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26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers, IGLC 2018

作者： Häringer, Paul Borrmann, André Dept. for Civil Geo and Environmental Engineering Technical University of Munich Germany Department of Computational Modeling and Simulation Dept. for Civil Geo and Environmental Engineering Technical University of Munich Germany

ISBN: (纸本)9789380689296

Cycle Planning, or Takt Time Planning, is a key method to reduce the variability between different activities within the execution of a construction. A construction section such as a floor consists of multiple work zones, which should have continuous flow and similar cycle times to efficiently coordinate needed resources. However, for concrete structures it is often difficult to find suitable sizes of casting segments and their grouping to work zones. Nowadays, scheduling experts usually use their practical experience to find an intuitive solution for Cycle Planning, which might be sub-optimal. The objective of our research is thus to develop a semiautomatic method to generate optimal work zones for a cycle. The proposed solution is a BIM-based Cycle Planning concept for the cast in-situ construction method of walls. This paper lays the foundation for our concept and evaluates different designs of Cycle Planning layouts to ensure the practical relevance of the generated work zones. We provide an approach to the semiautomatic method: after splitting all wall objects into smaller sections, an optimization algorithm aggregates wall sections into casting segments and casting segments into work zones. © IGLC 2018 - Proceedings of the 26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers. All rights reserved.

关键词： Lean production

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modeling boundary conditions in high-order, nodal, time-domain finite element methods 23

Modeling boundary conditions in high-order, nodal, time-doma...

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23rd International Congress on Acoustics: Integrating 4th EAA Euroregio, ICA 2019

作者： Pind, Finnur Jeong, Cheol-Ho Hesthaven, Jan S. Engsig-Karup, Allan P. Strømann-Andersen, Jakob Henning Larsen Denmark Acoustic Technology Dept. of Electrical Engineering Technical University of Denmark Denmark Chair of Computational Mathematics and Simulation Science École polytechnique fédérale de Lausanne Switzerland Scientific Computing Dept. of Applied Mathematics and Computer Science Technical University of Denmark Denmark

ISBN: (纸本)9783939296157

Accurate modeling of boundary conditions is an important aspect in room acoustic simulations. It has been shown that the acoustics of rooms is not only dependent on the frequency characteristic of the complex boundary impedance, but also on the angle dependent properties of the impedance ("extended reaction"). This paper presents a computationally efficient method for modeling local-reaction (LR) and extended-reaction (ER) boundary conditions in high-order, nodal, time-domain finite element methods, such as the spectral element method (SEM) or the discontinuous Galerkin finite element method (DGFEM). The frequency and angle dependent boundary impedance is mapped to a multipole model and formulated in differential form. The solution of the boundary differential equations comes with minimal computational cost. In the ER model, wave splitting is applied at the boundary to separate the incident and reflected parts of the sound field. The directional properties of the incident sound field are determined from the incident particle velocity and the boundary conditions are adjusted continuously according to the wave angle of incidence. The accuracy of the boundary condition model is assessed by comparing simulations against measurements, where a significantly improved match between simulations and measurements is found when the ER model is used. © 2019 Proceedings of the International Congress on Acoustics. All rights reserved.

关键词： *fpin@ Extended-reaction High-order numerical methods Sound absorption Wave-based room acoustic simulations

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Design of planet landers for soft landing with DHEM propulsion system-Phase I

Design of planet landers for soft landing with DHEM propulsi...

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AIAA Propulsion and Energy Forum and Exposition, 2019

作者： Mariappan, Amrith Sukumaran, Ajith Thianesh, U.K. Gowri Sankar, P. Kumar, Ashish Yoon, Sugjoon Sanal Kumar, V.R. Dept. of Aeronautical Engineering Kumaraguru College of Technology CoimbatoreTamil Nadu641 049 India Kumaraguru College of Technology CoimbatoreTamil Nadu641 049 India Modeling and Simulation Laboratory Dept. of Aerospace Engineering Sejong University 209 Neungdong-ro Gwangjin-gu Seoul Korea Republic of Sejong University 209 Neungdong-ro Gwangjin-gu Seoul Korea Republic of Indian Space Research Organisation TrivandrumKerala695022 India

