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Long-time integration of parametric evolution equations with physics-informed deeponets

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arXiv 2021年

作者： Wang, Sifan Perdikaris, Paris Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania PhiladelphiaPA19104 United States Department of Mechanichal Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States

Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. In recent years machine learning tools are aspiring to introduce new effective ways of simulating PDEs, however existing approaches are not able to reliably return stable and accurate predictions across long temporal horizons. We aim to address this challenge by introducing an effective framework for learning infinite-dimensional operators that map random initial conditions to associated PDE solutions within a short time interval. Such latent operators can be parametrized by deep neural networks that are trained in an entirely self-supervised manner without requiring any paired input-output observations. Global long-time predictions across a range of initial conditions can be then obtained by iteratively evaluating the trained model using each prediction as the initial condition for the next evaluation step. This introduces a new approach to temporal domain decomposition that is shown to be effective in performing accurate long-time simulations for a wide range of parametric ODE and PDE systems, from wave propagation, to reaction-diffusion dynamics and stiff chemical kinetics, all at a fraction of the computational cost needed by classical numerical solvers. © 2021, CC BY-NC-SA.

关键词： Domain decomposition methods

Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations

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arXiv 2022年

作者： Jin, Peng Huang, Jinfa Liu, Fenglin Wu, Xian Ge, Shen Song, Guoli Clifton, David A. Chen, Jie School of Electronic and Computer Engineering Peking University China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Department of Engineering Science University of Oxford United Kingdom Tencent JARVIS Lab China Oxford-Suzhou Centre for Advanced Research Suzhou China

Most video-and-language representation learning approaches employ contrastive learning, e.g., CLIP [53], to project the video and text features into a common latent space according to the semantic similarities of text-video pairs. However, such learned shared latent spaces are not often optimal, and the modality gap between visual and textual representation can not be fully eliminated. In this paper, we propose Expectation-Maximization Contrastive Learning (EMCL) to learn compact video-and-language representations. Specifically, we use the Expectation-Maximization algorithm to find a compact set of bases for the latent space, where the features could be concisely represented as the linear combinations of these bases. Such feature decomposition of video-and-language representations reduces the rank of the latent space, resulting in increased representing power for the semantics. Extensive experiments on three benchmark text-video retrieval datasets prove that our EMCL can learn more discriminative video-and-language representations than previous methods, and significantly outperform previous state-of-the-art methods across all metrics. More encouragingly, the proposed method can be applied to boost the performance of existing approaches either as a jointly training layer or an out-of-the-box inference module with no extra training, making it easy to be incorporated into any existing methods‡ Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

Temporal networks provide a unifying understanding of the evolution of cooperation

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arXiv 2023年

作者： Li, Aming Meng, Yao Zhou, Lei Masuda, Naoki Wang, Long Center for Systems and Control College of Engineering Peking University Beijing100871 China Center for Multi-Agent Research Institute for Artificial Intelligence Peking University Beijing100871 China School of Automation Beijing Institute of Technology Beijing100081 China Department of Mathematics State University of New York at Buffalo BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260 United States

Understanding the evolution of cooperation in structured populations represented by networks is a problem of long research interest, and a most fundamental and widespread property of social networks related to cooperation phenomena is that the node’s degree (i.e., number of edges connected to the node) is heterogeneously distributed. Previous results indicate that static heterogeneous (i.e., degree-heterogeneous) networks promote cooperation in stationarity compared to static regular (i.e., degree-homogeneous) networks if equilibrium dynamics starting from many cooperators and defectors is employed. However, the above conclusion reverses if we employ non-equilibrium stochastic processes to measure the fixation probability for cooperation, i.e., the probability that a single cooperator successfully invades a population. Here we resolve this conundrum by analyzing the fixation of cooperation on temporal (i.e., time-varying) networks. We theoretically prove and numerically confirm that on both synthetic and empirical networks, contrary to the case of static networks, temporal heterogeneous networks can promote cooperation more than temporal regular networks in terms of the fixation probability of cooperation. Given that the same conclusion is known for the equilibrium fraction of cooperators on temporal networks, the present results provide a unified understanding of the effect of temporal degree heterogeneity on promoting cooperation across two main analytical frameworks, i.e., equilibrium and non-equilibrium ones. Copyright © 2023, The Authors. All rights reserved.

关键词： Heterogeneous networks

Anomalous properties of spark plasma sintered boron nitride solids

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arXiv 2024年

作者： Biswas, Abhijit Serles, Peter Alvarez, Gustavo A. Schimpf, Jesse Hache, Michel Kong, Jonathan Demingos, Pedro Guerra Yuan, Bo Pieshkov, Tymofii S. Li, Chenxi Puthirath, Anand B. Gao, Bin Gray, Tia Zhang, Xiang Murukeshan, Jishnu Vajtai, Robert Dai, Pengcheng Singh, Chandra Veer Howe, Jane Zou, Yu Martin, Lane W. Clancy, James Patrick Tian, Zhiting Filleter, Tobin Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Department of Mechanical & Industrial Engineering University of Toronto 5 King’s College Road TorontoM5S 3G8 Canada Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Department of Materials Science and Engineering University of California Berkeley United States Department of Materials Science and Engineering University of Toronto 184 College St TorontoM5S 3E4 Canada Department of Physics and Astronomy McMaster University HamiltonL8S 4M1 Canada Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Materials Sciences Division Lawrence Berkeley National Laboratory United States

