Between-subject and within-subject variability is ubiquitous in biology and physiology, and understanding and dealing with this is one of the biggest challenges in medicine. At the same time, it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a ma...

In this article, a novel method for the extension of sample size in Latin Hypercube Sampling (LHS) is suggested. The method can be applied when an initial LH design is employed for the analysis of functions g of a random vector. The article explains how the statistical, sensitivity and reliability analyses of g can be divided into a hierarchical sequence of simulations with subsets of samples o...

Thermodynamic models and experimental data exhibit the usual systematic and random errors. The severity of their errors depends on their use, such as for process calculations in a process simulator. Similarly, the value of better thermodynamic models andror data should be measured with reference to such use. We have developed techniques for quantification of such thermodynamic-induced process u...

Abstract. It is shown how an arbitrary set of points in the hypercube can be Latinized, i.e., can be transformed into a point set that has the Latin hypercube property. The effect of Latinization on the star discrepancy and other uniformity measures of a point set is analyzed. For a few selected but representative point sampling methods, evidence is provided to show that Latinization lowers the...

Response surface approximations offer an effective way to solve complex problems. However limitations on computational expense pose restrictions to generate ample data and a simple model is typically used for approximation leaving the possibility of errors due to insufficient model known as bias errors. This paper presents a method to estimate pointwise RMS bias errors in response surface model...

Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF tech...

production planning of an open-pit mine is a procedure during which the rock blocks are assigned to different production periods in a way that leads to the highest net present value (npv) subject to some operational and technical constraints. this process becomes much more complicated by incorporation of the uncertainty existing in the input parameters. the commodity price uncertainty is among ...

We study the performance of alternative sampling methods for estimating multivariate normal probabilities through the GHK simulator. The sampling methods are randomized versions of some quasi-Monte Carlo samples (Halton, Niederreiter, Niederreiter-Xing sequences and lattice points) and some samples based on orthogonal arrays (Latin hypercube, orthogonal array and orthogonal array based Latin hy...

The hydraulic and acoustic performance of centrifugal pumps are interrelated contradictory in structure design. An optimization design method a volute based on radial basis function (RBF) neural network genetic algorithm (GA) is proposed to solve this problem. efficiency total sound pressure level the pump used as objectives. diameter base circle, width installation angle tongue, height diffuse...

To improve the safety, reliability, and performance of complex engineering systems, it is crucial to understand quantify uncertainties. This paper presents a framework non-intrusively semi-analytically parametric uncertainty within CFD simulations using Bayesian quadrature (BQ). An in-house quantification (UQ) code based upon this mathematical developed. The then validated by applying due varyi...