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SSRN 2024年

作者： Calcagni, Maria Teresa Salerno, Giovanni Martarelli, Milena Schlenger, Jonas Urs Hassan, Thomas Heinikainen, Rene Borrmann, André Fies, Bruno Revel, Gian Marco Department of Industrial Engineering and Mathematical Sciences Università Politecnica delle Marche Via Brecce Bianche 12 Ancona60131 Italy Computational Modeling and Simulation Technical University of Munich Arcisstraße 21 München80333 Germany Orange Rue Olivier de Serres 78 Paris75015 France Fira Group Oy Teknobulevardi 3-5 Vantaa01530 Finland Centre Scientifique et Technique du Batiment Avenue Jean Jaures 84 Champs sur Marne77420 France

Ensuring the durability of civil buildings is critical to preventing long-term structural failure. Traditional damage assessment methods, based on visual inspections, are labor-intensive and subjective. The adoption of Digital Building Twin (DBT) platforms emerges as a solution for comprehensive monitoring of the building throughout its life cycle. This study, part of the European BIM2TWIN project, focuses on concrete surface quality monitoring using vision techniques and deep learning algorithms. Four neural network models are created for cracks, honeycombing, pitting and exposed bars, collectively analyzing the images to identify and quantify defects. Project managers can assess the criticality of defects based on accurate pixel counts and geometric features, converting measurements from pixels to millimeters. The data are then stored in the DBT platform, providing a historical record for future reference and decision-making by project managers. © 2024, The Authors. All rights reserved.

关键词： Pixels

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Wearable Sensor Gait Analysis of Fall Detection using Attention Network

Wearable Sensor Gait Analysis of Fall Detection using Attent...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Haben Yhdego Jiang Li Christopher Paolini Michel Audette Computational Modeling and Simulation Engineering Old Dominion University Norfolk USA Electrical and Computer Engineering Old Dominion University Norfolk USA Electrical and Computer Engineering San Diego State University San Diego California

ISBN: (纸本)9781665429825

The statistical data from the National Council on Aging indicates that a senior adult dies in the US from a fall every 19 minutes. The care of elderly people can be improved by enabling the detection of falling events, especially if it triggers the pneumatic actuation of a protective airbag. This work focuses on detecting impending fall risk of senior subjects within the geriatric population, towards a planned approach to mitigating fall injuries through pneumatic airbag deployment. With the widespread adoption of wearable sensors, there is an increased emphasis on fall prediction models that effectively cope with accelerometry signal data. Fall detection and gait classification are challenging tasks, especially in differentiating falls from near falls. We propose to apply attention to the deep neural network (DNN) analysis of acceleration data where a fall is known to have occurred. We take the maximum value of the sensor signals to define the observation window of the detector. Powered by a transformer DNN with word embedding, attention networks have achieved a state-of-the-art in natural language processing (NLP) tasks. Besides the success of the transformer for efficiently processing long sequences, it supports parallel computing with fast computation. In this paper, we propose a novel transformer attention network for gait analysis of fall detection modeling with Time2Vec positional encoding-founded on a Masked Transformer Network. Using our dataset, we demonstrate that the proposed approach achieves better specificity and sensitivity than the present models.

关键词： Sensitivity computational modeling Sociology Transformers Natural language processing Real-time systems Fall detection

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modeling the modeler: An empirical study on how modelers learn to create simulations

Modeling the modeler: An empirical study on how modelers lea...

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2020 Spring simulation Multiconference, SpringSim 2020

作者： Kavak, Hamdi Padilla, Jose Diallo, Saikou Barraco, Anthony Department of Computational and Data Sciences George Mason University 4400 University Dr. FairfaxVA United States Virginia Modeling Analysis and Simulation Center Old Dominion University 1030 University Blvd. SuffolkVA United States

ISBN: (数字)9781565553705

ISBN: (纸本)9781713812883

This paper presents our novel efforts on automatically capturing and analyzing user data from a discrete-event simulation environment. We collected action data such as adding/removing blocks and running a model that enable creating calculated data fields and examining their relations across expertise groups. We found that beginner-level users use more blocks/edges and make more build errors compared to intermediate-level users. When examining the users with higher expertise, we note differences related to time spent in the tool, which could be linked to user engagement. The model running failure of beginner-level users may suggest a trial and error approach to building a model rather than an established process. Our study opens a critical line of inquiry focused on user engagement instead of process establishment, which is the current focus in the community. In addition to these findings, we report other potential uses of such user action data and lessons learned. © 2020 Society for modeling & simulation International (SCS)

