Quadratic Sensitivity Analysis of Fixtures and Locating Schemes for Rigid Parts

2000 ◽  
Vol 123 (3) ◽  
pp. 462-472 ◽  
Author(s):  
Johan S. Carlson
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Experiments ◽  
Geometric Constraints ◽  
Fixture Design ◽  
Practical Relevance ◽  
Sensitivity Equation ◽  
Relative Gain ◽  
Contact Points ◽  
Scheme Evaluation ◽  
Error Interaction

The main purpose of locating schemes are to position parts. The locating scheme utilizes tooling elements, referred to as locators, to introduce geometric constraints. A rigid part is uniquely positioned when it is brought into contact with the locators. By using kinematic analysis we derive a quadratic sensitivity equation that relates position error in locators with the resulting displacement of the part held by the locating scheme. The sensitivity equation which depends on the locator positions and the workpiece geometry around the contact points can be used for locating scheme evaluation, robust fixture design, tolerancing and diagnosis. The quadratic sensitivity equation derived in this paper is novel by adequate dealing with locator contact at nonprismatic surfaces, nonsmall errors, locator error interaction effects and locator errors in arbitrary directions. Theory for comparing the relative gain in precision by using the quadratic sensitivity equation instead of the linear is developed. The practical relevance of the quadratic sensitivity equation is tested through numerical experiments.

High-Fidelity AeroAcoustic Optimization Tool for Flexible Rotors

2020 ◽  
Author(s):  
Li Wang ◽  
Boris Diskin ◽  
Leonard V. Lopes ◽  
Eric J. Nielsen ◽  
Elizabeth Lee-Rausch ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Complex Variable ◽  
High Performance ◽  
Computational Cost ◽  
Geometric Constraints ◽  
General Level ◽  
High Fidelity ◽  
Variable Approach ◽  
Multidisciplinary Analysis ◽  
Tightly Coupled

A high-fidelity multidisciplinary analysis and gradient-based optimization tool for rotorcraft aero-acoustics is presented. Tightly coupled discipline models include physics-based computational fluid dynamics, rotorcraft comprehensive analysis, and noise prediction and propagation. A discretely consistent adjoint methodology accounts for sensitivities of unsteady flows and unstructured, dynamically deforming, overset grids. The sensitivities of structural responses to blade aerodynamic loads are computed using a complex-variable approach. Sensitivities of acoustic metrics are computed by chain-rule differentiation. Interfaces are developed for interactions between the discipline models for rotorcraft aeroacoustic analysis and the integrated sensitivity analysis. The multidisciplinary sensitivity analysis is verified through a complex-variable approach. To verify functionality of the multidisciplinary analysis and optimization tool, an optimization problem for a 40% Mach-scaled HART-II rotor-and-fuselage configuration is crafted with the objective of reducing thickness noise subject to aerodynamic and geometric constraints. The optimized configuration achieves a noticeable noise reduction, satisfies all required constraints, and produces thinner blades as expected. Computational cost of the optimization cycle is assessed in a high-performance computing environment and found to be acceptable for design of rotorcraft in general level-flight conditions.

Determination of contact points between workpiece and fixture elements as a tool for augmented reality in fixture design

2019 ◽  
Author(s):  
Vitalii Ivanov ◽  
Ivan Pavlenko ◽  
Oleksandr Liaposhchenko ◽  
Oleksandr Gusak ◽  
Vita Pavlenko
Keyword(s):  
Augmented Reality ◽  
Fixture Design ◽  
Contact Points

Design Sensitivity Analysis for the Meshfree Shell Structure

2001 ◽  
Author(s):  
Kyung K. Choi ◽  
Nam H. Kim ◽  
Mark E. Botkin
Keyword(s):  
Sensitivity Analysis ◽  
Shell Structure ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Analysis Method ◽  
Sensitivity Equation ◽  
Material Derivative ◽  
Design Variables ◽  
Sensitivity Analysis Method ◽  
Shell Formulation

Abstract A unified design sensitivity analysis method for a meshfree shell structure with respect to sizing, shape, and configuration design variables is presented in this paper. A shear deformable shell formulation is characterized by a CAD connection, thickness degeneration, meshfree discretization, and nodal integration. The design variable is selected from the CAD parameters, and a consistent design velocity field is then computed by perturbing the surface geometric matrix. The material derivative concept is used to obtain a design sensitivity equation in the parametric domain. Numerical examples show the accuracy and efficiency of the proposed design sensitivity analysis method compared to the analytical solution and the finite difference solution.

