We discuss Kriging Interpolation on high-performance computers as a method for spatial data interpolation. We analyse algorithms for implementing Kriging on high-performance and distributed architectures. In addition to a number of test problems, we focus on an application of comparing rainfall measurements with satellite imagery. We discuss our hardware and software system and the resulting pe...

In the present paper an adaptive Kriging surrogate model with active refinement is proposed to solve component reliability analysis problems (i.e. with a single design point) with a reasonable limit for the dimensionality of the basic random variables space. The model uses an adaptive Kriging-based trust region method to search for the design point and predict the failure probability based on t...

Truncated Gaussian simulation (TGS) and plurigaussian simulation (PGS) are widely accepted methods for generating realisations of geological domains (lithofacies) that reproduce contact relationships. The realisations can be used to evaluate transfer functions related to the lithofacies occurrence, the simplest ones of which are the probability of occurrence of each lithofacies and the most pro...

Spatial information surveyed by photogrammetry, airborne LiDAR and Mobile Measurement System (MMS) above ground level can be analyzed by scientists using standard geostatistical methodologies such as ordinary Kriging and sequential Gaussian simulation to interpolate heterogeneities of profiles from sparse sample data. Proven effective by researchers, the Kriging algorithm model is used by comme...

Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a sche...

We evaluate the performance of a numerical method for global optimization of expensive functions. The method is using a response surface to guide the search for the global optimum. This metamodel could be based on radial basis functions, kriging, or a combination of different models. We discuss how to set the cyclic parameters of the optimization method to get a balance between local and global...

This paper proposes a new interpolation method based on Kohonen self-organizing networks. This method performs very well, combining an accuracy comparable with usual optimal methods (kriging) with a shorter computing time, and is especially efficient when a great amount of data is available. Under some hypothesis similar to those used for kriging, unbiasness and optimality of neural interpolati...

The numerical simulation of eddy-current non-destructive testing methods involves high complexity and expensive computational load. However, one needs to reach reliable solutions for these problems in order to be able, in particular, to solve the related inverse problem. To overcome this difficulty a new approach recently appeared. The main idea here is to build a problem-specific database (for...

When analyzing data from computationally expensive simulation codes, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization and optimization. Kriging is a popular surrogate modeling technique used for the Design and Analysis of Computer Experiments (DACE). Hence, the past decade Kriging has been the subject of extensiv...

this study presents a new method for interpolation by use of copula for groundwater quality zoning. in this regard, the data of the concentration of bicarbonate in 87 piezometric wells on the plains of kerman and ravar in september 2013 were examined. for this purpose, four archimedean copula including clayton, frank, gumbel and joe have been used. then, the obtained results were compared to th...