A Hierarchical Statistical Sensitivity Analysis Method for Multilevel Systems With Shared Variables

2010 ◽  
Vol 132 (3) ◽  
Author(s):  
Yu Liu ◽  
Xiaolei Yin ◽  
Paul Arendt ◽  
Wei Chen ◽  
Hong-Zhong Huang
Keyword(s):  
Sensitivity Analysis ◽  
Design Stage ◽  
Engineering Systems ◽  
Hierarchical Systems ◽  
Multilevel Systems ◽  
Shared Variables ◽  
Sensitivity Analysis Method ◽  
Group A ◽  
Upper Level ◽  
The Impact

Statistical sensitivity analysis (SSA) is an effective methodology to examine the impact of variations in model inputs on the variations in model outputs at either a prior or posterior design stage. A hierarchical statistical sensitivity analysis (HSSA) method has been proposed in literature to incorporate SSA in designing complex engineering systems with a hierarchical structure. However, the original HSSA method only deals with hierarchical systems with independent subsystems. For engineering systems with dependent subsystem responses and shared variables, an extended HSSA method with shared variables (named HSSA-SV) is developed in this work. A top-down strategy, the same as in the original HSSA method, is employed to direct SSA from the top level to lower levels. To overcome the limitation of the original HSSA method, the concept of a subset SSA is utilized to group a set of dependent responses from the lower level submodels in the upper level SSA and the covariance of dependent responses is decomposed into the contributions from individual shared variables. An extended aggregation formulation is developed to integrate local submodel SSA results to estimate the global impact of lower level inputs on the top level response. The effectiveness of the proposed HSSA-SV method is illustrated via a mathematical example and a multiscale design problem.

An Extended Hierarchical Statistical Sensitivity Analysis Method for Multilevel Systems With Shared Variables

2009 ◽  
Author(s):  
Yu Liu ◽  
Xiaolei Yin ◽  
Paul Arendt ◽  
Wei Chen ◽  
Hong-Zhong Huang
Keyword(s):  
Sensitivity Analysis ◽  
Sampling Technique ◽  
Design Stage ◽  
Engineering Systems ◽  
Hierarchical Systems ◽  
Shared Variables ◽  
Sensitivity Analysis Method ◽  
Upper Level ◽  
Importance Sampling Technique ◽  
The Impact

Statistical sensitivity analysis (SSA) is an effective methodology to examine the impact of variations in model inputs on the variations in model outputs at either a prior or posterior design stage. A hierarchical statistical sensitivity analysis (HSSA) method has been proposed in literature to incorporate SSA in designing complex engineering systems with a hierarchical structure. However, the original HSSA method only deals with hierarchical systems with independent subsystems. Due to the existence of shared variables at lower levels, responses from lower level submodels that act as inputs to a higher level subsystem are both functionally and statistically dependent. For designing engineering systems with dependent subsystem responses, an extended hierarchical statistical sensitivity analysis (EHSSA) method is developed in this work to provide a ranking order based on the impact of lower level model inputs on the top level system performance. A top-down strategy, same as in the original HSSA method, is employed to direct SSA from the top level to lower levels. To overcome the limitation of the original HSSA method, the concept of a subset SSA is utilized to group a set of dependent responses from lower level submodels in the upper level SSA. For variance decomposition at a lower level, the covariance of dependent responses is decomposed into the contributions from individual shared variables. To estimate the global impact of lower level inputs on the top level output, an extended aggregation formulation is developed to integrate local submodel SSA results. The importance sampling technique is also introduced to re-use the existing data from submodels SSA during the aggregation process. The effectiveness of the proposed EHSSA method is illustrated via a mathematical example and a multiscale design problem.

scholarly journals PRODUCT QUALITY AT DESIGN STAGE

2020 ◽  
Vol 2020 (2) ◽  
pp. 11-18 ◽  
Author(s):  
Victor Tikhomirov ◽  
Mikhail Izmerov ◽  
Mikhail Shalygin
Keyword(s):  
Product Quality ◽  
Friction Angle ◽  
Design Stage ◽  
Friction Unit ◽  
Time Behavior ◽  
Engineering Systems ◽  
System Behavior ◽  
Environment Impact ◽  
Friction Process ◽  
The Impact

