For this, traditional engineering simulations and uncertainty handling by soft computing have been combined in a novel approach with knowledge management paradigms.
The performance of PLHS is compared with benchmark sampling strategies across multiple case studies for Monte Carlo simulation, sensitivity and uncertainty analysis.
They serve as basic elements and structures in varied fields of Metrology (chemical analysis, environmental investigation, medical imaging, particle observation, flow measurement, surveying), for modelling, description, simulation, error and uncertainty analysis, reconstruction, filtering, verification, and so on.
The study case highlights various aspects related to the conception of flexible projects, such as proper choice of design variables and identification of the potential of the flexibility, and it shows that the methodology is suitable for a decision-making process that integrates simulation modeling and uncertainty analysis.
The results of unfolding simulations must also be considered qualitative as general-purpose force-field parameters have been optimized only for room temperature simulations, and uncertainties may arise with regards to the dynamics of proteins at higher temperature conditions.
Increasing the number of samples will increase the accuracy of the summary statistics for the simulation and their uncertainty interval (but it will not decrease the uncertainty interval itself).
For this purpose, Crystal Ball software was found very suitable for performing Monte-Carlo simulation and estimating uncertainty; thus it was used for the random sampling from the probability density functions that were chosen for the contributing parameters according to the adopted entry capacity model of non-linear features.
Work is on-going to further expand the capabilities of the model, including 3D simulations, vertical cylinders, and uncertainty quantification.
The model accounts for variability among individuals (as it is a patient-level simulation), and also the uncertainty of key parameters (by performing a probabilistic sensitivity analysis).
The kwall, katt, and ksc calculation values and simulation uncertainty analysis for INER's HDR Ir primary standard chamber are listed in Table 1. Figure 7(a) illustrates the wall correction factors and the related parameters of INER's spherical graphite-wall cavity chamber, kwall, katt, and ksc, as functions of the incident photon energy.
