3 edition of **Selecting step sizes in sensitivity analysis by finite differences** found in the catalog.

Selecting step sizes in sensitivity analysis by finite differences

- 63 Want to read
- 15 Currently reading

Published
**1985**
by National Aeronautics and Space Administration, Scientific and Technical Information Branch, For sale by the National Technical Information Service] in [Washington, D.C.], [Springfield, Va
.

Written in English

- Finite element method,
- Finite differences

**Edition Notes**

Statement | Jocelyn Iott, Raphael T. Haftka, Howard M. Adelman |

Series | NASA technical memorandum -- 86382 |

Contributions | Haftka, Raphael T, Adelman, Howard M, United States. Scientific and Technical Information Branch |

The Physical Object | |
---|---|

Format | Microform |

Pagination | 1 v. |

ID Numbers | |

Open Library | OL14926824M |

Introduction. Sensitivity and specificity analysis is commonly used for the evaluation of screening or diagnostic studies. The most important aim of a screening or diagnostic study is, usually to determine how sensitive a screening or diagnostic test is in predicting an outcome when both the test and variable for clinical diagnosis are presented as dichotomous Cited by: Taken one step further, sensitivity analysis offers an insight into how your investment strategy is structured. You can use it to compare investment models by demonstrating how profitability.

Depending on the context, it might mean slightly different things. In general, however, the idea is the following: if you change something slightly, how much does the output of the model change? Let me give you a few informal examples. If you ar. Sensitivity analysis allows him to determine what level of accuracy is necessary for a parameter to make the model sufficiently useful and valid. If the tests reveal that the model is insensitive, then it may be possible to use an estimate rather than a value with greater precision. Sensitivity analysis can also indicate which parameter values areFile Size: KB.

2. Sensitivity analysis means that your results are not highly determined by your model specification (i.e. you could add an additional control variable, or a slightly different functional form, and still get similar results). Thus, (1) is how stable your results are to inputs and (2) is how reactive your results are to design. sensitivity analysis of discretized structural systems. The techniques include a finite difference step size selection algorithm, a method for derivatives of iterative solutions, a Green's function technique for derivatives of transient response, simultaneous .

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Selecting step sizes in sensitivity analysis by finite differences. Sensitivity analysis is an important part of a mathematical modeller's toolbox for model analysis. In this review paper, we.

Get this from a library. Selecting step sizes in sensitivity analysis by finite differences. [Jocelyn Iott; Raphael T Haftka; Howard M Adelman; United. Sensitivity techniques for structures discretized by finite element analysis are described.

In particular, static response, eigenvalue problems and linear transient response are covered. and Adelman, H. M., “Selecting Step Sizes in Sensitivity Analysis by Finite Differences”, NASA TMSensitivity of Discrete Systems.

In Cited by: Iott, J., Haftka, R.T., and Adelman, H.M., “Selecting Step Sizes in Sensitivity Analysis by Finite Differences,” NASA TM, Google ScholarCited by: General remarks on sensitivity analysis, the study of changes in a model output produced by varying model inputs, are made first.

Sampling methods are. Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs.

A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis. In fact if you are working with pdes you have von Neumann stability criteria for how small the grid steps are.

In my own work I have just played around with the step size, and indeed with adaptive schemes (step size is determined by the problem itself and the step size is updated accordingly).

$\endgroup$ – Chinny84 Nov 26 '14 at Regional Sensitivity Analysis (or Monte-Carlo filtering) Regional Sensitivity Analysis (RSA), also called Monte Carlo filtering, is a family of methods mainly aimed at identifying regions in the inputs space corresponding to particular values (e.g.

high or low) of the output, and that can be used for mapping and for dominant controls by: guide the modification of a finite-element model to better correlate analytical and test results; and (4) to approximate structural response by using Taylor series expansions. The most basic and straightforward approach to sensitivity analysis is the finite-difference method; however, it is computationally slow and its accuracy must.

Selecting a Suitable Sensitivity Analysis Method The Sensitivity Analysis Experiment and Results Conclusions Example 3: A Chemical Reactor Setting the Problem Thermal Runaway Analysis of a Batch Reactor Selecting the Sensitivity Analysis Method Sensitivity analysis is The process to test the results & conclusions of economic evaluations for soundness or robustness, by varying the assumptions & variables over a range of plausible values Sensitivity Analysis.

y analysis seem to have the same o rder of accuracy as the FE co de itself (except the Finite Di erences fo r a inadequate stepsize). The Direct Metho d w as sho wn to be the most e cient fo r the studied case. { Joaquim Ma rtins { Octob er 7, { The design sensitivity analysis (DSA) capability provides the derivatives of certain output variables with respect to specified design derivatives are commonly referred to as sensitivities, because they provide a first-order measure of how sensitive the output variable is to a change in the design output variables for which sensitivities are computed.

How to do Sensitivity Analysis using Cadence Pspice Simulation tool. Step by step Guide for Worst Case Analysis (Sensitivity Analysis) in Pspice: Draw the required schematic.

For our example, we had drawn a group of resistors powered by 12VDC supply. We considered 5% tolerance for all resistors. Available in the National Library of Australia collection. Author: Adelman, Howard M; Format: Book, Microform, Online; 1 v.

design sensitivity is considered herein are: Structural Procedure Library a. Design objective b. Design model response As a result, the design sensitivity analysis capability in is currently limited to finite element models of structures with linear response in the computation of 1.

Gradients for a. An objective function (or the design. The Energy Finite Element Method (EFEM) is the application of finite element techniques in power balance equation to obtain a localized time- and space-averaged energy density solution [].

Since energy conservation is imposed locally in power flow analysis, it is possible to represent the structural geometry in detail, which isCited by: 2. Sensitivity Analysis: The Direct and Adjoint Method Masterarbeit zur Erlangung des akademischen Grades Diplomingenieur The Finite Element Method applied to the Test Problem 48 parts can also be found in the book from Le Tallec and Laporte [4]).File Size: KB.

References Relating to Grid Sensitivity. A recommended book is by Peter Roache's classic text on "Computational Fluid Dynamics" and ''Verification and Validation in Computational Science and Engineering''.

Another reference is the following one it studies the mixing process of two domains. It is important to note that the Reynolds number is defined using the projected area of the cylinder, as seen by the flow, and is kept constant in our analysis. Moreover, we use finite differences to compute the shape sensitivity as the ellipse parameter 𝜏 is varied.

We employ an O-grid for the cylinders such that the outer domain is Cited by:. Probability and Sensitivity you can specify the sensitivity study range with a Delta and a Step to both sides (+ and -) of the means value as shown below (Figure 8): Figure 8 Defining and Setting of Parameters for Sensitivity Analysis When you do a sensitivity study of the above, at the end, SLOPE/W provides a sensitivity graph (Figure File Size: KB.This is a bit of an oversimplification, but model validation generally tells one about how well the current model fits the data at hand.

Sensitivity analyses tell one how likely your results based upon that model would change given new information or changes to your assumptions. For example, someone could develop a model aimed at determining the impact that an .Chapter 6: Sensitivity Analysis introductory book, we will concentrate on this form of sensitivity analysis.

LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) VARIABLE VALUE REDUCED COST X1 X2