Sensitivity analysis (SA) is an important procedure in engineering design to obtain valuable information about the model behavior to guide a design process. For design under uncertainty, probabilistic sensitivity analysis (PSA) methods have been developed to provide insight into the probabilistic behavior of a model. In this paper, the goals of PSA at different design stages are investigated. I...

This paper investigates the commonly overlooked “sensitivity” of sensitivity analysis (SA) to what we refer to as parameter “perturbation scale”, which can be defined as a prescribed size of the sensitivityrelated neighbourhood around any point in the parameter space (analogous to step size Dx for numerical estimation of derivatives). We discuss that perturbation scale is inherent to any (local...

The problem of choosing the variable parameters a stabilizer an object which minimize additive quadratic integral functional reflecting complex requirements for closed stabilization system is considered. To solve combined method parametric synthesis stabilizer, sequential combination Sobol grid and Nelder-Mead method, proposed. At first stage by applying Sobolev working point in pace its transf...

This paper deals with the sensitivity analysis (SA) of inventory management models when uncertainty in the input parameters is given full consideration. We make use of Sobol’ function and variance decomposition method for determining the most influential parameters on the model output. We first illustrate the method by means of an analytical example. We provide the expression of the global impo...

The distributions of endophytic bacteria in Alopecurus aequalis Sobol and Oxalis corniculata L. grown in soils contaminated with different levels of polycyclic aromatic hydrocarbons (PAHs) were investigated with polymerase chain reaction followed by denaturing gradient gel electrophoresis technology (PCR-DGGE) and cultivation methods. Twelve types of PAHs, at concentrations varying from 0.16 to...

Global sensitivity analysis provides insight into how sources of uncertainty contribute to in predictions computational models. indices, also called variance-based indices and Sobol are most often computed with Monte Carlo methods. However, when the model is computationally expensive only a small number samples can be generated, that is, so-called small-data settings, usual estimates may lack s...

With the rapid development of mobile communication technology, design phones has become more complex, and research on electromagnetic radiation from that reaches human head important. Therefore, first all, a model phone daily use was established. Then, based established simulation model, safety exposure to evaluated. The generalized polynomial chaos (gPC) method used establish proxy specific ab...