scholarly journals Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

2020 ◽  
Vol 10 (21) ◽  
pp. 7851
Author(s):  
Przemysław Ignaciuk ◽  
Łukasz Wieczorek
Keyword(s):  
Inventory Management ◽  
Numerical Experiments ◽  
Fitness Function ◽  
Management Policy ◽  
Uncertain Demand ◽  
Satisfaction Level ◽  
Contact Points ◽  
Operational Costs ◽  
Distribution Process ◽  
Continuous Genetic Algorithm

Globalization opens up new perspectives for handling goods distribution in logistic networks. However, establishing an efficient inventory policy is challenging by virtue of the analytical and computational complexity. In this study, the goods distribution process that was governed by the order-up-to policy, implemented in either a distributed or centralized way, was investigated in the logistic systems with complex interconnection topologies. Uncertain demand may be imposed at any node, not just at conveniently chosen contact points, with a lost-sales assumption that introduces a non-linearity into the node dynamics. In order to adjust the policy parameters, the continuous genetic algorithm (CGA) was applied, with the fitness function incorporating both the operational costs and customer satisfaction level. This study investigated how to select the parameters of the popular inventory management policy when operating in the non-trivial networked structures. Moreover, precise guidelines for the CGA tuning in the considered class of problems were provided and evaluated in extensive numerical experiments.

The Numerical Simulation of Workpiece Clamping

2014 ◽  
Vol 474 ◽  
pp. 218-223 ◽  
Author(s):  
Jarmila Oravcová
Keyword(s):  
Numerical Simulation ◽  
Finite Element Method ◽  
Finite Element ◽  
Numerical Experiments ◽  
Simulation Models ◽  
Contact Points ◽  
Reaction Forces ◽  
The Creation ◽  
Made In ◽  
Element Method

The paper deals with the effects of clamping forces on the workpiece during clamping fixture. It describes an experiment using numerical simulation. With numerical experiments we wanted to find out displacement of basic points of the model and changes in the reaction forces in contact points. In the experiment it was considered with initial inaccuracies of contact points. Verification of their effect was made on simulation models of workpieces, which were made in software ANSYS. The creation of the model was used finite element method.

Design Sensitivity Analysis of Nonlinear Shell Structure With Frictionless Contact

2003 ◽  
Author(s):  
Kyung K. Choi ◽  
Kiyoung Yi ◽  
Nam H. Kim ◽  
Mark E. Botkin
Keyword(s):  
Sensitivity Analysis ◽  
Finite Deformation ◽  
Shell Structure ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Integration Scheme ◽  
Configuration Design ◽  
Sensitivity Equation ◽  
Material Derivative ◽  
Frictionless Contact

A continuum-based shape and configuration design sensitivity analysis method for a finite deformation elastoplastic shell structure with frictionless contact has been developed. Shell elastoplasticity is treated based on the projection method that performs the return mapping on the subspace defined by the zero-normal stress condition. An incrementally objective integration scheme is used in the context of finite deformation shell analysis, wherein stress objectivity is preserved for finite rotation increments. The penalty regularization method is used to approximate the contact variational inequality. The material derivative concept is used to develop continuum based design sensitivity. The design sensitivity equation is solved without iteration at each converged load step. Numerical implementation of the proposed shape and configuration design sensitivity analysis is carried out using the meshfree method. The accuracy and efficiency of the proposed method is illustrated using numerical examples.

Quality-adjusted time without symptoms or toxicity (Q-TWiST) of lenvatinib plus everolimus versus everolimus monotherapy in patients with advanced renal cell carcinoma (RCC).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5067-5067
Author(s):  
Chung-Han Lee ◽  
Yin Wan ◽  
Alan D. Smith ◽  
RAN Xie ◽  
Robert J. Motzer
Keyword(s):  
Sensitivity Analysis ◽  
Disease Progression ◽  
Progression Free Survival ◽  
Base Case ◽  
Health State ◽  
Primary Analysis ◽  
Health States ◽  
Relative Gain ◽  
Grade 3 ◽  
Mean Time

