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45th AIAA Aerospace Sciences Meeting 2007

作者： Shih, A. Ito, Y. Koomullil, R. Kasmai, T. Jankun-Kelly, M. Thompson, D. Brewer, W. University of Alabama at Birmingham Birmingham AL 35294 United States Mississippi State University Mississippi State MS 39762 United States Fluid Physics Int. Mississippi State MS 39762 United States Dept. of Mechanical Engineering United States AIAA United States Computational Simulation and Design Center Box 9627 United States Department of Aerospace Engineering Box A United States Box 1361

ISBN: (纸本)1563478900

In this paper, we present a technique for generating solution adaptive meshes that utilizes feature-aligned surfaces embedded in the computational domain. A feature detection algorithm is first employed to identify regions of the domain where features of interest are located. Surfaces associated with these features are then meshed and a volume mesh that respects these embedded surface meshes is then generated. This approach is promising because it provides a mechanism for controlling local grid quality as well as automatically aligning cell faces with the feature. For flows that include topologically and/or geometrically complex features, we describe a mesh refinement technique that can be used in tandem with the embedded surface meshes to provide a mechanism for refining throughout the computational domain. We include results from three cases to illustrate how the method works.

关键词： Mesh generation

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A CONCEPTUAL-MODEL OF FIELD BEHAVIOR OF AIR SPARGING AND ITS IMPLICATIONS FOR APPLICATION

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GROUND WATER MONITORING AND REMEDIATION 1994年第4期14卷 132-139页

作者： AHLFELD, DP DAHMANI, A JI, W David P. Ahlfeld is an associate professor in the Department of Civil Engineering at the University of Connecticut (Box U-37 Dept. of Civil Engineering The University of Connecticut Storrs CT 06269). He holds a Ph.D. in civil engineering from Princeton University. His research interests include ground water modeling and remediation. Amine Dahmani is engineering project manager in the Environmental Research Institute at the University of Connecticut (Box U-210 Environmental Research Institute The University of Connecticut Storrs CT 06269). He holds a Ph.D. in petroleum engineering from Louisiana State University. His primary research activities are in soil contamination characterization leaching potential of pollutants and innovative ground water remediation technologies. Wei Ji is a Ph.D. student in the Department of Civil Engineering at the University of Connecticut (Box U-37 Dept. of Civil Engineering The University of Connecticut Storrs CT 06269). He has a B.S. in fluid mechanics and an M.S. in computational mathematics from Peking University China. His research interests include fundamental studies of conceptual models modeling of multiphase fluid flow and ground water contaminant transport.

The basic physics of air flow through saturated porous media are reviewed and implications are drawn for the practical application of air sparging. A conceptual model of the detailed behavior of an air sparging system is constructed using elements of multiphase flow theory and the results of recent experimental work. Implications of the conceptual model on air sparging topics are discussed. The meaning of radius of influence in the context of air sparging is found to be ambiguous. The hydrodynamic effects of air sparging such as mounding of ground water and flow impedance are explored. Limitations on rates of remediation and operational strategies for improving sparging effectiveness are examined.

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ORDER-RELEASE PLANNING USING VARIABLE LEAD TIMES BASED ON A BACKWARD simulation-MODEL

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 1995年第10期33卷 2867-2888页

作者： WATSON, EF MEDEIROS, DJ SADOWSKI, RP Dept. Of Quantitative Business Analysis Louisiana Stale University Baton Rouge LA 70803 6316 3190 CEBA Building United States Dept. Of Industrial and Management Systems Engineering Penn State University University Park PA 16802 United States Simulation Services and Consulting Systems Modeling Corporation University Park Sewickley PA 15090 United States

The problem of order-release planning for discrete parts manufacturing is addressed. Traditionally, order-release planning in a multi-stage shop is performed with material requirements planning (MRP) logic, which generally assumes that capacity is infinite and that lead times can be estimated using historical data, past experience, and general rules-of-thumb. These assumptions often result in infeasible plans. A new approach to order-release planning termed BACKSIM, that is based on discrete simulation, is proposed. With this approach, order-release plans are generated via a backward explosion logic similar to MRP except that a simulation model of the facility is used. Since the simulation model accurately captures real-world capacity constraints and operational rules, the order-release plans are theoretically feasible. Essentially, component lead times are calculated based on the anticipated queueing in the system each time BACKSIM is executed. A technique is developed that allows BACKSIM to be fairly compared with the MRP approach.

