Software

These computer codes are free software provided by SSRG under the terms of the GNU General Public License (http://www.gnu.org/licenses/).

	Cross-entropy-based Adaptive Importance Sampling Using Gaussian Mixture Developer: Ryan H.Y. Wong (currently working at AECOM in Hong Kong) What it does: Perform adaptive importance sampling for component and system reliability problems using the “Cross-entropy-based Adaptive Importance Sampling Using Gaussian Mixture” (Kurtz and Song 2013). Purpose of development: Undergraduate research to develop free computer codes for state-of-the-art algorithms (sponsored by the Department of Civil and Environmental Engineering at UIUC). Reference: N. Kurtz and J. Song, “Cross-entropy-based Adaptive Importance Sampling Using Gaussian Mixture,” Structural Safety, Vol. 42, pp. 35-44, 2013. Download: HERE (The “accepted author manuscript” of the paper is included) How to use: Unzip the file into a local folder and set paths. Run an input file (see the examples and input file template). Then, run “ceaisgm.m”. Read “CEAISGM.txt” for more details.
	Sequential Conditioned Importance Sampling Developers: Young Joo Lee (currently at Ulsan National Institute of Science and Technology) and Junho Song What it does: Evaluates multinormal probabilities using the “Sequential Conditioned Importance Sampling” (Ambartzumian et al. 1998) through a vectorized (i.e. improved efficiency) Matlab code. Purpose of development: Research on identifying critical sequence of failures induced by fatigue crack growth and quantifying the risk of system collapse. Reference: R. Ambartzumian, A. Der Kiureghian, V.Ohanian, and H.Sukiasian, “Multinormal Probability by Sequential Conditioned Importance Sampling,” Probabilistic Engineering Mechanics, Vol.13, No.4, pp.299-308, 1998. Download: HERE
	FERUM toolbox for Matrix-based System Reliability (MSR) Analysis Developer: Bora Gencturk (currently at University of Houston) What it does: Computes the system failure probability and its parameter sensitivities (with respect to parameters that do not affect the correlation coefficients between components) using the MSR method (Song and Kang, 2009) How to use: (a) Standalone mode: the user provides the component failure probabilities (and sensitivities) and correlation coefficient matrix for direct MSR analysis; and (b) FERUM toolbox mode: the user provides input data for first order component reliability analyses by FERUM. The code collects the calculated component failure probabilities (and sensitivities) and calculate the correlation coefficient matrix to perform MSR analysis. A detailed manual written by the developer (Bora Gencturk) is enclosed. Purpose of development: Final term project of CEE491: Decision and Risk Analysis at the University of Illinois, Urbana-Champaign (Spring 2008). Disclaimer: This is an open-source code provided to promote education and research, and may contain methods under further development. Reference: J. Song, and W.H. Kang, “System Reliability and Sensitivity under Statistical Dependence by Matrix-based System Reliability Method,” Structural Safety, Vol.31, No.2, pp.148-156, 2009. Download: HERE
	More computer codes coming soon… including an open-source code for Sequential Compounding Method (SCM; Kang and Song, 2010).