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Hopping-Transport Mechanism for Reconfigurable Logic in Disordered Dopant Networks

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Physical Review Applied 2022年第6期17卷 064025-064025页

作者： Henri Tertilt Jesse Bakker Marlon Becker Bram de Wilde Indrek Klanberg Bernard J. Geurts Wilfred G. van der Wiel Andreas Heuer Peter A. Bobbert Institut für physikalische Chemie Westfälische Wilhelms-Universität Münster Münster Germany NanoElectronics Group University of Twente Enschede Netherlands Multiscale Modeling and Simulation Group Faculty of Electrical Engineering Mathematics and Computer Science MESA+ Institute for Nanotechnology and Center for Brain-Inspired Nano Systems (BRAINS) University of Twente Enschede Netherlands Center for Computational Energy Research (CCER) Eindhoven University of Technology Netherlands Fachbereich Physik Westfälische Wilhelms-Universität Münster Münster Germany Department of Applied Physics Eindhoven University of Technology Netherlands

We present an atomic-scale mechanism based on variable-range hopping of interacting charges enabling reconfigurable logic in dopant network processing units. Kinetic Monte Carlo simulations of the hopping process show temperature-dependent current-voltage characteristics and artificially evolved basic Boolean logic gates in very good agreement with experiment. The simulations provide unique insights into the local electrostatic potential and current flow in the dopant network, showing subtle changes induced by control voltages that set the conditions for the logic operation. These insights will be crucial in the systematic further development of this burgeoning technology for unconventional computing. The establishment of the principles underlying the logic functionality of these devices encourages the exploration and utilization of the same principles in other materials and device geometries.

关键词： Doping effects Hopping transport Neuromorphic computing Devices for digital logic, storage & processing Disordered systems Doped semiconductors Genetic algorithm Monte Carlo methods

Finite cell method for functionally graded materials based on V-models and homogenized microstructures

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Advanced modeling and simulation in engineering Sciences 2020年第1期7卷 1-33页

作者： Wassermann, Benjamin Korshunova, Nina Kollmannsberger, Stefan Rank, Ernst Elber, Gershon Chair for Computation in Engineering Technical University of Munich Arcisstr. 21 München 80333 Germany Chair of Computational Modeling and Simulation Technical University of Munich Arcisstr. 21 München 80333 Germany Institute for Advanced Study Technical University of Munich Lichtenbergstr. 2a Garching 85748 Germany Center for Graphics and Geometric Computing Technion Israel Institute of Technology Haifa 3200003 Israel

This paper proposes an extension of the finite cell method (FCM) to V-rep models, a novel geometric framework for volumetric representations. This combination of an embedded domain approach (FCM) and a new modeling framework (V-rep) forms the basis for an efficient and accurate simulation of mechanical artifacts, which are not only characterized by complex shapes but also by their non-standard interior structure. These types of objects gain more and more interest in the context of the new design opportunities opened by additive manufacturing, in particular when graded or micro-structured material is applied. Two different types of functionally graded materials (FGM) are considered: The first one, multi-material FGM is described using the inherent property of V-rep models to assign different properties throughout the interior of a domain. The second, single-material FGM—which is heterogeneously micro-structured—characterizes the effective material behavior of representative volume elements by homogenization and performs large-scale simulations using the embedded domain approach. © 2020, The Author(s).

关键词： Additive manufacturing Direct simulation Finite cell method Functionally Ggraded material Homogenization V-models V-reps

Polyconvex anisotropic hyperelasticity with neural networks

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arXiv 2021年

作者： Klein, Dominik K. Fernández, Mauricio Martin, Robert J. Neff, Patrizio Weeger, Oliver Cyber-Physical Simulation Group Department of Mechanical Engineering Centre for Computational Engineering Technical University of Darmstadt Dolivostr. 15 Darmstadt64293 Germany Access e.V. Intzestr. 5 Aachen52072 Germany Chair for Nonlinear Analysis and Modeling Faculty of Mathematics University of Duisburg-Essen Thea-Leymann-Str. 9 Essen45127 Germany

