Imperial College London
Alternate

DrSergeiKucherenko

Faculty of Engineering, Department of Chemical Engineering

Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 6624s.kucherenko Website

 
 
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Location

 

Centre for Process Systems(C505)Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

52 results found

Sobol' IM, Kucherenko S, 2010, Derivative based global sensitivity measures, Procedia - Social and Behavioral Sciences, Vol: 2, Pages: 7745-7746, ISSN: 1877-0428

We introduce new global sensitivity measures called derivative based global sensitivity measures (DGSM). We also show that there is a link between DGSM and Sobol' total sensitivity indices which makes this approach theoretically sound and general. It can be seen as the generalization of the Morris method. The computational time required for numerical evaluation of DGSM can be much lower than that for estimation of the Sobol' sensitivity indices although it is problem dependent. The efficiency of the method can be further improved by using the automatic differentiation algorithm for calculation DGSM.

Journal article

Sobol IM, Kucherenko S, 2010, A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices, COMPUTER PHYSICS COMMUNICATIONS, Vol: 181, Pages: 1212-1217, ISSN: 0010-4655

Journal article

Kiparissides A, Kucherenko SS, Mantalaris A, Pistikopoulos ENet al., 2009, Global Sensitivity Analysis Challenges in Biological Systems Modeling, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 48, Pages: 7168-7180, ISSN: 0888-5885

Journal article

Kucherenko S, Rodriguez-Fernandez M, Pantelides C, Shah Net al., 2009, Monte Carlo evaluation of derivative-based global sensitivity measures, 5th International Conference on Sensitivity Analysis of Model Output (SAMO 2007), Publisher: ELSEVIER SCI LTD, Pages: 1135-1148, ISSN: 0951-8320

Conference paper

Sobol IM, Kucherenko S, 2009, Derivative based global sensitivity measures and their link with global sensitivity indices, MATHEMATICS AND COMPUTERS IN SIMULATION, Vol: 79, Pages: 3009-3017, ISSN: 0378-4754

Journal article

Gatelli D, Kucherenko S, Ratto M, Tarantola Set al., 2009, Calculating first-order sensitivity measures: A benchmark of some recent methodologies, 5th International Conference on Sensitivity Analysis of Model Output (SAMO 2007), Publisher: ELSEVIER SCI LTD, Pages: 1212-1219, ISSN: 0951-8320

Conference paper

Feil B, Kucherenko S, Shah N, 2009, Comparison of Monte Carlo and Quasi Monte Carlo Sampling Methods in High Dimensional Model Representation, 1st International Conference on Advances in System Simulation, Publisher: IEEE, Pages: 12-+

Conference paper

Kiparissides A, Rodriguez-Fernandez M, Kucherenko S, Mantalaris A, Pistikopoulos Eet al., 2008, Application of Global Sensitivity Analysis to Biological Models, 18th European Symposium on Computer Aided Process Engineering (ESCAPE-18), Publisher: ELSEVIER SCIENCE BV, Pages: 689-694, ISSN: 1570-7946

Conference paper

Kucherenko S, Belotti P, Liberti L, Maculan Net al., 2007, New formulations for the kissing number problem, 3rd Cologne/Twente Workshop on Graphs and Combinatorial Optimization, Publisher: ELSEVIER, Pages: 1837-1841, ISSN: 0166-218X

Conference paper

Sobol IM, Tarantola S, Gatelli D, Kucherenko SS, Mauntz Wet al., 2007, Estimating the approximation error when fixing unessential factors in global sensitivity analysis, RELIABILITY ENGINEERING & SYSTEM SAFETY, Vol: 92, Pages: 957-960, ISSN: 0951-8320

Journal article

Rodriguez-Fernandez M, Kucherenko S, Pantelides C, Shah Net al., 2007, Optimal experimental design based on global sensitivity analysis, 17th European Symposium on Computer Aided Process Engineering (ESCAPE-17), Publisher: ELSEVIER SCIENCE BV, Pages: 63-68, ISSN: 1570-7946

Conference paper

Sobol IM, Kucherenko SS, 2005, On Global sensitivity analysis of quasi-Monte Carlo algorithms, Monte Carlo Methods and Applications, Vol: 11, Pages: 83-92, ISSN: 0929-9629

Different Quasi-Monte Carlo algorithms corresponding to the same Monte Carlo algorithm are considered. Even in the case when their constructive dimensions are equal and the same quasi-random points are used, the efficiencies of these algorithms may differ. Global sensitivity analysis provides an insight into this situation. As a model problem two well-known approximations of a Wiener integral are considered: the standard one and the Brownian bridge. The advantage of the Brownian bridge is confirmed. © VSP 2005.