关键词： Discrete event simulation

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Enforcing essential boundary conditions on domains defined by point clouds

arXiv

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arXiv 2021年

作者： Hartmann, Frank Kollmannsberger, Stefan Technische Universität München Arcisstr. 21 München80333 Germany Chair of Computational Modeling and Simulation Technische Universität München Arcisstr. 21 München80333 Germany

This paper develops and investigates a new method for the application of Dirichlet boundary conditions for computational models defined by point clouds. Point cloud models often stem from laser or structured-light scanners which are used to scan existing mechanical structures for which CAD models either do not exist or from which the artifact under investigation deviates in shape or topology. Instead of reconstructing a CAD model from point clouds via surface reconstruction and a subsequent boundary conforming mesh generation, a direct analysis without pre-processing is possible using embedded domain finite element methods. These methods use non-boundary conforming meshes which calls for a weak enforcement of Dirichlet boundary conditions. For point cloud based models, Dirichlet boundary conditions are usually imposed using a diffuse interface approach. This leads to a significant computational overhead due to the necessary computation of domain integrals. Additionally, undesired side effects on the gradients of the solution arise which can only be controlled to some extent. This paper develops a new sharp interface approach for point cloud based models which avoids both issues. The computation of domain integrals is circumvented by an implicit approximation of corresponding Voronoi diagrams of higher order and the resulting sharp approximation avoids the side-effects of diffuse approaches. Benchmark examples from the graphics as well as the computational mechanics community are used to verify the algorithm. All algorithms are implemented in the FCMLab framework and provided at https://***/cie_sam_public/fcmlab/. Further, we discuss challenges and limitations of point cloud based analysis w.r.t. application of Dirichlet boundary conditions. © 2021, CC BY.

关键词： Boundary conditions

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A generic and density-sensitive method for multi-scale pedestrian dynamics

arXiv

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arXiv 2020年

作者： Biedermann, Daniel H. Clever, Jan Borrmann, André Chair of Computational Modeling and Simulation Technische Universität München Arcisstrasse 21 München80333 Germany

Microscopic approaches to the simulation of pedestrian dynamics rely on modelling the behaviour of individual agents and their mutual interactions. Regarding the spatial resolution, microscopic simulators are either based on continuous (SpaceCont) or discrete (SpaceDisc) approaches. To combine the advantages of both approaches, we propose to integrate SpaceCont and SpaceDisc into a hybrid simulation model. Such a hybrid approach allows simulating critical regions with a continuous spatial resolution and uncritical ones with discrete spatial resolution while enabling consistent information exchange between the two simulation models. We introduce a generic approach that provides consistent solutions for the challenges resulting from coupling diverging time steps and spatial resolutions. Furthermore, we present a dynamic and density-sensitive approach to detect dense areas during the simulation run. If a critical region is detected, the simulation model used in this area is dynamically switched to a space-continuous one. The correctness of the hybrid model is evaluated by comparison with a established simulator. Its superior computational efficiency is shown by runtime comparison with a standard microscopic *** with the simulation results of other, well-established simulation models. © 2020, CC BY-NC-ND.

关键词： Image resolution

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Ab initio phonon transport across grain boundaries in graphene using machine learning based on small dataset

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Physical Review Materials 2022年第4期6卷 044004-044004页

作者： Amirreza Hashemi Ruiqiang Guo Keivan Esfarjani Sangyeop Lee Computational Modeling and Simulation Program University of Pittsburgh Pittsburgh Pennsylvania 15261 USA Department of Mechanical Engineering and Materials Science University of Pittsburgh Pittsburgh Pennsylvania 15261 USA Department of Mechanical and Aerospace Engineering University of Virginia Charlottesville Virginia 22904 USA Department of Materials Science and Engineering University of Virginia Charlottesville Virginia 22904 USA Department of Physics University of Virginia Charlottesville Virginia 22904 USA Department of Physics and Astronomy University of Pittsburgh Pittsburgh Pennsylvania 15261 USA