In the present work, two machine learning based constitutive models for finite deformations are proposed. Using input convex neural networks, the models are hyperelastic, anisotropic and fulfill the polyconvexity condition, which implies ellipticity and thus ensures material stability. The first constitutive model is based on a set of polyconvex, anisotropic and objective invariants. The second approach is formulated in terms of the deformation gradient, its cofactor and determinant, uses group symmetrization to fulfill the material symmetry condition, and data augmentation to fulfill objectivity approximately. The extension of the dataset for the data augmentation approach is based on mechanical considerations and does not require additional experimental or simulation data. The models are calibrated with highly challenging simulation data of cubic lattice metamaterials, including finite deformations and lattice instabilities. A moderate amount of calibration data is used, based on deformations which are commonly applied in experimental investigations. While the invariant-based model shows drawbacks for several deformation modes, the model based on the deformation gradient alone is able to reproduce and predict the effective material behavior very well and exhibits excellent generalization capabilities. In addition, the models are calibrated with transversely isotropic data, generated with an analytical polyconvex potential. For this case, both models show excellent results, demonstrating the straightforward applicability of the polyconvex neural network constitutive models to other symmetry groups. © 2021, CC BY-NC-ND.

关键词： Machine learning

Vesicle shape deformation using a discontinuous Galerkin method 6

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Vesicle shape deformation using a discontinuous Galerkin met...

6th ECCOMAS European Conference on computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th ECCOMAS European Conference on computational Fluid Dynamics, ECFD 2018

作者： Kim, Tae-Yeon Jiang, Wen Lee, Sung Mun Song, Jeong-Hoon Park, Eun-Jae Civil Infrastructure and Environmental Engineering Khalifa University of Science and Technology Abu Dhabi127788 United Arab Emirates Fuels Modeling and Simulation Idaho National Laboratory Idaho FallsID83415 United States Department of Biomedical Engineering Khalifa University of Science and Technology Abu Dhabi127788 United Arab Emirates Department of Civil Environmental and Architectural Engineering University of Colorado at Boulder BoulderCO80309 United States Department of Computational Science and Engineering Yonsei University Seoul03722 Korea Republic of

ISBN: (纸本)9788494731167

This work concerns the development of a finite-element algorithm to discretize the phase-field model for the shape deformation of a vesicle based on the idea of discontinuous Galerkin method. The phase-field model originated from minimization of Canham-Helfrich elastic bending energy involves fourth-order gradients and thus C1-basis functions are required for the standard conforming Galerkin formulation. We introduce a relatively inexpensive, nonconforming method based on C0-basis functions. We present the variational form of the method including additional terms to weakly enforce continuity of the derivatives across interelement boundaries and its stabilization is achieved via Nitsche's method. Numerical tests for the equilibrium shape of a single component vesicle are performed to demonstrate the performance of the proposed variational formulation. copyright © Crown copyright (2018).All right reserved.

关键词： Galerkin methods

The impact of AI on engineering design procedures for dynamical systems

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arXiv 2024年

作者： de Payrebrune, Kristin M. Flaßkamp, Kathrin Ströhla, Tom Sattel, Thomas Bestle, Dieter Röder, Benedict Eberhard, Peter Peitz, Sebastian Stoffel, Marcus Rutwik, Gulakala Aditya, Borse Wohlleben, Meike Sextro, Walter Raff, Maximilian Remy, C. David Yadav, Manish Stender, Merten van Delden, Jan Lüddecke, Timo Langer, Sabine C. Schultz, Julius Blech, Christopher RPTU Kaiserslautern-Landau Institute for Computational Physics in Engneering Gottlieb-Daimler-Straße 74 Kaiserslautern67663 Germany Saarland University Systems Engineering Systems Modeling and Simulation Campus Saarbrücken66123 Germany TU Ilmenau Mechatronics group Max-Planck-Ring 12 Ilmenau98693 Germany Brandenburg University of Technology Cottbus-Senftenberg Chair of Engineering Mechanics and Vehicle Dynamics Siemens-Halske-Ring 14 Cottbus03046 Germany University of Stuttgart Institute of Engineering and Computational Mechanics Pfaffenwaldring 9 Stuttgart70569 Germany TU Dortmund Department of Computer Science & Lamarr Institute Joseph-von-Fraunhofer-Str. 25 Dortmund44227 Germany RWTH Aachen University Institute of General Mechanics Eilfschornsteinstraße 18 Aachen52062 Germany Paderborn University Faculty of Mechanical Engineering Dynamics and Mechatronics Warburger Str. 100 Paderborn33098 Germany University of Stuttgart Institute for Nonlinear Mechanics Pfaffenwaldring 9 Stuttgart70569 Germany Technische Universität Berlin Chair of Cyber-Physical Systems in Mechanical Engineering Straße des 17. Juni 135 Berlin10623 Germany University of Göttingen Institute of Informatics Goldschmidtstr. 7 Göttingen37077 Germany Technische Universität Braunschweig Institute for Acoustics and Dynamics Langer Kamp 19 Braunschweig38106 Germany

Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The development of mechatronic systems is undergoing a similar transformation. Over the past decade, modeling, simulation, and optimization techniques have become integral to the design process, paving the way for the adoption of AI-based methods. In this paper, we examine the potential for integrating AI into the engineering design process, using the V-model from the VDI guideline 2206, considered the state-of-the-art in product design, as a foundation. We identify and classify AI methods based on their suitability for specific stages within the engineering product design workflow. Furthermore, we present a series of application examples where AI-assisted design has been successfully implemented by the authors. These examples, drawn from research projects within the DFG Priority Program SPP 2353: Daring More Intelligence - Design Assistants in Mechanics and Dynamics, showcase a diverse range of applications across mechanics and mechatronics, including areas such as acoustics and robotics. © 2024, CC BY.

关键词： Mechatronics

Theoretical insights into the chemical bonding, electronic structure, and spectroscopic properties of the lanarkite Pb2SO5 structure

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arXiv 2023年

作者： Fabris, Guilherme S.L. Ferrer, Mateus M. Sambrano, Julio R. Almeida, Cláudio R.R. Paskocimas, Carlos A. La Porta, Felipe A. Graduate Program in Materials Science and Engineering Technological Development Center Universidade Federal de Pelotas RS Pelotas96010-610 Brazil Modeling and Molecular Simulation Group São Paulo State University Bauru São Paulo17033-360 Brazil Department of Materials Engineering Federal University of Rio Grande do Norte RN Natal59078-970 Brazil Postgraduate Program in Science and Engineering of Materials Federal University of Rio Grande do Norte RN Natal59078-970 Brazil Federal University of Technology - Paraná Nanotechnology and Computational Chemistry Laboratory Avenida dos Pioneiros 3131 CEP PR Londrina86036-370 Brazil State University of Londrina Post-Graduation Program in Chemistry Rodovia Celso Garcia Cid 445 km 380 CEP PR Londrina86057-970 Brazil

Lanarkite is a mineral formed by a combination of lead, sulphur, and oxygen atoms arranged in the general chemical formula Pb2SO5 (PSO) that crystallises with monoclinic symmetry (belonging to the C2/m space group, No. 12). This mineral was first discovered in Lanarkshire, Scotland and was named after its location. PSO has a unique structure comprising alternating penta-coordinated lead [PbO5] and tetra-coordinated sulphur [SO4] clusters. This lanarkite-type structure has recently attracted significant scientific interest and has been the focus of the superconducting material research community. However, its chemistry needs to be explored further. This article presents a comprehensive investigation on the chemical bonding, electronic structure, and spectroscopic properties of the lanarkite-type PSO structure from a computational perspective. Thus, different functionals in the DFT (e.g., PBE, PBE0, PBESOL, PBESOL0, BLYP, WC1LYP37, and B3LYP) were assessed to accurately predict their fundamental properties. All the DFT calculations were performed using a triple-zeta valence plus polarisation basis set. Among all the DFT functionals tested in this study, PBE showed the best agreement with the experimental data available in the literature. Our results also reveal that the [PbO5] clusters are formed with three Pb–O bond lengths, with values of about 2.32, 2.59, and 2.84 Å, respectively, while the [SO4] clusters have the same S–O bond length of 1.57 Å. We performed a complete topological analysis of this system to comprehend these structural differences. Additionally, the PSO structure has an indirect band gap energy of 2.9 eV and an effective mass ratio (mℎ∗ /me∗) of about 0.415 (using PBE calculations) which may, in principle, indicate a low recombination of electron-hole pairs in the lanarkite structure. Therefore, we believe that a detailed understanding of their electronic structures, spectroscopic properties as well as their chemical bonding is critically important

关键词： Lead compounds

A BIM-Based Framework to Visually Evaluate Circularity and Life Cycle Cost of buildings.

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A BIM-Based Framework to Visually Evaluate Circularity and L...

