In this paper we study the ability of the Cokriging method to represent functions with multiple local minima and sharp discontinuities for use in the multidimensional design of a low-boom supersonic business jet wing-body-canard configuration. Cokriging approximation models are an extension of the original Kriging method which incorporate secondary information such as the values of the gradient...

The Kriging method is an interpolation scheme that can be used for modeling deter-ministic computer analyses as the realization of a stochastic process. The technique has been recognized as an alternative to the traditional Response Surface method in generating approximation models of computationally expensive CFD analyses. This is due to its ability to interpolate sample data and to model a fu...

We propose a new framework for design under uncertainty based on stochastic computer simulations and multi-level recursive co-kriging. The proposed methodology simultaneously takes into account multi-fidelity in models, such as direct numerical simulations versus empirical formulae, as well as multi-fidelity in the probability space (e.g. sparse grids versus tensor product multi-element probabi...

     Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolation of spatially referenced data and the prediction of v...

This paper concentrates on the computational challenge in multidisciplinary design optimization (MDO) and a comprehensive strategy combining enhanced collaborative optimization (ECO) and kriging approximation models is introduced. In this strategy, the computational and organizational advantages of original collaborative optimization (CO) are inherited by ECO, which can satisfy the strengthened...

Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolat...

nowadays, air pollution in cities with regard to its harmful outcomes has been turned into one of the serious challenges in urban management. pollutants as carbon monoxide, sulfur dioxide, and the aerosols that are known to be among the most important factors related to heart, vascular, and lung disease, have underlined public welfare and health, and the organizations concerned with community h...

Kriging (Gaussian process, spatial correlation) metamodels approximate the Input/Output (I/O) functions implied by the underlying simulation models; such metamodels serve sensitivity analysis and optimization, especially for computationally expensive simulations. In practice, simulation analysts often know that the I/O function is monotonic. To obtain a Kriging metamodel that preserves this kno...

We have developed a domain agnostic ordinary kriging algorithm accessible via a standardsbased service-oriented architecture for sensor networks. We exploit the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards. We need on-demand interpolation maps so runtime performance is a major priority. Our sensor data comes from wind in-situ observation stations in an area approximate...