1 Synopsys Saber Simulation Performance Measure(s) Performance Measure(s) Model(s) Nominal Design Nominal Design Sensitivity Analysis Sensitivity Analysis.

Slides:



Advertisements
Similar presentations
Uncertainties in Predictions of Arctic Climate Peter Challenor, Bablu Sinha (NOC) Myles Allen (Oxford), Robin Tokmakian (NPS)
Advertisements

27/11/02DEFINE Workshop, Pisa1 Robustness Testing Marie-Claude Gaudel, LRI Thierry Jéron, IRISA Collaborations with IMAG, LABRI, LAAS (CNRS/AS « méthodes.
Probabilistic Analysis using FEA A. Petrella. What is Probabilistic Analysis ‣ All input parameters have some uncertainty ‣ What is the uncertainty in.
1 Sixty-Four-Slice Computed Tomography of the Coronary Arteries: Cost-Effectiveness Analysis of Patients Presenting to the ED with Low Risk Chest Pain.
Worst Case Analysis Using Analog Workbench by Andrew G. Bell ITT Industries.
A Project Is Not a Black Box Chapter 10. Topics Covered  Sensitivity Analysis  Break Even Analysis  Monte Carlo Simulation  Decision Trees.
Approaches to Data Acquisition The LCA depends upon data acquisition Qualitative vs. Quantitative –While some quantitative analysis is appropriate, inappropriate.
Computational statistics, course introduction Course contents  Monte Carlo Methods  Random number generation  Simulation methodology  Bootstrap  Markov.
Position Error in Assemblies and Mechanisms Statistical and Deterministic Methods By: Jon Wittwer.
Tensile Strength of Composite Fibers Author: Brian Russell Date: December 4, 2008 SMRE - Reliability Project.
An Example of Monte Carlo Sensitivity Analysis Mock Seep Tent Example.
Effective Depletion Depth JC & Marina. 04/30/01Jianchun (JC) Wang2 Depletion Depth Methods FPIX0 pstop at 30° X inc Depth: d  XiXi.
Dimensional Variation Analysis
Frankfurt (Germany), 6-9 June 2011 Ying Wang – China – Session2– Paper 0587 Voltage Sag Frequency Assessment Considering Customer Satisfaction Degree Ying.
Reliability Model for Compressor Failure SMRE Term Project Paul Zamjohn August 2008.
1 Sustainable Withdrawal Rates and How Alternative Strategies Affect the Heirs Peter James Lingane, EA, CFP® Financial Security by Design Lafayette, CA.
Robust Design and Reliability-Based Design ME 4761 Engineering Design 2015 Spring Xiaoping Du.
V11 Module 5 Talk Plan 1.Presentation of the CFS tool o Goal & Use o Structure o Technical issues 2.Practice on a case study.
Implementation of a double-hurdle model Bruno Garcia The Stata Journal (2013), 13, Number 4, pp Presented by Gulzat.
Chapter 14 Monte Carlo Simulation Introduction Find several parameters Parameter follow the specific probability distribution Generate parameter.
Probabilistic Mechanism Analysis. Outline Uncertainty in mechanisms Why consider uncertainty Basics of uncertainty Probabilistic mechanism analysis Examples.
Jinghua Fu Institute of Particle Physics, CCNU, Wuhan TUHEP, Tsinghua University, Beijing On the Measurement of Event Mean Pt Fluctuations Motivation Analytical.
Advances in Robust Engineering Design Henry Wynn and Ron Bates Department of Statistics Workshop at Matforsk, Ås, Norway 13 th -14 th May 2004 Design of.
D0 SAM – status and needs Plagarized from: D0 Experiment SAM Project Fermilab Computing Division.
Laboratoire Méthodes et Structures Informatique MSI LABORATORY PRESENTATION 83, rue d’Isle LIMOGES - France -
1 Risk Assessment Via Monte Carlo Simulation: Tolerances Versus Statistics B. Ross Barmish ECE Department University of Wisconsin, Madison Madison, WI.
Par: Grace McNamara MONTE CARLO, MONACO.
課程四 : 風險分析 Application: The replacement decision Public utilities and annual cost Risk Analysis Sensitivity analysis Scenario analysis Mote Carlo simulation.