5067 Background: In the primary analysis of Study 205 phase II trial (NCT01136733), lenvatinib+everolimus (vs everolimus) significantly prolonged progression-free survival (median PFS; 14.6 vs 5.5 months, HR = 0.40, 95% CI [0.24, 0.68]) in advanced RCC patients who received one prior anti-angiogenic therapy. Overall treatment differences were evaluated in a post hoc analysis using a quality-adjusted time without symptoms of disease or toxicity of treatment (Q-TWiST) methodology. Methods: Patients’ survival time was partitioned into three mutually exclusive health states: time spent with grade 3/4 toxicity (TOX), time prior to disease progression and without grade 3/4 toxicity (TWiST) and time post disease progression (REL). Mean time spent in each state was weighted by a health-state utility associated with that state and summed to calculate the Q-TWiST. Non-parametric bootstrapping method was used to generate 95% CI, which evaluates the between-treatment differences. At base case, utility for TWiST, TOX and REL were assigned as 1.0, 0.5 and 0.5, respectively. A sensitivity analysis was used, applying utilities across the range of 0 (similar to death) to 1.0 (perfect health). A relative gain in Q-TWiST of ≥10% and ≥15% has been established in previous literature as clinically important and clearly clinically important, respectively. Results: Patients receiving lenvatinib+everolimus (n = 51) vs everolimus (n = 50) had significantly longer mean time in TWiST (10.9 vs 6.4 months; difference 4.5 [95% CI: 1.4, 7.8]) and numerically longer in TOX (1.9 vs 0.7 months; difference 1.2 [95% CI: -0.3, 3.1]) but shorter in REL (5.8 vs 8.5 months; difference -2.8 [95% CI: -6.2, 0.6]). At base case, lenvatinib+everolimus patients had a significant mean Q-TWiST gain of 3.7 months (14.7 vs 11.0; 95% CI of difference [1.3, 6.3]), with a relative gain of 24% vs everolimus. In a sensitivity analysis using alternative utility values for TWiST (varied from 0.55 - 0.9) with utility of TOX and REL both set as 0.5, absolute mean Q-TWiST gain ranged from 1.7 to 3.3 months, with a relative gain ranging from 11.0% to 21.2% (all significant). With TWiST utility set as 1.0 and utility of TOX and REL varying from 0 to 1.0, Q-TWiST gain ranged from 1.7 to 5.8 months (mostly significant and became non-significant as the REL utility gets closer to 1.0 and TOX utility gets closer to 0). Conclusions: Within Study 205, lenvatinib+everolimus resulted in a statistically significant and clinically important gain in Q-TWiST vs everolimus alone. Clinical trial information: NCT01136733 .

Modeling and Compensation of Nonlinear Systems Using Sensitivity Analysis

1968 ◽  
Vol 90 (2) ◽  
pp. 187-194
Author(s):  
J. G. Thompson ◽  
R. H. Kohr
Keyword(s):  
Sensitivity Analysis ◽  
Nonlinear Systems ◽  
Performance Index ◽  
Characteristic Parameter ◽  
Sensitivity Equation ◽  
System Sensitivity ◽  
System Equation ◽  
Sensitivity Functions ◽  
Minimization Procedure ◽  
Free Parameters

In this paper sensitivity analysis techniques are applied to two aspects of the nonlinear system design problem: The modeling of nonlinear systems and the compensation of nonlinear systems. In the modeling problem the free parameters of the model are selected to minimize an integral performance index where the integrand is a function of the response of the model and the response of the modeled system. Sensitivity functions, which indicate the sensitivity of the response of the model to changes in the free parameters are used in the minimization procedure. Similarly, in the compensation problem, the adjustable parameters of the compensated system are selected to minimize an integral performance index where the integrand is a function of the response of the compensated system and a desired response. Sensitivity functions, which indicate the sensitivity of the response of the compensated system to changes in the adjustable parameters, are again used in the minimization procedure. The sensitivity functions are obtained from multiple solutions of the general sensitivity equation subjected to various forcing functions. The general sensitivity equation is obtained by differentiation of the model equation or of the compensated system equation. The free or the adjustable parameters are determined as functions of some characteristic parameter which represents the magnitude of the input, the degree of the nonlinearity or some other performance characteristic of the system. All the required computations may be performed by a digital computer. Three nonlinear examples are given to illustrate the method.

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