The purpose of the work consists in the presentation to the scientific community a special methodology for tribo-system designing, where a design process interacts with the analysis of possible behavior of a friction angle while operating specified technical conditions taking into account an environment impact that is taking into account a forecasting of tribo-system behavior under specified conditions. For that the best possibility is the creation of the computer model of a friction unit with the estimate of its time behavior during the impact of outer parameters upon it and the impact of inner factors, for this purpose a design-engineer must have competences in different fields of science and technology. Besides, a designer must develop procedures for replacement, restoration and repair to support an operating status of the equipment under development for the whole life required. A basic method of friction process investigations is a computer modeling of friction unit behavior. The result and investigation novelty is the development of a special methodology for designing technical systems taking into account the simulation of their evolution ensuring product quality at the designing stage. In such a way there are shown principles for machinery quality assurance during designing engineering systems.

scholarly journals An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 95
Author(s):  
Jiewei Chen ◽  
Huijuan Cui ◽  
Yangyang Xu ◽  
Quansheng Ge
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Output Measurement ◽  
Sensitivity Analysis Method ◽  
The Impact

Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future.

scholarly journals Mapping-Based Hierarchical Sensitivity Analysis for Multilevel Systems With Multidimensional Correlations

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Can Xu ◽  
Ping Zhu ◽  
Zhao Liu ◽  
Wei Tao
Keyword(s):  
Sensitivity Analysis ◽  
Analysis Method ◽  
Computational Framework ◽  
Copula Theory ◽  
Multilevel Systems ◽  
Sensitivity Indices ◽  
Response Variance ◽  
Sensitivity Analysis Method ◽  
Vine Copula ◽  
Input Uncertainties

Abstract Hierarchical sensitivity analysis (HSA) of multilevel systems is to assess the effect of system’s input uncertainties on the variations of system’s performance through integrating the sensitivity indices of subsystems. However, it is difficult to deal with the engineering systems with complicated correlations among various variables across levels by using the existing hierarchical sensitivity analysis method based on variance decomposition. To overcome this limitation, a mapping-based hierarchical sensitivity analysis method is proposed to obtain sensitivity indices of multilevel systems with multidimensional correlations. For subsystems with dependent variables, a mapping-based sensitivity analysis, consisting of vine copula theory, Rosenblatt transformation, and polynomial chaos expansion (PCE) technique, is provided for obtaining the marginal sensitivity indices. The marginal sensitivity indices can allow us to distinguish between the mutual depend contribution and the independent contribution of an input to the response variance. Then, extended aggregation formulations for local variables and shared variables are developed to integrate the sensitivity indices of subsystems at each level so as to estimate the global effect of inputs on the response. Finally, this paper presents a computational framework that combines related techniques step by step. The effectiveness of the proposed mapping-based hierarchical sensitivity analysis (MHSA) method is verified by a mathematical example and a multiscale composite material.

Reliability sensitivity analysis method for time-dependent problem based on first-passage method

2018 ◽  
Vol 233 (4) ◽  
pp. 787-802
Author(s):  
Wenxuan Wang ◽  
Hangshan Gao ◽  
Changcong Zhou ◽  
Wanghua Xu
Keyword(s):  
Sensitivity Analysis ◽  
Time Dependent ◽  
Sensitivity Index ◽  
Analysis Method ◽  
First Passage ◽  
Reliability Sensitivity ◽  
Reliability Sensitivity Analysis ◽  
Sensitivity Analysis Method ◽  
Global Reliability Sensitivity ◽  
The Impact

The sensitivity index plays a critical role in the design of product and is used to quantify the impact degree of the uncertainty of the input variable to the uncertainty of the interest output. This paper presents a new local reliability sensitivity method and a global reliability sensitivity analysis method of time-dependent reliability problems. Firstly, according to the Poisson's assumption-based first-passage method, the local reliability sensitivity index is directly obtained by calculating the partial derivative of the failure probability to the distribution parameters of input random variable. Then, the moment-independent global reliability sensitivity index of the time-dependent problems is derived based on the concept of moment-independent. Finally, the efficiency and accuracy of the proposed method are verified with the reference results of Monte Carlo simulation.