Machine Design Under Uncertainty. Outline Uncertainty in mechanical components Why consider uncertainty Basics of uncertainty Uncertainty analysis for.
Fault-Tolerant Control. Fault Tolerance Passive Passive  Tolerance achieved by the use of feedback control laws that are robust to possible system faults.
Monte-Carlo based Expertise A powerful Tool for System Evaluation & Optimization  Introduction  Features  System Performance.
Robust Design: The Future of Engineering Analysis in Design
Components are existing in ONE of TWO STATES: 1 WORKING STATE with probability R 0 FAILURE STATE with probability F R+F = 1 RELIABLEFAILURE F R Selecting.
© 2014 Minitab, Inc. Justin Callahan Commercial Sales Representative.
The Snowball Effect: Statistical Evidence that Big Earthquakes are Rapid Cascades of Small Aftershocks Karen Felzer U.S. Geological Survey.
Nonlinear regression Review of Linear Regression.
Frankfurt (Germany), 6-9 June 2011 Manuel Avendaño J. V. Milanović Manuel Avendaño – UK – Session 2 – Paper 0529 METHODOLOGY FOR FLEXIBLE, COST-EFFECTIVE.
1 SMART-T Briefing to OSMA SAS - July 19, 2004 SMART-T Project Overview Kurt D. Guenther AS&M / Dryden Flight Research Center July 19, 2004.
Compel20001 The Power of SABER Simulation Tools for Power Design Steve Chwirka Compel2000.
Particle Tracking for CDC prototype Amangaliyev Temirlan.
Geraint Palmer Optimisation using Linear Programming.
Vladimir Gromov, NIKHEF, Amsterdam. GOSSIPO-3 Working Group February 03, Local Oscillator in the GOSSIPO-3 readout chip.
A Challenge Problem on Uncertainty Quantification & Value of Information 1 Patrick Koch Dassault Systèmes SIMULIA 2013 NAFEMS World Congress Salzburg,
Copyright 2012, AgrawalLecture 12: Alternate Test1 VLSI Testing Lecture 12: Alternate Test Dr. Vishwani D. Agrawal James J. Danaher Professor of Electrical.
16/9/2011UCERF3 / EQ Simulators Workshop ViscoSim Fred Pollitz USGS, Menlo Park.
מהפכות באנגליה.
May 20, 2010 Meeting David W. Smith
Xavier Bonnin and Davide Aguglia
1 Seminar 3 Finite differences vs Monte Carlo methods.
Date of download: 12/16/2017 Copyright © ASME. All rights reserved.
Homework 8 - Monte Carlo Simulation using Minitab
A New Control Framework
Pricing Barrier Options Using Monte Carlo Simulation
Monte Carlo Simulation Managing uncertainty in complex environments.
MONTECARLO (STATIC) SIMULATIONS
Probabilistic Methods: Theory and Application to Human Anatomy
VLSI Testing Lecture 12: Alternate Test
الجفاف وآثاره على النبات
تحليل الحساسية Sensitive Analysis.
Physics-based simulation for visual computing applications
بعض النقاط التي تؤخذ في الحسبان عند تقييم الاستثمارات الزراعية
MONTECARLO (STATIC) SIMULATIONS
التعامل مع ضغوطات العمل إعداد وتقديم إقبال المطيري
Chapter 5 Circuit Simulation.
Chapter 14 Monte Carlo Simulation
Discrete-time markov chain (continuation)
SIGNAL Band: Very Sensitive
11. Monte Carlo Applications
Substation Automation IT Needs
Maximum Likelihood Estimation (MLE)
Presentation transcript:

1 Synopsys Saber Simulation Performance Measure(s) Performance Measure(s) Model(s) Nominal Design Nominal Design Sensitivity Analysis Sensitivity Analysis Robust Design Robust Design Parameters / Tolerances Parameters / Tolerances Monte Carlo Simulations Monte Carlo Simulations Pareto Analysis Pareto Analysis Stress Analysis Stress Analysis Fault Analysis Fault Analysis

2 Synopsys Saber Simulation (Grouped) Performance Measure(s) Performance Measure(s) Model(s) Nominal Design Nominal Design Sensitivity Analysis Sensitivity Analysis Robust Design Robust Design Parameters / Tolerances Parameters / Tolerances Monte Carlo Simulations Monte Carlo Simulations Pareto Analysis Pareto Analysis Stress Analysis Stress Analysis Fault Analysis Fault Analysis

3 PerformanceModel(s) Nominal Design Sensitivity Analysis