ISBN: (数字)9781624105906

ISBN: (纸本)9781624105906

The dual-head electromagnetic (DHEM) propulsion system is capable to create a spinning motion to the multirotor planet landers without any propellant system. The DHEM devices not only have greater applications in space exploration, but also have much application for the near-earth atmosphere surveillance especially during the natural calamity. This is the continuation of our previous connected paper (AIAA 2019-1125) wherein we could demonstrate the capability of the in-house designed DHEM device for producing continuously the reciprocating moment of a magnetic piston using the polarity changer timing circuit (PCTC). In this companion paper parametric analytical studies have been carried out for the design optimization of planet landers with a DHEM propulsion system for a soft landing. The variable density planet environments of Venus and Mars have been selected for the modeling and simulation. During our preliminary studies in India the DHEM propulsion system is facilitated with a four bladed coaxial propeller for examining the performance characteristics of our proposed soft landing Venus lander. A prototype of the static working model of the DHEM device is tested and qualified in the Space Propulsion Laboratory (SPL) of Kumaraguru College of Technology. In another attempt the DHEM device is connected to a quadcopter and simulations have been carried out using a mixed reality simulation (MRS) technique in the modeling and simulation laboratory (MSL) of Sejong University. The MRS is the combination of the virtual part together with the real part. During the quadcopter model validation, a full virtual part is represented through a computer with X-plane flight simulator and a full real part is represented by a real quadcopter operating within an airfield at South Korea. The technique developed in the MSL is to connect the real quadcopter and the virtual quadcopter together using X-plane, MISSION PLANNER and MATLAB interface for MRS. The earth ground experimental fligh

关键词： Timing circuits

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i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations

arXiv

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arXiv 2024年

作者： Litman, Yair Kapil, Venkat Feldman, Yotam M.Y. Tisi, Davide Begušić, Tomislav Fidanyan, Karen Fraux, Guillaume Higer, Jacob Kellner, Matthias Li, Tao E. Pós, Eszter S. Stocco, Elia Trenins, George Hirshberg, Barak Rossi, Mariana Ceriotti, Michele Y. Hamied Department of Chemistry University of Cambridge Lensfield Road CambridgeCB2 1EW United Kingdom Dept. of Physics and Astronomy University College London 17-19 Gordon St LondonWC1H 0AH United Kingdom Thomas Young Centre & London Centre for Nanotechnology 19 Gordon St LondonWC1H 0AH United Kingdom School of Chemistry Tel Aviv University Tel Aviv6997801 Israel Laboratory of Computational Science and Modeling Institut des Matériaux École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Div. of Chemistry and Chemical Engineering California Institute of Technology PasadenaCA91125 United States MPI for the structure and Dynamics of Matter Hamburg Germany School of Physics Tel Aviv University Tel Aviv6997801 Israel Department of Physics and Astronomy University of Delaware NewarkDE19716 United States

Atomic-scale simulations have progressed tremendously over the past decade, largely due to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to reach extensive length and time scales. The i-PI package facilitates integrating the latest developments in this field with advanced modeling techniques, thanks to a modular software architecture based on inter-process communication through a socket interface. The choice of Python for implementation facilitates rapid prototyping but can add computational overhead. In this new release, we carefully benchmarked and optimized i-PI for several common simulation scenarios, making such overhead negligible when i-PI is used to model systems up to tens of thousands of atoms using widely adopted machine learning interatomic potentials, such as Behler-Parinello, DeePMD and MACE neural networks. We also present the implementation of several new features, including an efficient algorithm to model bosonic and fermionic exchange, a framework for uncertainty quantification to be used in conjunction with machine-learning potentials, a communication infrastructure that allows deeper integration with electronic-driven simulations, and an approach to simulate coupled photon-nuclear dynamics in optical or plasmonic cavities. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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CrossSimON: A novel probabilistic approach to cross-platform online social network simulation 17

CrossSimON: A novel probabilistic approach to cross-platform...

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17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019

作者： Liu, Jinwei Chung, Wingyan Huang, Yifan Toraman, Cagri School of Modeling Simulation and Training University of Central Florida OrlandoFL32826 United States Department of Computer Science Faculty of Engineering University of Hong Kong Pokfulam Hong Kong Hong Kong Dept. of Decision Sciences and Managerial Econ. School of Business Admin. Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)9781728125046

The increasing popularity and diversity of online social networks (OSNs) have attracted more and more people to participate in multiple OSNs. Learning users' behavior and information diffusion across platforms is critical for cyber threat detection, but it is still a challenge due to the surge of users participating in multiple social platforms. Existing research on profile matching requires user identity information to be available, which may not be realistic. Little prior research payed attention to mapping behavioral patterns across platforms. We designed and implemented an efficient two-level probabilistic approach called CrossSimON to mapping user-group behavior across platforms. CrossSimON considers the activity level and network position at both individual user level and group level to correlate activities across social platforms. To evaluate the effectiveness of CrossSimON in modeling social activity across platforms, we conducted experiments on three online social platforms: GitHub, Reddit and Twitter. Our experimental results show that CrossSimON outperformed the Benchmark in 3 out of 5 simulation metrics. CrossSimON achieved better performance in user activity prediction. The research provides new strategy for cross-platform online social network simulation, and new findings on simulating OSNs and predictive analytics for understanding online social network behavior. © 2019 IEEE.

