Learn More
Realistic representation of stochastic inputs associated with various sources of uncertainty in the simulation of fluid flows leads to high dimensional representations that are compu-tationally prohibitive. We investigate the use of adaptive ANOVA decomposition as an effective dimension–reduction technique in modeling steady incompressible and com-pressible(More)
Keywords: Compressive sensing Generalized polynomial chaos Chebyshev probability measure High-dimensions a b s t r a c t We consider elliptic stochastic partial differential equations (SPDEs) with random coefficients and solve them by expanding the solution using generalized polynomial chaos (gPC). Under some mild conditions on the coefficients, the(More)
Hierarchical uncertainty quantification can reduce the computational cost of stochastic circuit simulation by employing spectral methods at different levels. This paper presents an efficient framework to simulate hierarchically some challenging stochastic circuits/systems that include high-dimensional subsystems. Due to the high parameter dimensionality, it(More)
Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of(More)
Process variations are a major concern in today's chip design since they can significantly degrade chip performance. To predict such degradation, existing circuit and MEMS simulators rely on Monte Carlo algorithms, which are typically too slow. Therefore, novel fast stochastic simulators are highly desired. This paper first reviews our recently developed(More)
OBJECTIVE Lyme disease and Human granulocytic anaplasmosis are tick-borne diseases caused by Borrelia burgdorferi and Anaplasma phagocytophilum respectively. We have investigated infection and co-infection of the two diseases in the population of forest areas of eight provinces in China by measuring seroprevalence of antibodies against B. burgdorferi and A.(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. [1] Sensor placement at the extrema of empirical orthogonal functions (EOFs)(More)
It is shown in literature that sensor placement at the extrema of Proper Orthogonal Decomposition (POD) modes is efficient and leads to accurate reconstruction of the field of quantity of interest (velocity, pressure, salinity, etc.) from a limited number of measurements in the oceanography study. In this paper, we extend this approach of sensor placement(More)