词： MATLAB

Convex Optimization in Legged Robots

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arXiv 2023年

作者： Saraf, Prathamesh Shaikh, Mustafa Phan, Myron Department of Electrical and Computer Engineering Department of Mechanical and Aerospace Engineering University of California - San Diego United States

Convex optimization is crucial in controlling legged robots, where stability and optimal control are vital. Many control problems can be formulated as convex optimization problems, with a convex cost function and constraints capturing system dynamics. Our review focuses on active balancing problems and presents a general framework for formulating them as second-order cone programming (SOCP) for robustness and efficiency with existing interior point algorithms. We then discuss some prior work around the Zero Moment Point stability criterion, Linear Quadratic Regulator Control, and then the feedback model predictive control (MPC) approach to improve prediction accuracy and reduce computational costs. Finally, these techniques are applied to stabilize the robot for jumping and landing tasks. Further research in convex optimization of legged robots can have a significant societal impact. It can lead to improved gait planning and active balancing which enhances their ability to navigate complex environments, assist in search and rescue operations and perform tasks in hazardous environments. These advancements have the potential to revolutionize industries and help humans in daily life. © 2023, CC BY.

关键词： Model predictive control

Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

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Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao Liang Weiwei Li Congwei Liao Shunyu Jin Chuan Liu Kai Wang Shengdong Zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical Engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China State Key Laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and Information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical Engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang University International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time of<110 ms under exertion of dynamic stimuli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

Performance of Adaptive Neuro-Fuzzy Inference System State-of-Charge Estimation of Lithium-Ion Batteries for Electric Ship 8

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Performance of Adaptive Neuro-Fuzzy Inference System State-o...

8th International Conference on Computational Intelligence and Applications, ICCIA 2023

作者： Marisno, Denny Chin, Cheng Siong Shan, Chunlai See, Simon Newcastle University in Singapore Faculty of Science Agriculture Engineering Singapore Northwest Institute of Mechanical and Electrical Engineering Simulation and Test Technology Department Xianyang China Shanghai Jiao Tong University 800 Dongchuan RD. Minhang District Department of Computer Science and Engineering Shanghai200240 China

ISBN: (纸本)9798350339741

Estimating the State of Charge (SoC) is a crucial part of a battery management system (BMS) for the electric ship. An Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the SoC using the ANFIS under different ambient temperature variations is proposed. A five-layer Artificial Neural Network for SoC estimation is used. The ANFIS achieves the lowest prediction error compared to the Neural Network, electrical circuit model, coulomb counting, Kalman Filter, Fuzzy Neural Network, and Support Vector Machine method. © 2023 IEEE.

关键词： Battery management systems

Single-input single-output multi-touch soft sensor systems using band-pass filters

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npj Flexible Electronics 2022年第1期6卷 681-690页

作者： Junhyung Kim Suhan Kim Yong-Lae Park Department of Mechanical Engineering Institute of Advanced Machines and DesignInstitute of Engineering ResearchSeoul National UniversitySeoul 08826Republic of Korea Department of Electrical Engineering and Computer Science Research Laboratory of ElectronicsMassachusetts Institute of Technology77 Massachusetts AvenueCambridgeMA 02139USA

In many soft sensor systems,external wires for connecting the sensors to control circuits have posed practical problems,in terms of compact form factors and physical *** study proposes a design of soft sensor arrays that can operate with a drastically reduced number of wires without degrading the original *** proposed concept is an array of soft sensing modules,each of which consists of an inductor and a capacitor embedded next to the resistive sensing module,constructing a resistorinductor-capacitor band-pass *** adjusting the values of the capacitance and the inductance,unique frequency band is assigned to each sensing module,enabling the distinctive detection using only two external wires regardless of the number of *** multi-touch sensing functionality of the system is analytically modeled and experimentally *** advantage of the design,a fingertip tactile sensor and an insole foot pressure sensor are demonstrated as practical applications.

关键词： connecting constructing touch

Environmental Sound Classification Based on Multi-channel Features and Hybrid Attention 17

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Environmental Sound Classification Based on Multi-channel Fe...

17th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2024

作者： Liu, Guishan Zhou, Shuai Peng, Zhangjun Li, Li School of Computer Science and Technology Southwest University of Science and Technology Sichuan Mianyang621000 China College of Mechanical and Electrical Engineering Sichuan Electronic Machinery Vocational and Technical College Sichuan Mianyang621000 China Sichuan Autonomous Controllable Artificial Intelligence Engineering Technology Center Sichuan Mianyang621000 China

ISBN: (纸本)9798331507398

Environmental sound classification (ESC) is an important research direction, but it remains challenging due to the wide variety of environmental sounds which are difficult to uniformly represent and can be easily interfered by noise. The ESC has limitations in accurately separating and recognizing sounds in multi-class complex scenarios, especially under conditions of noise interference or overlapping sound sources. To improve the accuracy of ESC recognition, this paper proposes a classification method that utilizes a multi-channel feature and a mixed attention model. Firstly, the time-level and frequency-domain signals of the ESC are extracted, and filters are applied to extract spectral features and reconstruct into a feature graph. The limitations of single-feature representation are addressed by leveraging the complementarity between the three-channel features. Secondly, a hybrid classification model composed of channel and time-frequency concentration module classification model is introduced. The channel attention model calculates the feature map and assigns weights to different channels, and the channel features with more effective information and better resolution of this kind of sound can be allocated more weights. The time-frequency concentration module, however, focuses on more effective information in the time domain and frequency domain. The method proposed in this paper can effectively suppress the background noise, eliminate redundancy, and improve the convergence speed and classification accuracy. The recognition accuracies on ESC-10 and ESC-50 datasets reach 96.25% and 89.56% respectively, and 98.40% on the Urbansound8k dataset. © 2024 IEEE.

关键词： Frequency domain analysis