Establishing the structure-property relationship for grain boundaries (GBs) is critical for developing next-generation functional materials but has been severely hampered due to its extremely large configurational space. Atomistic simulations with low computational cost and high predictive power are strongly desirable, but the conventional simulations using empirical interatomic potentials and density functional theory suffer from the lack of predictive power and high computational cost, respectively. A machine learning interatomic potential (MLIP) recently emerged but often requires extensive size of the training dataset, making it a less feasible approach. Here, we demonstrate that an MLIP trained with a rationally designed small training dataset can predict thermal transport across GBs in graphene with ab initio accuracy at an affordable computational cost. We employed a rational approach based on the structural unit model to find a small set of GBs that can represent the entire configurational space and thus can serve as a cost-effective training dataset for the MLIP. Only 5 GBs were found to be enough to represent the entire configurational space of graphene GBs. Using the atomistic Green's function approach and the MLIP, we revealed that the structure-thermal resistance relation in graphene does not follow the common understanding that large dislocation density causes larger thermal resistance. In fact, thermal resistance is nearly independent of dislocation density at room temperature and is higher when the dislocation density is small at sub-room temperature. We explain this intriguing behavior with the buckling near a GB causing a strong scattering of flexural phonon modes. In this paper, we show that a machine learning technique combined with conventional wisdom (e.g., structural unit model) can extend the recent success of ab initio thermal transport simulation, which has been mostly limited to single crystals, to complex yet practically important polycry

关键词： Phonons Graphene Landauer formula Machine learning

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A computational Pipeline for Patient-Specific Prediction of the Postoperative Mitral Valve Functional State

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Journal of Biomechanical Engineering 2023年第11期145卷 111002-111002页

作者： Liu, Hao Simonian, Natalie T. Pouch, Alison M. Iaizzo, Paul A. Gorman, Joseph H. Gorman, Robert C. Sacks, Michael S. James T. Willerson Center for Cardiovascular Modeling and Simulation The Oden Institute for Computational Engineering and Sciences Department of Biomedical Engineering The University of Texas at Austin AustinTX78712-1229 United States Departments of Radiology and Bioengineering University of Pennsylvania PhiladelphiaPA19104 United States Visible Heart Laboratories Department of Surgery University of Minnesota MinneapolisMN55455 United States Gorman Cardiovascular Research Group Department of Surgery Smilow Center for Translational Research Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States

While mitral valve (MV) repair remains the preferred clinical option for mitral regurgitation (MR) treatment, long-term outcomes remain suboptimal and difficult to predict. Furthermore, pre-operative optimization is complicated by the heterogeneity of MR presentations and the multiplicity of potential repair configurations. In the present work, we established a patient-specific MV computational pipeline based strictly on standard-of-care pre-operative imaging data to quantitatively predict the post-repair MV functional state. First, we established human mitral valve chordae tendinae (MVCT) geometric characteristics obtained from five CT-imaged excised human hearts. From these data, we developed a finite-element model of the full patient-specific MV apparatus that included MVCT papillary muscle origins obtained from both the in vitro study and the pre-operative three-dimensional echocardiography images. To functionally tune the patient-specific MV mechanical behavior, we simulated pre-operative MV closure and iteratively updated the leaflet and MVCT prestrains to minimize the mismatch between the simulated and target end-systolic geometries. Using the resultant fully calibrated MV model, we simulated undersized ring annuloplasty (URA) by defining the annular geometry directly from the ring geometry. In three human cases, the postoperative geometries were predicted to 1 mm of the target, and the MV leaflet strain fields demonstrated close agreement with noninvasive strain estimation technique targets. Interestingly, our model predicted increased posterior leaflet tethering after URA in two recurrent patients, which is the likely driver of long-term MV repair failure. In summary, the present pipeline was able to predict postoperative outcomes from pre-operative clinical data alone. This approach can thus lay the foundation for optimal tailored surgical planning for more durable repair, as well as development of mitral valve digital twins. © 2023 American Society of Mec

关键词： Geometry

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Fatigue prediction for metallic additively manufactured lattice components using FCM based on average strain energy density approach

Fatigue prediction for metallic additively manufactured latt...