scholarly journals Sensitivity Analysis of Deviation Source for Fast Assembly Precision Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Jianjun Tang ◽  
Xitian Tian ◽  
Junhao Geng
Keyword(s):  
Sensitivity Analysis ◽  
Transformation Method ◽  
Assembly Sequences ◽  
Sensitivity Analysis Method ◽  
Source Dimension ◽  
Assembly Deviation ◽  
The Impact ◽  
Coupling Phenomena ◽  
Assembly Precision

Assembly precision optimization of complex product has a huge benefit in improving the quality of our products. Due to the impact of a variety of deviation source coupling phenomena, the goal of assembly precision optimization is difficult to be confirmed accurately. In order to achieve optimization of assembly precision accurately and rapidly, sensitivity analysis of deviation source is proposed. First, deviation source sensitivity is defined as the ratio of assembly dimension variation and deviation source dimension variation. Second, according to assembly constraint relations, assembly sequences and locating, deviation transmission paths are established by locating the joints between the adjacent parts, and establishing each part’s datum reference frame. Third, assembly multidimensional vector loops are created using deviation transmission paths, and the corresponding scalar equations of each dimension are established. Then, assembly deviation source sensitivity is calculated by using a first-order Taylor expansion and matrix transformation method. Finally, taking assembly precision optimization of wing flap rocker as an example, the effectiveness and efficiency of the deviation source sensitivity analysis method are verified.

A Hierarchical Statistical Sensitivity Analysis Method for Complex Engineering Systems Design

2008 ◽  
Vol 130 (7) ◽  
Author(s):  
Xiaolei Yin ◽  
Wei Chen
Keyword(s):  
Sensitivity Analysis ◽  
Systems Design ◽  
Accurate Solution ◽  
General Situation ◽  
Sensitivity Index ◽  
Engineering Systems ◽  
Top Down ◽  
Complex Engineering ◽  
The Impact ◽  
Complex Engineering Systems

Statistical sensitivity analysis (SSA) is playing an increasingly important role in engineering design, especially with the consideration of uncertainty. However, it is not straightforward to apply SSA to the design of complex engineering systems due to both computational and organizational difficulties. In this paper, to facilitate the application of SSA to the design of complex systems especially those that follow hierarchical modeling structures, a hierarchical statistical sensitivity analysis (HSSA) method containing a top-down strategy for SSA and an aggregation approach to evaluating the global statistical sensitivity index (GSSI) is developed. The top-down strategy for HSSA is introduced to invoke the SSA of the critical submodels based on the significance of submodel performances. A simplified formulation of the GSSI is studied to represent the effect of a lower-level submodel input on a higher-level model response by aggregating the submodel SSA results across intermediate levels. A sufficient condition under which the simplified formulation provides an accurate solution is derived. To improve the accuracy of the GSSI formulation for a general situation, a modified formulation is proposed by including an adjustment coefficient (AC) to capture the impact of the nonlinearities of the upper-level models. To improve the efficiency, the same set of samples used in submodel SSAs is used to evaluate the AC. The proposed HSSA method is examined through mathematical examples and a three-level hierarchical model used in vehicle suspension systems design.

scholarly journals A Novel Sensitivity Analysis Method in Structural Performance of Hydraulic Press

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Peihao Zhu ◽  
Lianhong Zhang ◽  
Rui Zhou ◽  
Lihai Chen ◽  
Bing Yu ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Structural Optimization ◽  
Machine Tools ◽  
Hydraulic Press ◽  
Structural Performance ◽  
Analysis Method ◽  
Design Variables ◽  
Sensitivity Analysis Method ◽  
Strength And Stiffness ◽  
The Impact

Sensitivity analysis plays a key role in structural optimization, but traditional methods of sensitivity analysis in strength and stiffness are time consuming and of high cost. In order to effectively carry out structural optimization of hydraulic press, this paper presents a novel sensitivity analysis method in structural performance of hydraulic press, which saves a great deal of time and design costs. The key dimension parameters of the optimization of design variables, which remarkably impact on the structural performance of hydraulic press, are efficiently selected. The impact order of various sensitivity parameters in strength and stiffness of machine tools is consistent with the sensitivity ranking of regression analysis. The research results provide the basis for the hydraulic machine design and references in research of machine tools and equipment.