Journal article

Kucherenko S, Sytsko Y, 2005, Application of deterministic low-discrepancy sequences in global optimization, COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, Vol: 30, Pages: 297-318, ISSN: 0926-6003

Journal article

Sobol IM, Kucherenko SS, 2005, On global sensitivity analysis of quasi-Monte Carlo algorithms, Monte Carlo Methods and Applications, Vol: 11, ISSN: 0929-9629

Journal article

Liberti L, Maculan N, Kucherenko S, 2004, The Kissing Number Problem: A New Result from Global Optimization, Electronic Notes in Discrete Mathematics, Vol: 17, Pages: 203-207, ISSN: 1571-0653

Determining the maximum number of D-dimensional spheres of radius r that can be adjacent to a central sphere of radius r is known as the Kissing Number Problem (KNP). The problem has been solved for 2 and 3 dimensions. The smallest open case is 4 dimensions: a solution with 24 spheres is known, and an upper bound of 25 has been found. We present a new nonlinear mathematical programming model for the solution of the KNP. This problem is solved using a quasi Monte Carlo variant of a multi level single linkage algorithm for global optimization. The numerical results indicate that the solution of the KNP is 24 spheres, and not 25. © 2004 Elsevier B.V. All rights reserved.

Journal article

Hung WY, Kucherenko S, Samsatli NJ, Shah Net al., 2004, A flexible and generic approach to dynamic modelling of supply chains, JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, Vol: 55, Pages: 801-813, ISSN: 0160-5682

Journal article

Hung WY, Kucherenko S, Samsatli NJ, Shah Net al., 2003, An efficient sampling technique for stochastic supply chain simulations

To enable a fair comparison of various supply chain initiatives, realistic supply chain simulation models need to capture the system dynamics and characteristics of individual supply chain members by modelling their physical and business activities. Of equal importance is the need to quantit' the supply chain performance under uncertainty. This requires detailed stochastic models that are usually very high in dimension and thus require extensive computation. In this paper we present an efficient sampling technique to reduce the number of simulations required to obtain accurate performance metrics. Latin Supercube Sampling (LSS) based on Sobol' subsets is applied to generate the sample points for the uncertain variables. Numerical experiments and a case study are used to illustrate the higher efficiency of this sampling method.

Other

Kucherenko SS, Leaver KD, 2000, Modelling effects of surface tension on surface topology in spin coatings for integrated optics and micromechanics, JOURNAL OF MICROMECHANICS AND MICROENGINEERING, Vol: 10, Pages: 299-308, ISSN: 0960-1317

Journal article

Kucherenko S, Pan J, Yeomans JA, 2000, A combined finite element and finite difference scheme for computer simulation of microstructure evolution and its application to pore-boundary separation during sintering, COMPUTATIONAL MATERIALS SCIENCE, Vol: 18, Pages: 76-92, ISSN: 0927-0256

Journal article

Westwood C, Pan JZ, Le HR, Kucherenko S, Crocombe Aet al., 2000, A simplified model for cavity growth along a grain-boundary by coupled surface and grain-boundary diffusion, EUROPEAN JOURNAL OF MECHANICS A-SOLIDS, Vol: 19, Pages: 17-30, ISSN: 0997-7538

Journal article

Pan J, Le H, Kucherenko S, Yeomans JAet al., 1998, A model for the sintering of spherical particles of different sizes by solid state diffusion, ACTA MATERIALIA, Vol: 46, Pages: 4671-4690, ISSN: 1359-6454

Journal article

Pan J, Cocks ACF, Kucherenko S, 1997, Finite element formulation of coupled grain-boundary and surface diffusion with grain-boundary migration, PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 453, Pages: 2161-2184, ISSN: 1364-5021

Journal article

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