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International Congress on Advanced Electromagnetic Materials in Microwaves and Optics (METAMATERIALS)

作者： R. De Biasi O. Oztoprak F. Zanini S. Carmignato F. Berto S. Kollmannsberger M. Benedetti Department of Industrial Engineering Via Sommarive 9 University of Trento Trento Italy School of Engineering and Design Chair of Computational Modeling and Simulation Arcisstraße 21 Technical University of Munich Munich Germany Department of Management and Engineering Stradella San Nicola 3 University of Padova Vicenza Italy Department of Chemical Engineering Materials Environment Via Eudossiana 18 University of Rome Sapienza Roma Italy Faculty of Civil and Environmental Sciences Chair of Data Science in Engineering Coudraystraße 13b Bauhaus-Universität Weimar Weimar Germany

ISBN: (数字)9798350373493

ISBN: (纸本)9798350373509

An accurate prediction of the fatigue life of metallic additively manufactured lattice structures is still a challenging task. The proposed work addresses this challenge of industrial relevance through the computation of an as-built geometry of a lattice structure directly from its X-ray computed tomography reconstruction. The computation is carried out by taking advantage of the Finite Cell Method and applies the average strain energy density method to predict fatigue failure. The proof of concept provided in this work shows an excellent agreement in the fatigue prediction, paving the way for a computationally accurate fatigue life prediction of other types of metamaterials.

关键词： Geometry Accuracy Lattices Fatigue Metamaterials Topology X-ray imaging Stress Strain Testing

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Bending behavior of additively manufactured lattice structures: Numerical characterization and experimental validation

arXiv

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arXiv 2021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 Institute for Advanced Study Technische Universität München Germany Department of Civil Engineering Aalto University Finland

Selective Laser Melting (SLM) technology has undergone significant development in the past years providing unique flexibility for the fabrication of complex metamaterials such as octet-truss lattices. However, the microstructure of the final parts can exhibit significant variations due to the high complexity of the manufacturing process. Consequently, the mechanical behavior of these lattices is strongly dependent on the process-induced defects, raising the importance on the incorporation of as-manufactured geometries into the computational structural analysis. This, in turn, challenges the traditional mesh-conforming methods making the computational costs prohibitively large. In the present work, an immersed image-to-analysis framework is applied to efficiently evaluate the bending behavior of AM lattices. To this end, we employ the Finite Cell Method (FCM) to perform a three-dimensional numerical analysis of the three-point bending test of a lattice structure and compare the as-designed to as-manufactured effective properties. Furthermore, we undertake a comprehensive study on the applicability of dimensionally reduced beam models to the prediction of the bending behavior of lattice beams and validate classical and strain gradient beam theories applied in combination with the FCM. The numerical findings suggest that the SLM octet-truss lattices exhibit size effects, thus, requiring a flexible framework to incorporate high-order continuum theories. © 2021, CC BY-NC-ND.

关键词： Finite element method

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Design and validation of a unity-based simulation to investigate gesture based control of semi-autonomous vehicles 12th

Design and validation of a unity-based simulation to investi...

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12th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020

作者： Sanders, Brian Shen, Yuzhong Vincenzi, Dennis Department of Engineering and Technology Embry-Riddle Aeronautical University Worldwide Daytona Beach United States Department of Computational Modeling and Simulation Engineering Old Dominion University NorfolkVA United States Department of Graduate Studies Embry-Riddle Aeronautical University Worldwide Daytona Beach United States

ISBN: (纸本)9783030496944

The objective of this investigation is to explore the use of hand gestures to control semi-autonomous vehicles. This was achieved through the use of simulations built in Unity and real-life demonstrations. Screen-spaced simulations modeled the control of a recreational quadcopter while Virtual Reality simulations followed by actual demonstrations used a small ground vehicle. The purpose of the actual demonstrations was to validate observations and lessons learned about vehicle control and human performance from the simulations. The investigative process involved identifying natural gestures to control basic functions of a vehicle, matching them to the selected gesture capture technology, developing algorithms to interpret those gestures for vehicle control, and arranging the appropriate visual environment using the Unity game engine to investigate preferred use of those gestures. Observations and participant feedback aided in refining the gesture algorithms for vehicle control and visual information, indicated the simulations provided suitable learning experiences and environments from which to assess human performance. Results indicate that the gesture-based approach holds promise given the availability of new technology. © Springer Nature Switzerland AG 2020.

关键词： Ground vehicles

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