Employing Multidimensional Data Visualization Tools to Assess the Impact of Constraint Uncertainties on Complex Design Problems

2017 ◽  
Author(s):  
Gary M. Stump ◽  
Simon W. Miller ◽  
Michael A. Yukish ◽  
Christopher M. Farrell
Keyword(s):  
Data Visualization ◽  
Decision Makers ◽  
Multidimensional Data ◽  
Design Problems ◽  
Design Constraints ◽  
Performance Space ◽  
Multidimensional Data Visualization ◽  
Complex Design ◽  
Visualization Tools ◽  
The Impact

A potential source of uncertainty within multi-objective design problems can be the exact value of the underlying design constraints. This uncertainty will affect the resulting performance of the selected system commensurate with the level of risk that decision-makers are willing to accept. This research focuses on developing visualization tools that allow decision-makers to specify uncertainty distributions on design constraints and to visualize their effects in the performance space using multidimensional data visualization methods to solve problems with high orders of computational complexity. These visual tools will be demonstrated using an example portfolio design scenario in which the goal of the design problem is to maximize the performance of a portfolio with an uncertain budget constraint.

scholarly journals Multidimensional data visualization

2002 ◽  
Vol 34 (2) ◽  
pp. 158-162 ◽  
Author(s):  
Matthew J. Pastizzo ◽  
Robert F. Erbacher ◽  
Laurie B. Feldman
Keyword(s):  
Data Visualization ◽  
Multidimensional Data ◽  
Multidimensional Data Visualization

Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments

2006 ◽  
Author(s):  
Jun Liu ◽  
Daniel W. Apley ◽  
Wei Chen
Keyword(s):  
Robust Design ◽  
Prediction Interval ◽  
Computer Experiments ◽  
Design Problems ◽  
Deterministic Optimization ◽  
Automotive Engine ◽  
Design Objective ◽  
Design Variables ◽  
Complex Design ◽  
The Impact

The use of metamodels in simulation-based robust design introduces a new source of uncertainty that we term model interpolation uncertainty. Most existing approaches for treating interpolation uncertainty in computer experiments have been developed for deterministic optimization and are not applicable to design under uncertainty. With the randomness present in noise and/or design variables that propagates through the metamodel, the effects of model interpolation uncertainty are not nearly as transparent as in deterministic optimization. In this work, a methodology is developed within a Bayesian framework for quantifying the impact of interpolation uncertainty on robust design objective. By viewing the true response surface as a realization of a random process, as is common in kriging and other Bayesian analyses of computer experiments, we derive a closed-form analytical expression for a Bayesian prediction interval on the robust design objective function. This provides a simple, intuitively appealing tool for distinguishing the best design alternative and conducting more efficient computer experiments. Even though our proposed methodology is illustrated with a simple container design and an automotive engine piston design example here, the developed analytical approach is the most useful when applied to high-dimensional complex design problems in a similar manner.

Application of Multidimensional Data Visualization by Means of Self-Organizing Kohonen Maps to Evaluate Classification Possibilities of Various Coal Types / Zastosowanie Wizualizacji Wielowymiarowych Danych Za Pomocą Sieci Kohonena Do Oceny Możliwości Klasyfikacji Różnych Typów Węgla

2015 ◽  
Vol 60 (1) ◽  
pp. 39-50 ◽  
Author(s):  
Dariusz Jamróz ◽  
Tomasz Niedoba
Keyword(s):  
Data Visualization ◽  
Multidimensional Data ◽  
Material Quality ◽  
Kohonen Maps ◽  
Multidimensional Data Visualization ◽  
Visualization Techniques ◽  
Modern Tool ◽  
Coal Type

Abstract Multidimensional data visualization methods are a modern tool allowing to classify some analysed objects. In the case of grained materials e.g. coal, many characteristics have an influence on the material quality. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. To achieve this purpose, the method of Kohonen maps was applied by means of which three types of coal - 31, 34.2 and 35 (according to Polish classification of coal types) were investigated. It was stated that the applied methodology allows to identify certain coal types efficiently and can be used as a qualitative criterion for grained materials.

Sign in / Sign up

Export Citation Format

Share Document