Hexagonal boron nitride (h-BN) is brittle, however, its atomic-scale structural engineering can lead to unprecedented physical properties. Here we report the bulk synthesis of high-density crystalline h-BN solids by using high-temperature spark plasma sintering (SPS) of micron size h-BN powders. In addition to the high mechanical strength and ductile response of such materials, we have obtained anomalous values of dielectric constant beyond theoretical limits, high thermal conductivity, and exceptional neutron radiation shielding capability. Through exhaustive characterizations we reveal that SPS induces non-basal plane crystallinity, twisting of layers, and facilitates inter-grain fusion with a high degree of in-plane alignment across macroscale dimensions, resulting in near-theoretical density and anomalous properties. Our findings highlight the importance of material design, via new approaches such as twisting and interconnections between atomically thin layers, to create novel ceramics with properties that could go beyond their intrinsic theoretical predictions. © 2024, CC BY.

关键词： Spark plasma sintering

On the elastoplastic behavior in collisional compression of spherical dust aggregates

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arXiv 2024年

作者： Arakawa, Sota Tanaka, Hidekazu Kokubo, Eiichiro Okuzumi, Satoshi Tatsuuma, Misako Nishiura, Daisuke Furuichi, Mikito Center for Mathematical Science and Advanced Technology Japan Agency for Marine-Earth Science and Technology 3173-25 Showa-machi Kanazawa-ku Yokohama236-0001 Japan Astronomical Institute Graduate School of Science Tohoku University 6-3 Aramaki Aoba-ku Sendai980-8578 Japan Center for Computational Astrophysics National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Earth and Planetary Sciences Tokyo Institute of Technology 2-12-1 Ookayama Meguro Tokyo152-8550 Japan Interdisciplinary Theoretical and Mathematical Sciences Program RIKEN 2-1 Hirosawa Wako Saitama351-0198 Japan

Aggregates consisting of submicron-sized cohesive dust grains are ubiquitous, and understanding the collisional behavior of dust aggregates is essential. It is known that low-speed collisions of dust aggregates result in either sticking or bouncing, and local and permanent compaction occurs near the contact area upon collision. In this study, we perform numerical simulations of collisions between two aggregates and investigate their compressive behavior. We find that the maximum compression length is proportional to the radius of aggregates and increases with the collision velocity. We also reveal that a theoretical model of contact between two elastoplastic spheres successfully reproduces the size- and velocity-dependence of the maximum compression length observed in our numerical simulations. Our findings on the plastic deformation of aggregates during collisional compression provide a clue to understanding the collisional growth process of aggregates. Copyright © 2024, The Authors. All rights reserved.

关键词： Dust

Multi-core synthesis and maximum satisfiability applied to optimal sizing of solar photovoltaic systems

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TechRxiv

TechRxiv 2021年

作者： Trindade, Alessandro Galvão, Edilson Cordeiro, Lucas The Post-graduate Program in Electrical Engineering Manaus Brazil Department of Electricity Federal University of Amazonas Manaus Brazil School of Computer Science The University of Manchester United Kingdom

Annual global energy consumption growth is around 1.3% with forecasts until 2040. Photovoltaic systems became a suitable alternative to nuclear and fossil energy generation. In order to support this technology’s dissemination, we develop and evaluate an automated formal synthesis approach that assists in decision-making for off-grid systems. Our proposed approach, called PVz, is based on a variant of the counterexample-guided inductive synthesis;it has a multi-core feature, which can obtain the optimal sizing of photovoltaic systems focusing on Life Cycle Cost analysis. Given the electrical needs of a home, we seek a set of electrical equipment with the best possible combination of devices that meet the specified requirements. We calculate all costs related to maintenance over 20 years. The results presented are based on seven case studies;some of them are real ones from the Amazon region in Brazil. The same case studies were solved by a commercial optimization tool. Our technique and the commercial tool results were validated with popular simulation software to perform a fair comparison. Furthermore, we analyze some topics such as run-time, optimal solution, and configuration of the resulting systems. We claim that our technique is advantageous compared to the existing approaches in the literature. © 2021, CC BY-NC-SA.

