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18篇 您的检索式：作者名="ZABARAS Nicholas"

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		题名	作者	年代	出处	被引量
	1	A Bayesian inference approach to the inverse heat conduction problem显示文摘	Jingbo Wang Nicholas Zabaras	2004	International Journal of Heat and Mass Transfer2004，，47：	1
	2	An inverse method for deterring elastic material properties and a material interface显示文摘	Schnur D S Zabaras Nicholas	1992	Int J Num Method Engrg1992，33，：	1
	3	A Bayesian inference approach to the inverse heat conduction problem 显示文摘	WANG Jingbo ZABARAS Nicholas	2004	International Journal of Heat and Mass Transfer2004，，47：	1
	4	Using Bayesian statistics in the estimation of heat source in radiation显示文摘	WANG Jingbo ZABARAS Nicholas	2005	International Journal of Heat and Mass Transfer2005，，48：	1
	5	Shape optimization and preform design in metal forming processes显示文摘	Akkaram Srikanth Nicholas Zabaras		0，，190：	1
	6	A maximum entropy approach for property prediction of random microstructures显示文摘	Nicholas Zabaras	2006	Acta Materialia2006，54，：	1
	7	An Adaptive Hierarchical Sparse Grid Collocation Algorithm for the Solution of Stochastic Differ- ential Equations 显示文摘	Xiang Ma Nicholas Zabaras	2009	Journal of Computational Physics2009，228，：	1
	8	An Adaptive High -dimensional Stochastic Model Representation Technique for the Solution of Stochastic Partial Differential Equations显示文摘	Xiang Ma Nicholas Zabaras	2010	Journal of Compu- tational Physics2010，229，：	1
	9	A thermomechanical study of the effects of mold topography on the solidification of alumi- num alloys显示文摘	LI Jian-tan NICHOLAS ZABARAS	2005	Materials Science and Engineering A2005，404，4：	1
	10	Viscous damping approximation of laminated anisotropic composite plates using the finite element method 显示文摘	NICHOLAS ZABARAS TASNEEM PERVEZ	1990	Computer Methods in Applied Mechanics and Engineering1990，81，3：	1
	11	On the Control of Solidification Using Magnetic Fields and Magnetic Field Gradients显示文摘	Baskar Ganapathysubramanian Nicholas Zabaras	2005	International Journal of Heat and Mass Transfer2005，48，：	1
	12	Using Magnetic Field Gradients to Control the Directional Solidification of Alloys and the Growth of Single Crystals显示文摘	Baskar Ganapathysubramanian Nicholas Zabaras	2004	Journal of Crystal Growth2004，270，：	1
	13	Control of Macrosegregation during the Solidification of Alloys Using Magnetic Fields显示文摘	Baskar Ganapathysubramanian Nicholas Zabaras	2006	International Journal of Heat and Mass Transfer2006，49，：	1
	14	Using Bayesian statistics in the estimation of heat source in radiation 显示文摘	Jingbo Wang Nicholas Zabaras	2005	International Journal of Heat and Mass Transfer2005，48，1：	1
	15	Shape optimization and preform design in metal forming processes显示文摘	Akkaram Srikanth Nicholas Zabaras	2000	Computer Methods in Applied Mechanics and Engineering2000，190，1314：	1
	16	Sensory perception and quality attributes of high pressure processed carrots in comparison to raw, sous-vide and cooked carrots 显示文摘	Ximenita I Trejo Araya Nicholas Smale Dimitrios Zabaras	2009	Innovative Food Science and Emerging Technologies2009，10，：	1
	17	Adaptive Locally Weighted Projection Regression Method for Uncertainty Quantification显示文摘We develop an efficient,adaptive locally weighted projection regression(ALWPR)framework for uncertainty quantification(UQ)of systems governed by ordinary and partial differential equations.The algorithm adaptively selects the new input points with the largest predictive variance and decides when and where to add new localmodels.It effectively learns the local features and accurately quantifies the uncertainty in the prediction of the statistics.The developed methodology provides predictions and confidence intervals at any query input and can dealwithmulti-output cases.Numerical examples are presented to show the accuracy and efficiency of the ALWPR framework including problems with non-smooth local features such as discontinuities in the stochastic space.	Peng Chen Nicholas Zabaras	2013	Communications in Computational Physics2013，14，9：	0
	18	Thermal Response Variability of Random Polycrystalline Microstructures显示文摘A data-driven model reduction strategy is presented for the representation of random polycrystal microstructures.Given a set of microstructure snapshots that satisfy certain statistical constraints such as given low-order moments of the grain size distribution,using a non-linear manifold learning approach,we identify the intrinsic low-dimensionality of the microstructure manifold.In addition to grain size,a linear dimensionality reduction technique(Karhunun-Lo´eve Expansion)is used to reduce the texture representation.The space of viable microstructures is mapped to a low-dimensional region thus facilitating the analysis and design of polycrystal microstructures.This methodology allows us to sample microstructure features in the reduced-order space thus making it a highly efficient,low-dimensional surrogate for representing microstructures(grain size and texture).We demonstrate the model reduction approach by computing the variability of homogenized thermal properties using sparse grid collocation in the reduced-order space that describes the grain size and orientation variability.	Bin Wen Zheng Li Nicholas Zabaras	2011	Communications in Computational Physics2011，10，8：	0

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