Central Europe towards Sustainable Building 2019, CESB 2019

作者： Di Biccari, C. Abualdenien, J. Borrmann, A. Corallo, A. Department of Innovation Engineering University of Salento Edificio Aldo Romano Campus Ecotekne Lecce73100 Italy Department of Computational Modeling and Simulation Department of Civil Geo and Environmental Engineering Technical University of Munich Arcistrasse 21 Munich80333 Germany

The Circular Economy paradigm seeks to shift products and systems from linear to "closed loop" life cycles applying specific business models and strategies to their designs and lifelines. The implementation of the circular economy in buildings depends on the efforts made by all the stakeholder involved in the life cycle of a building, where it can draw most of the benefits if the application of a circular business model is planned during the design phases. Building Information Modelling is an approach that helps designers in creating and managing semantically rich 3D-models describing the status of the building over its life cycle. In this paper, a BIM-based framework for evaluating the application of circular business models of buildings from the circularity and the life cycle cost points of views is proposed. © Published under licence by IOP Publishing Ltd.

关键词： Life cycle

Fluorine intercalated graphene: Formation of a 2D spin lattice through pseudoatomization

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arXiv 2020年

作者： Mishra, Shashi B. Yadav, Satyesh K. Kanhere, D.G. Nanda, B.R.K. Condensed Matter Theory and Computational Lab Department of Physics IIT Madras Chennai India Department of Metallurgy and Materials Engineering IIT Madras Chennai India Centre for Modeling and Simulation Savitribai Phule Pune University Pune India

A suspended layer made up of ferromagnetically ordered spins could be created between two mono/multilayer graphene through intercalation. Stability and electronic structure studies show that, when fluorine molecules are intercalated between two mono/multilayer graphene, their bonds get stretched enough (∼ 1.9−2.0 Å) to weaken their molecular singlet eigenstate. Geometrically, these stretched molecules form a pseudoatomized fluorine layer by maintaining a van der Waals separation of ∼ 2.6 Å from the adjacent carbon layers. As there is a significant charge transfer from the adjacent carbon layers to the fluorine layers, a mixture of triplet and doublet states stabilize to induce local spin-moments at each fluorine sites and in turn form a suspended 2D spin lattice. The spins of this lattice align ferromagnetically with nearest neighbour coupling strength as large as ∼ 100 meV. Our finite temperature ab initio molecular dynamics study reveals that the intercalated system can be stabilized up to a temperature of 100 K with an average magnetic moment of ∼ 0.6 µB/F. However, if the graphene layers can be held fixed, the room temperature stability of such a system is feasible. Copyright © 2020, The Authors. All rights reserved.

关键词： Fluorine

Image-based numerical characterization and experimental validation of tensile behavior of octet-truss lattice structures

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arXiv 2020年

作者： Korshunova, Nina Alaimo, Gianluca Hosseini, Seyyed Bahram Carraturo, Massimo Reali, Alessandro Niiranen, Jarkko Auricchio, Ferdinando Rank, Ernst Kollmannsberger, Stefan Chair of Computational Modeling and Simulation Technische Universität München Germany Department of Civil Engineering and Architecture University of Pavia Italy Department of Civil Engineering Aalto University Finland Institute for Advanced Study Technische Universität München Germany

The production of lightweight metal lattice structures has received much attention due to the recent developments in additive manufacturing (AM). The design flexibility comes, however, with the complexity of the underlying physics. In fact, metal additive manufacturing introduces process-induced geometrical defects that mainly result in deviations of the effective geometry from the nominal one. This change in the final printed shape is the primary cause of the gap between the as-designed and as-manufactured mechanical behavior of AM products. Thus, the possibility to incorporate the precise manufactured geometries into the computational analysis is crucial for the quality and performance assessment of the final parts. Computed tomography (CT) is an accurate method for the acquisition of the manufactured shape. However, it is often not feasible to integrate the CT-based geometrical information into the traditional computational analysis due to the complexity of the meshing procedure for such high-resolution geometrical models and the prohibitive numerical costs. In this work, an embedded numerical framework is applied to efficiently simulate and compare the mechanical behavior of as-designed to as-manufactured octet-truss lattice structures. The parts are produced using laser powder bed fusion (LPBF). Employing an immersed boundary method, namely the Finite Cell Method (FCM), we perform direct numerical simulations (DNS) and first-order numerical homogenization analysis of a tensile test for a 3D printed octet-truss structure. Numerical results based on CT scan (as-manufactured geometry) show an excellent agreement with experimental measurements, whereas both DNS and first-order numerical homogenization performed directly on the 3D virtual model (as-designed geometry) of the structure show a significant deviation from experimental data. © 2020, CC BY-NC-ND.

关键词： 3D printers