scholarly journals A dynamic modelling strategy for Bayesian computer model emulation

2009 ◽  
Vol 4 (2) ◽  
pp. 393-411 ◽  
Author(s):  
Fei Liu ◽  
Mike West
Keyword(s):  
Computer Model ◽  
Dynamic Modelling ◽  
Computer Model Emulation

scholarly journals Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments

Technometrics ◽  
2021 ◽  
pp. 1-36
Author(s):  
Pulong Ma ◽  
Anirban Mondal ◽  
Bledar A. Konomi ◽  
Jonathan Hobbs ◽  
Joon Jin Song ◽  
...  
Keyword(s):  
Computer Model ◽  
Large Scale ◽  
High Dimensional ◽  
System Uncertainty ◽  
Functional Output ◽  
Computer Model Emulation

Dynamic modelling of entrainment in rapid landslides

2005 ◽  
Vol 42 (5) ◽  
pp. 1437-1448 ◽  
Author(s):  
Scott McDougall ◽  
Oldrich Hungr
Keyword(s):  
Growth Rate ◽  
Simple Model ◽  
Computer Model ◽  
Exponential Growth ◽  
Debris Flows ◽  
Dynamic Modelling ◽  
Back Analysis ◽  
Simple Material ◽  
3D Terrain ◽  
Rapid Landslide

Entrainment of path material is an important feature of many rapid landslides. The associated increases in volume and changes in flow character can significantly influence mobility. A simple material entrainment algorithm, based on the assumption of natural exponential growth with displacement, has been incorporated into a new computer model designed to simulate rapid landslide motion across 3D terrain. The user controls the growth rate and can also implement a change in rheology at the onset of entrainment. A hypothetical example is used to demonstrate the influence of the mass and momentum transfer assumptions. A back-analysis of the 1999 Nomash River landslide is included to show that the simple model is capable of simulating the bulk characteristics of a complex event involving substantial entrainment.Key words: landslides, debris flows, rock avalanches, entrainment, erosion, dynamic modelling.

Automated Metamaterial Design with Computer Model Emulation and Bayesian Optimization

2014 ◽  
Vol 575 ◽  
pp. 201-205
Author(s):  
Bin Liu ◽  
Chun Lin Ji
Keyword(s):  
Reverse Engineering ◽  
Computer Model ◽  
Large Scale ◽  
Optimization Technique ◽  
Geometric Dimension ◽  
Bayesian Optimization ◽  
Functional Regression ◽  
Engineering Process ◽  
Scale Design ◽  
Computer Model Emulation

We present an automated computation system for large scale design of metamaterials (MTMs). A computer model emulation (CME) technique is used to generate a forward mapping from the MTM particle’s geometric dimension to the corresponding electromagnetic (EM) response. Then the design problem translates to be a reverse engineering process which aims to find optimal values of the geometric dimensions for the MTM particles. The core of the CME process is a statistical functional regression module using a Gaussian Process mixture (GPM) model. The reverse engineering process is implemented with a Bayesian optimization technique. Experimental results demonstrate that the proposed approach can facilitate rapid design of MTMs.

1593: Computer Model to Predict Patency Outcome after Vasoepididymostomy

2004 ◽  
Vol 171 (4S) ◽  
pp. 420-420
Author(s):  
Sijo J. Parekattil ◽  
Paul Shin ◽  
Anthony J. Thomas ◽  
Ashok Agarwal
Keyword(s):  
Computer Model

Interpreting Open- and Closed-Loop Transfer Relations Between Cardiorespiratory Parameters: Lessons Learned from a Computer Model of Beat-to-Beat Cardiovascular Regulation

1997 ◽  
Vol 36 (04/05) ◽  
pp. 237-240
Author(s):  
P. Hammer ◽  
D. Litvack ◽  
J. P. Saul
Keyword(s):  
Computer Model ◽  
Closed Loop ◽  
Computer Models ◽  
Cardiovascular Regulation ◽  
Cardiovascular Control ◽  
Lessons Learned ◽  
Multiple Systems ◽  
Response Characteristics ◽  
Similarities And Differences

Abstract:A computer model of cardiovascular control has been developed based on the response characteristics of cardiovascular control components derived from experiments in animals and humans. Results from the model were compared to those obtained experimentally in humans, and the similarities and differences were used to identify both the strengths and inadequacies of the concepts used to form the model. Findings were confirmatory of some concepts but contrary to some which are firmly held in the literature, indicating that understanding the complexity of cardiovascular control probably requires a combination of experiments and computer models which integrate multiple systems and allow for determination of sufficiency and necessity.

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