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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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Models and representation of their ownership

Models and representation of their ownership

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simulation Winter Conference

作者： H.S. Sarjoughian B.P. Zeigler Dept. of Electr. & Comput. Eng. Arizona Univ. Tucson AZ USA Arizona Center for Integrative Modeling and Simulation Electrical and Computer Engineering Department University of Arizona Tucson Tucson AZ USA

Models, similar to other intellectual properties, are increasingly being treated as commodities worthy of protection. Providing ownership for models is key for promoting model reusability, composability, and distributed simulation. However, to date, it appears no principled approach has been developed to support ownership of models. Instead, individuals such as modelers and legal personnel employ ad hoc means to obtain and (re)use models developed and owned by others. We briefly describe access control capabilities offered by computer languages, operating systems, and HLA ownership management services. The examinations of such methods suggest the need for formal ownership specification. We discuss, in an informal setting, requirements for model ownership from the point of view of increasing demand and necessity for model reuse, distributed simulation, and future trends for collaborative model development. We develop concepts for model ownership suitable for collaborative model development and distributed execution. Based on the developed concepts, we present an approach, within the DEVS modeling and simulation framework, for specifying model ownership. We close with the consideration of the proposed approach for the Collaborative DEVS modeling environment and a brief discussion of HLA services relevant to model ownership.

关键词： Collaboration computational modeling Intellectual property Protection Law Legal factors Personnel Access control Computer languages Operating systems

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Particle swarm optimization with local search for height-map surface reconstruction from point clouds in reverse engineering

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Neural Computing and Applications 2024年 1-20页

作者： Gálvez, Akemi Fister, Iztok Deb, Suash Fister, Iztok Iglesias, Andrés Dept. of Applied Mathematics and Computational Sciences E.T.S.I. Caminos Canales y Puertos University of Cantabria Avda. de los Castros s/n Santander39005 Spain Faculty of Pharmaceutical Sciences Toho University 2-2-1 Miyama Funabashi274-8510 Japan Faculty of Electrical Engineering and Computer Science University of Maribor Koroska cesta 34 Maribor2000 Slovenia IT & Educational Consultant Ranchi India Distinguished Professorial Associate Decision Sciences and Modeling Program Victoria University Melbourne Australia

Surface reconstruction is a classical process in industrial engineering and manufacturing, particularly in reverse engineering, where the goal is to obtain a digital model from a physical object. For that purpose, the real object is typically scanned or digitized and the resulting point cloud is then fitted to mathematical surfaces through numerical optimization. The choice of the approximating functions is crucial for the accuracy of the process. Real-world objects such as manufactured workpieces often require complex nonlinear approximating functions, which are not well suited for standard numerical methods. In a previous paper presented at the ISMSI 2023 conference, we addressed this issue by using manually selected approximation functions via optimization through the cuckoo search algorithm with Lévy flights. Building upon that work, this paper presents an enhanced and extended method for surface reconstruction by using height-map surfaces obtained through a combination of exponential, polynomial and logarithmic functions. A feasible approach for this goal is to consider continuous bivariate distribution functions, which ensures consistent models along with good mathematical properties for the output shapes, such as smoothness and integrability. However, this approach leads to a difficult multivariate, constrained, multimodal continuous nonlinear optimization problem. To tackle this issue, we apply particle swarm optimization, a popular swarm intelligence technique for continuous optimization. The method is hybridized with a local search procedure for further improvement of the solutions and applied to a benchmark of 15 illustrative examples of point clouds fitted to different surface models. The performance of the method is analyzed through several computational experiments. The numerical and graphical results show that the method is able to recover the shape of the point clouds accurately and automatically. Furthermore, our approach outperforms other alternati

关键词： Particle swarm optimization (PSO)

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Scalable atomistic simulation algorithms for materials research

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Scientific Programming 2002年第4期10卷 263-270页

作者： Nakano, Aiichiro Kalia, Rajiv K. Vashishta, Priya Campbell, Timothy J. Ogata, Shuji Shimojo, Fuyuki Saini, Subhash Department of Computer Science Dept. of Mat. Sci. and Engineering University of Southern California Los Angeles CA 90089 United States Concurrent Computing Lab. for MS Biol. Comp. and Visualization Center Louisiana State University Baton Rouge LA 70803 United States Department of Applied Sciences Yamaguchi University Ube 755-8611 Japan Faculty of Integrated Arts and Sci. Hiroshima University Higashi-Hiroshima 739-0046 Japan IT Modeling and Simulation NASA Ames Research Center Moffett Field CA 94035-1000 United States

A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD) simulations and quantum-mechanical (QM) calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. The production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.