关键词： Mapping

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Advanced migraine prediction hardware system 50

Advanced migraine prediction hardware system

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50th Summer Computer simulation Conference, SCSC 2018, Part of the 2018 Summer simulation Multi-Conference, SummerSim 2018

作者： Henares, Kevin Pagán, Josué Ayala, José L. Risco-Martín, José L. Dept. of Computer Architecture and Automation Complutense University of Madrid Madrid Spain Electronic Engineering Department Universidad Politécnica de Madrid Spain CCS-Center for Computational Simulation Madrid Spain Dept. of Computer Architecture and Automation Complutense University of Madrid CCS-Center for Computational Simulation Madrid Spain

ISBN: (纸本)9781510860209

Migraine is one of the most disabling neurological diseases. Its prevalence reaches 15% of the population in developed countries and lead to high economic costs for private and national health systems. There is no cure for the migraine yet. Objective and accurate migraine prediction turns necessary in order to increase the effectiveness of the current treatments. To tackle this problem authors demonstrated in previous works the feasibility of the migraine modeling and presented a DEVS-based model for migraine prediction in a real time framework. This work presents the first step to bring migraine predictive models and simulations to real devices for the first time in the literature. To do this, the DEVS-based model has been ported to a robust hardware description language (VHDL) to be implemented into a FPGA. This paper leads to the final stage: the physical implementation of a predictive migraine monitoring device. © 2018 Society for modeling & simulation International (SCS).

关键词： Field programmable gate arrays (FPGA)

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Non-intrusive Polynomial Chaos Expansion Based Uncertainty Analysis of Bioethanol Production Process

Non-intrusive Polynomial Chaos Expansion Based Uncertainty A...

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International Conference on Computing, Mathematics and engineering Technologies (iCoMET)

作者： Iftikhar Ahmad Uzair Ibrahim Zumrud Imdad Gulsayyar Ali Dept. of Chemical and Material Engineering National University of Sciences and Technology Islamabad Pakistan National University of Sciences and Technology Islamabad PK Research Center for Modeling and Simulation National University of Sciences and Technology Islamabad Pakistan

Ethanol production has been a topic of great interest since the world found the significance of renewable biofuels. Process efficiency and sustainability are main points of focus for ethanol production. Uncertainty in input parameters and its effect on the process outcome, i.e., ethanol production, has been a challenge in realizing efficient operations for the process. This study aims quantification of the effect of uncertainty in process inputs on the production of ethanol. The study is based on an Aspen PLUS® flowsheet of ethanol production from corn stover. MATLAB®-Excel®-Aspen® interfacing is used to estimate ethanol production for different values of input variables. The data generated through the interfacing was used to develop a data-driven model. The data-driven model based on the idea of ensemble learning was used within a Polynomial Chaos Expansion to quantify the accumulative effect of uncertainty in process input variable on process output, i.e., ethanol production.

关键词： Uncertainty Production Ethanol Input variables Mathematical model Biochemistry Temperature distribution

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Tracking blade tip vortices for numerical flow simulations of hovering rotorcraft

Tracking blade tip vortices for numerical flow simulations o...

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AIAA Aerospace Sciences Meeting, 2018

作者： Kao, David L. Smith, Katherine L. Liu, Zhanping Division NASA Ames Research Center Moffett FieldCA94035 United States Dept. of Mathematics Old Dominion University NorfolkVA23529 United States Dept. of Modeling Simulation and Visualization Engineering Old Dominion University NorfolkVA23529 United States

ISBN: (数字)9781624105241

ISBN: (纸本)9781624105241

Blade tip vortices generated by a helicopter rotor blade are a major source of rotor noise and airframe vibration. The noise and vibration occur when a vortex passes close to, and interacts with, a rotor blade. Accurate prediction of Blade Vortex Interaction (BVI) remains a challenge for computational Fluid Dynamics (CFD). Although considerable research has been devoted to BVI noise reduction and experimental techniques for measuring the blade tip vortices in a wind tunnel, there are only a handful of post-processing tools available for extracting vortex core lines from CFD simulation data. In order to obtain the vortex core radius, most of these tools require the user to manually select a vortex core to perform the calculation. Furthermore, none of these tools provide an ability to track the growth of a vortex core, which is a measure of how quickly the vortex diffuses over time. This paper introduces an automated approach for tracking the core growth of a blade tip vortex from CFD simulations of rotorcraft in hover. The proposed method enables effective quantification and visualization of blade tip vortices in helicopter rotor wakes. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Vortex flow

