DEVS Distributed Modeling Framework - A Parallel Implementation for the Cloud

2016 ◽  
Keyword(s):  
Parallel Implementation ◽  
Modeling Framework ◽  
Distributed Modeling

scholarly journals Remote sensing and GIS application for river runoff and water quality modeling in a hilly forested watershed of Japan

2010 ◽  
Vol 13 (2) ◽  
pp. 198-216 ◽  
Author(s):  
Binaya R. Shivakoti ◽  
Shigeo Fujii ◽  
Shuhei Tanaka ◽  
Hirotaka Ihara ◽  
Masashi Moriya
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Cover ◽  
Spatial Information ◽  
Remote Sensing And Gis ◽  
Water Quality Modeling ◽  
Model Verification ◽  
Modeling Framework ◽  
Area Index ◽  
Distributed Modeling

The main objective of this study is to present a simplified distributed modeling framework based on the storage balance concept of a Tank Model and by utilizing inputs from remote sensing data and GIS analysis. The modeling process is simplified by (1) minimizing the number of parameters with unknown values and 2) retaining important characteristics (such as land cover, topography, geology) of the study area in order to account for spatial variability. Remote sensing is used as a main source of distributed data and the GIS environment is used to integrate spatial information into the model. Remote sensing is utilized mainly to derive land cover, leaf area index (Lai) and transpiration coefficient (Tc). Topographic variables such as slope, drainage direction and soil topographic index (Tindex) are derived from a digital elevation model (DEM) using GIS. The model is used to estimate evapotranspiration (Et) loss, river flow rate and selected water quality parameters (CODMn and TP). Model verification adopted a comparison of estimated results with observed data collected at different temporal scales (storm events, daily, alternate days and every 10 days). A simplified distributed modeling framework coupled with remote sensing and GIS is expected to be an alternative to complex distributed modeling processes, which required values of parameters usually unavailable at a grid scale.

scholarly journals MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference

2020 ◽  
Vol 95 (7) ◽  
Author(s):  
Robert J. B. Goudie ◽  
Rebecca M. Turner ◽  
Daniela De Angelis ◽  
Andrew Thomas
Keyword(s):  
Bayesian Inference ◽  
Parallel Implementation ◽  
Modeling Framework

Distributed Modeling and Decentralized H∞ Control of a Segmented Telescope Mirror

2007 ◽  
Author(s):  
Daniel Kerley ◽  
Edward J. Park ◽  
Jennifer Dunn
Keyword(s):  
Large Scale ◽  
Surface Model ◽  
Modeling Framework ◽  
Optical Telescope ◽  
Loop Control ◽  
Distributed Modeling ◽  
Decentralized Controllers ◽  
Benchmark System ◽  
Spatially Interconnected Systems ◽  
Scale Control

In this paper a distributed dynamic model for a segmented primary mirror of an optical telescope is presented, based on the distributed modeling framework for spatially interconnected systems. The next generation of optical telescopes will employ highly segmented primary mirrors, which leads to a large-scale control problem. The distributed modeling technique allows for the design of scalable decentralized controllers that are better suited for such systems. A numerical seven segment mirror surface model is used as the benchmark system for comparing the performance between a scalable decentralized H∞ controller and a global H∞ controller. The closed-loop control simulation results show that both controllers perform comparably for the benchmark case. However when the number of the segments increases significantly (e.g. > 100) the scalable decentralized control will allow for a more tractable solution than the monolithic global control.

scholarly journals Development of a Distributed Modeling Framework to Estimate Thermal Comfort along 2020 Tokyo Olympic Marathon Course

Atmosphere ◽  
2018 ◽  
Vol 9 (6) ◽  
pp. 210 ◽  
Author(s):  
Satoshi Hirabayashi ◽  
Tsutomu Abe ◽  
Fumiko Imamura ◽  
Chie Morioka
Keyword(s):  
Solar Radiation ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Energy Budget ◽  
View Factor ◽  
Street Trees ◽  
M Cell ◽  
Modeling Framework ◽  
Distributed Modeling ◽  
Human Thermal Comfort

Heat stress is an issue for marathon races in the summer, such as the one planned for the 2020 Tokyo Summer Olympic games. The Tokyo Metropolitan Government is planning to grow existing street trees’ canopies to enlarge their shade to reduce air temperature and solar radiation. To formulate a baseline to assess the effect of street trees and buildings on human thermal comfort, Distributed-COMfort FormulA (D-COMFA), a prototype of a distributed computer model using a geographic information system (GIS) was developed. D-COMFA calculates the energy budget of a human body on a 1 m cell basis, using readily available datasets such as weather measurements and polygon data for street structures. D-COMFA was applied to a street segment along the marathon course in Tokyo on an hourly-basis on 9 August 2016, the hottest day in Tokyo in 2016. Our case study showed that the energy budget was positively related to the sky view factor, air temperature, and solar radiation. The energy budget was reduced on average by 26–62% in the shade throughout the day.

scholarly journals A Parallel Implementation of the Finite State Projection Algorithm for the Solution of the Chemical Master Equation

2020 ◽  
Author(s):  
Huy Vo ◽  
Brian Munsky
Keyword(s):  
Master Equation ◽  
High Performance ◽  
Parallel Implementation ◽  
Chemical Species ◽  
Chemical Master Equation ◽  
Kolmogorov Equation ◽  
Projection Algorithm ◽  
Reaction Networks ◽  
Modeling Framework ◽  
Finite State

AbstractStochastic reaction networks are a popular modeling framework for biochemical processes that treat the molecular copy numbers within a single cell as a continuous time Markov chain, whose forward Chapman-Kolmogorov equation is known in biochemistry literature as the chemical master equation (CME). The solution of the CME contains extremely useful information that can be compared to experimental data in order to improve the quantitative understanding of biochemical reaction networks within the cell. However, this solution is costly to compute as it requires integrating an enormous system of differential equations that grows exponentially with the number of chemical species. To address this issue, we introduce a novel multiple-sinks Finite State Projection algorithm that approximates the CME with an adaptive sequence of reduced-order models with an effecient parallelization based on MPI. The implementation is tested on models of sizable state spaces using a high-performance computing node on Amazon Web Services, showing favorable scalability.

Distributed Modeling Of Building Systems Through Cyber-Physical Integration

2019 ◽  
pp. 12-17
Keyword(s):  
Data Structure ◽  
Operating Conditions ◽  
Physical Models ◽  
Distributed Model ◽  
Physical Processes ◽  
Distributed Modeling ◽  
Distributed Models ◽  
Operating Modes ◽  
Building Systems ◽  
Important Practical Application

This article describes the proposed approaches to creating distributed models that can, with given accuracy under given restrictions, replace classical physical models for construction objects. The ability to implement the proposed approaches is a consequence of the cyber-physical integration of building systems. The principles of forming the data structure of designed objects and distributed models, which make it possible to uniquely identify the elements and increase the level of detail of such a model, are presented. The data structure diagram of distributed modeling includes, among other things, the level of formation and transmission of signals about physical processes inside cyber-physical building systems. An enlarged algorithm for creating the structure of the distributed model which describes the process of developing a data structure, formalizing requirements for the parameters of a design object and its operating modes (including normal operating conditions and extreme conditions, including natural disasters) and selecting objects for a complete group that provides distributed modeling is presented. The article formulates the main approaches to the implementation of an important practical application of the cyber-physical integration of building systems - the possibility of forming distributed physical models of designed construction objects and the directions of further research are outlined.

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