关键词： Parallel algorithms

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Deep Learning for Image Sequence Classification of Astronomical Events

arXiv

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arXiv 2018年

作者： Carrasco-Davis, Rodrigo Cabrera-Vives, Guillermo Förster, Francisco Estévez, Pablo A. Huijse, Pablo Protopapas, Pavlos Reyes, Ignacio Martínez-Palomera, Jorge Donoso, Cristóbal Dept. of Electrical Engineering Universidad de Chile Dept. of Computer Science Universidad de Concepción Informatics Institute Universidad Austral de Chile Dept. of Astronomy Universidad de Chile Institute for Applied Computational Science Harvard University Center for Mathematical Modeling Universidad de Chile Millennium Institute of Astrophysics Chile

We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This approach avoids the computation of light curves or difference images. This is the first time that sequences of images are used directly for the classification of variable objects in astronomy. The second contribution of this work is the image simulation process. We generate synthetic image sequences that take into account the instrumental and observing conditions, obtaining a realistic, unevenly sampled, and variable noise set of movies for each astronomical object. The simulated dataset is used to train our RCNN classifier. This approach allows us to generate datasets to train and test our RCNN model for different astronomical surveys and telescopes. Moreover, using a simulated dataset is faster and more adaptable to different surveys and classification tasks. We aim at building a simulated dataset whose distribution is close enough to the real dataset, so that a fine tuning could match the distributions and solve the domain adaptation problem. To test the RCNN classifier trained with the synthetic dataset, we used real-world data from the High cadence Transient Survey (HiTS) obtaining an average recall of 85%, improved to 94% after performing fine tuning with 10 real samples per class. We compare the results of our RCNN model with those of a light curve random forest classifier. The proposed RCNN with fine tuning has a similar performance on the HiTS dataset compared to the light curve random forest classifier, trained on an augmented training set with 10 real samples per class. The RCNN approach presents several advantages in an alert stream classification scenario, such as a reduction of the data pre-processing, faster online evaluation and easier performance improvement using a few real data samples. The results obtained encourage us to use the proposed method for astronomical alert bro

关键词： Recurrent neural networks

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Realizing farthest-point voronoi diagrams 28

Realizing farthest-point voronoi diagrams

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28th Canadian Conference on computational Geometry, CCCG 2016

作者： Biedl, Therese Grimm, Carsten Palios, Leonidas Shewchuk, Jonathan Verdonschot, Sander Cheriton School of Computer Science University of Waterloo Canada Computational Geometry Lab School of Computer Science Carleton University OttawaON Canada Institut für Simulation und Graphik Fakultät für Informatik Otto-von-Guericke-Universität Magdeburg Magdeburg Germany Dept. of Computer Science and Engineering University of Ioannina Greece Computer Science Division University of California BerkeleyCA United States School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada

The farthest-point Voronoi diagram of a set of n sites is a tree with n leaves. We investigate whether arbitrary trees can be realized as farthest-point Voronoi diagrams. Given an abstract ordered tree T with n leaves and prescribed edge lengths, we produce a set of n sites S in O(n) time such that the farthest-point Voronoi diagram of S represents T. We generalize this algorithm to smooth, strictly convex, symmetric distance functions. Lastly, given a subdivision Z of Rk with k a small constant, we check in linear time whether Z realizes a kdimensional farthest-point Voronoi diagram. © Canadian Conference on computational Geometry, CCCG *** right reserved.

关键词： Graphic methods

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Design space visualization and its application to a design by shopping paradigm

Design space visualization and its application to a design b...

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2003 ASME Design engineering Technical Conferences and Computers and Information in engineering Conference

作者： Stump, Gary M. Simpson, Timothy W. Yukish, Mike Harris, E. Nathan Applied Research Laboratory Pennsylvania State University University Park PA 16802 United States Dept. of Mechanical Engineering Pennsylvania State University University Park PA 16802 United States Prod. and Process Design Department Applied Research Laboratory Pennsylvania State University University Park PA 16802 United States Modeling and Simulation Lockheed Martin Space Systems Space and Strategic Missiles Denver CO 80201 United States

We have developed a data visualization interface that facilitates a design by shopping paradigm, allowing a decision-maker to form a preference by viewing a rich set of good designs and use this preference to choose an optimal design. Design automation has allowed us to implement this paradigm, since a large number of designs can be synthesized in a short period of time. The interface allows users to visualize complex design spaces by using multi-dimensional visualization techniques that include customizable glyph plots, parallel coordinates, linked views, brushing, and histograms. As is common with data mining tools, the user can specify upper and lower bounds on the design space variables, assign variables to glyph axes and parallel coordinate plots, and dynamically brush variables. Additionally, preference shading for visualizing a user's preference structure and algorithms for visualizing the Pareto frontier have been incorporated into the interface to help shape a decision-maker's preference. Use of the interface is demonstrated using a satellite design example by highlighting different preference structures and resulting Pareto frontiers. The capabilities of the design by shopping interface were driven by real industrial customer needs, and the interface was demonstrated at a spacecraft design conducted by a team at Lockheed Martin, consisting of Mars spacecraft design experts.

关键词： Computer aided design

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