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Considering discrepancy when calibrating a mechanistic electrophysiology model

arXiv

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arXiv 2020年

作者： Lei, Chon Lok Ghosh, Sanmitra Whittaker, Dominic G. Aboelkassem, Yasser Beattie, Kylie A. Cantwell, Chris D. Delhaas, Tammo Houston, Charles Novaes, Gustavo Montes Panfilov, Alexander V. Pathmanathan, Pras Riabiz, Marina Weber dos Santos, Rodrigo Worden, Keith Mirams, Gary R. Wilkinson, Richard D. Computational Biology & Health Informatics Dept. of Computer Science University of Oxford United Kingdom MRC Biostatistics Unit University of Cambridge United Kingdom Centre for Mathematical Medicine & Biology School of Mathematical Sciences University of Nottingham United Kingdom Department of Bioengineering University of California San Diego United States Systems Modeling and Translational Biology GlaxoSmithKline R&D Stevenage United Kingdom ElectroCardioMaths Programme Centre for Cardiac Engineering Imperial College London United Kingdom CARIM School for Cardiovascular Diseases Maastricht University Netherlands Graduate Program in Computational Modeling Universidade Federal de Juiz de Fora Brazil Department of Physics and Astronomy Ghent University Belgium Laboratory of Computational Biology and Medicine Ural Federal University Ekaterinburg Russia U.S. Food and Drug Administration Center for Devices and Radiological Health Office of Science and Engineering Laboratories United States Department of Biomedical Engineering King’s College London Alan Turing Institute United Kingdom Dynamics Research Group Department of Mechanical Engineering University of Sheffield United Kingdom School of Mathematics and Statistics University of Sheffield United Kingdom

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propagates through to outputs or predictions. In this perspective piece we draw attention to an important and under-addressed source of uncertainty in our predictions — that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes (GPs) and autoregressive-moving-average (ARMA) models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Structure-Based Experimental Datasets for Benchmarking of Protein simulation Force Fields

arXiv

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arXiv 2023年

作者： Cavender, Chapin E. Case, David A. Chen, Julian C.-H. Chong, Lillian T. Keedy, Daniel A. Lindorff-Larsen, Kresten Mobley, David L. Ollila, O.H. Samuli Oostenbrink, Chris Robustelli, Paul Voelz, Vincent A. Wall, Michael E. Wych, David C. Gilson, Michael K. Skaggs School of Pharmacy and Pharmaceutical Sciences UC San Diego 9500 Gilman Drive La Jolla CA92093 United States Dept. of Chemistry & Chemical Biology Rutgers University PiscatawayNJ08854 United States Bioscience Division Los Alamos National Laboratory Los Alamos NM87545 United States Department of Chemistry and Biochemistry The University of Toledo ToledoOH43606 United States University of Pittsburgh 219 Parkman Avenue PittsburghPA15260 United States Structural Biology Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Department of Chemistry and Biochemistry City College of New York New YorkNY10031 United States PhD Programs in Biochemistry Biology and Chemistry CUNY Graduate Center New YorkNY10016 United States Linderstrøm-Lang Centre for Protein Science Department of Biology University of Copenhagen Copenhagen NDK-2200 Denmark Pharmaceutical Sciences Department University of California Irvine IrvineCA United States University of Helsinki Institute of Biotechnology Helsinki Finland Institute for Molecular Modeling and Simulation University of Natural Resources and Life Sciences Muthgasse 11 Vienna1190 Austria Dartmouth College Department of Chemistry HanoverNH03755 United States Department of Chemistry Temple University PhiladelphiaPA United States Computer Computational and Statistical Sciences Division Los Alamos National Laboratory Los AlamosNM87545 United States The Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States

This review article provides an overview of structurally oriented, experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear magnetic resonance (NMR) spectroscopy and room temperature (RT) protein crystallography. We discuss why these observables are useful for assessing force field accuracy, how they can be calculated from simulation trajectories, and statistical issues that arise when comparing simulations with experiment. The target audience for this article is computational researchers and trainees who develop, benchmark, or use protein force fields for molecular simulations. © 2023, CC BY.

关键词： Proteins

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