scholarly journals The Impact of Temporary Means of Access on Buildings Envelope’s Maintenance Costs

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 601
Author(s):  
Cláudia Ferreira ◽  
Ilídio S. Dias ◽  
Ana Silva ◽  
Jorge de Brito ◽  
Inês Flores-Colen
Keyword(s):  
Sensitivity Analysis ◽  
Building Envelope ◽  
Design Stage ◽  
Maintenance Costs ◽  
Alternative Means ◽  
Tiling Systems ◽  
Maintenance Work ◽  
Surrounding Space ◽  
The Cost ◽  
The Impact

Accessibility to buildings’ envelope depends on efficient inspection and other maintenance actions of their components. When access to these components is not planned, special means of access are required to carry out the maintenance work. Means of access, besides having a fundamental role on the quality of maintenance works of building envelope components, also represents a considerable part of the maintenance costs. Thus, to optimize costs and resources in maintenance plans, assessment of the impact of the means of access on maintenance costs is crucial. For works in height, there are several alternative means of access. The choice of the most adequate solution is strongly linked to the characteristics (e.g., architecture, height) and constraints (e.g., users, surrounding space) of each building, the maintenance needs of the envelope, and the time and funds available for the intervention. Therefore, in this study, a sensitivity analysis to understand how the cost of means of access can influence the maintenance costs is carried out. Moreover, the optimisation of maintenance activities in façade claddings is also analysed. This study intends to assess whether it is advantageous to consider permanent means of access during the design phase or opt for temporary means of access. In a first stage, the impact of six temporary means of access (supported and suspended scaffolds; articulated booms; telescopic booms; scissor lifts; and rope access) on the maintenance plans developed for the six types of claddings (ceramic tiling systems—CTS, natural stone claddings—NSC, rendered façades—RF, painted surfaces—PS, external thermal insulation composite systems—ETICS, and architectural concrete façades—ACF) is examined. The impact is estimated through a stochastic maintenance model based on Petri nets. After that, a sensitivity analysis and a multi-criteria decision analysis are performed. Based on the results, general recommendations are presented concerning the maintenance strategies to adopt in the cladding solutions analysed. The results reveal that planning the means of access during the design stage can be economically beneficial for all buildings’ envelope components.

A Hierarchical Statistical Sensitivity Analysis Method for Complex Engineering Systems

2007 ◽  
Author(s):  
Xiaolei Yin ◽  
Wei Chen
Keyword(s):  
Sensitivity Analysis ◽  
Hierarchical Modeling ◽  
Systems Design ◽  
Accurate Solution ◽  
General Situation ◽  
Sensitivity Index ◽  
Engineering Systems ◽  
Complex Engineering ◽  
The Impact ◽  
Complex Engineering Systems

The method of Statistical Sensitivity Analysis (SSA) is playing an increasingly important role in engineering design, especially with the consideration of uncertainty. However, applying SSA to the design of complex engineering systems is not straight forward due to both computational and organizational difficulties. In this paper, a Hierarchical Statistical Sensitivity Analysis (HSSA) method is developed to facilitate the application of SSA to the design of complex systems especially those follow hierarchical modeling structures. A top-down strategy for HSSA is introduced to only invoke the SSA of critical submodels based on the significance of submodel performances. A simplified formulation of the Global Statistical Sensitivity Index (GSSI) is studied to represent the effect of a lower-level submodel input on a higher-level model response by aggregating the submodel SSA results across intermediate levels. A sufficient condition under which the simplified formulation provides an accurate solution is derived. To improve the accuracy of the GSSI formulation for a general situation, a modified formulation is proposed by including an Adjustment Coefficient (AC) to capture the impact of the nonlinearities of the upper level models. To save cost, the evaluation of the AC shares the same set of samplings used in the submodel SSA. The proposed HSSA method is examined through mathematical examples and a 3-level hierarchical model used in vehicle suspension systems design.

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