关键词： Decision making

Quantifying Outdoor Cooling Effects of Vertical Green System on Mean Radiant Temperature

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SSRN

SSRN 2023年

作者： Kim, Eun Sub Yun, Seok Hwan Lee, Dong Kun Kim, Na Youn Piao, Zheng Gang Kim, Sang Hyuck Park, Seunghwan Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Program Seoul National University Seoul08826 Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of Department of Building Energy Research Korea Institute of Civil Engineering and Building Technology Goyang10223 Korea Republic of

Vertical green systems (VGS) are expected to mitigate outdoor heat stress through a transpiration cooling effect. There is a lack of knowledge on how VGS influence outdoor thermal comfort, particularly focusing on energy flux. This study quantifies the outdoor cooling effects of VGS, and distinguishes the energy flux between them and outdoor urban spaces. In addition, we discuss their cooling efficiency. Outdoor experiments were conducted during the hot summer period on building facades in city. Our study on VGS focused on the measurement of climatic variables, surface temperatures of plant leaves (Fatsia japonica), net radiation, and estimating transpiration and evaporation. The surface temperature of VGS were up to 4.3 °C higher than those of high albedo walls, while the reflected radiations (short and long-wave radiation) were 120 w/m2 lower than albedo walls during the day. The mean radiant temperature (MRT) of VGS was 3.02 °C lower than the high albedo wall during daytime, except in the case of shaded areas (0.45 °C). We confirmed that the cooling efficiency of transpiration was 7.38 times more effective than evaporation from soil without plants. Therefore, VGS is efficient in terms of long-term heat reduction and can be an effective strategy to mitigate outdoor heat stress. © 2023, The Authors. All rights reserved.

关键词： Transpiration

Fast PDE-constrained optimization via self-supervised operator learning: A preprint

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arXiv 2021年

作者： Wang, Sifan Bhouri, Mohamed Aziz Perdikaris, Paris Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania PhiladelphiaPA19104 United States Department of Mechanichal Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States

Design and optimal control problems are among the fundamental, ubiquitous tasks we face in science and engineering. In both cases, we aim to represent and optimize an unknown (black-box) function that associates a performance/outcome to a set of controllable variables through an experiment. In cases where the experimental dynamics can be described by partial differential equations (PDEs), such problems can be mathematically translated into PDE-constrained optimization tasks, which quickly become intractable as the number of control variables and the cost of experiments increases. In this work we leverage physics-informed deep operator networks (DeepONets) – a self-supervised framework for learning the solution operator of parametric PDEs – to build fast and differentiable surrogates for rapidly solving PDE-constrained optimization problems, even in the absence of any paired input-output training data. The effectiveness of the proposed framework will be demonstrated across different applications involving continuous functions as control or design variables, including time-dependent optimal control of heat transfer, and drag minimization of obstacles in Stokes flow. In all cases, we observe that DeepONets can minimize high-dimensional cost functionals in a matter of seconds, yielding a significant speed up compared to traditional adjoint PDE solvers that are typically costly and limited to relatively low-dimensional control/design parametrizations. © 2021, CC BY-NC-SA.

关键词： Constrained optimization

In vitro biocompatibility of polycaprolactone/hydroxyapatite nanocomposite membranes modified by oleic acid for bone regeneration

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Colloids and Surfaces A: Physicochemical and engineering Aspects 2024年 688卷

作者： Lin, Ruei-Hong Hung, Huey-Shan Tang, Cheng-Ming Tsou, Hsi-Kai Chen, Po-Hsiang Yueh, Chun-Yu Wang, Hui-Min David Functional Neurosurgery Division Neurological Institute Taichung Veterans General Hospital Taichung40293 Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung40227 Taiwan Translational Medicine Research China Medical University Hospital Taichung404327 Taiwan Graduate Institute of Biomedical Science China Medical University Taichung404333 Taiwan Institute of Oral Sciences Chung Shan Medical University Taichung40201 Taiwan Department of Dentistry Chung Shan Medical University Hospital Taichung40201 Taiwan Functional Neurosurgery Division Neurological Institute Taichung Veterans General Hospital Taichung40293 Taiwan Department of Rehabilitation Jen-Teh Junior College of Medicine Nursing and Management Miaoli County35664 Taiwan College of Health National Taichung University of Science and Technology Taichung403027 Taiwan School of Medicine China Medical University Taichung404333 Taiwan Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung80708 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung40227 Taiwan Department of Medical Laboratory Science and Biotechnology China Medical University Taichung40402 Taiwan

The bone defect is common in the orthopedic clinic, possibly due to trauma, tumor, or congenital diseases. Also, some patients with alveolar bone defects in the dental clinic result from the different proliferation speeds between soft and hard tissue. Biomaterials made of polymers and bioceramics have been developed to deal with these problems but mixing them directly can result in a low-mechanical strength complex. To solve this, we used oleic acid (C18) as a surfactant to improve the dispersity of hydroxyapatite (HA) in the polycaprolactone (PCL) matrix, and then immerse the material in a simulated biomineralization process. The results showed that the low crystallinity PCL formed an evenly distributed mineralized layer that had phosphate ions signal and a hydroxyapatite peak. The biocompatibility of the material was assessed using MC3T3 cells, and found that the PCL-HA membrane and PCL-C18-HA membranes had significant cell filopodia and lamellipodia. Additionally, the polycaprolactone/oleic acid/hydroxyapatite (PCL-C18-HA) membrane had the highest cell viability among all groups. The addition of C18 also decreased the platelets activation degree but had a significant difference in the reactive oxygen species (ROS) amount compared to the control, which requires further investigation. Overall, this study successfully fabricated a safe and promising polycaprolactone/hydroxyapatite/oleic acid nanocomposite membrane as a potential solution for bone biomaterials. © 2024 Elsevier B.V.

关键词： Hydroxyapatite