We have significant accomplishments on uncertainty quantification in inverse problems for dynamical systems, generalized sensitivity and optimal design of experiments, elasticity and viscoelasticity modeling for buried target detection, and general inverse problem methodology for proliferating populations. Our efforts have continued on development of efficient accurate integration of Fokker Pla...

Stochastic Satisfiability Modulo Theories (SSMT) is a quantitative extension of Satisfiability Modulo Theories (SMT) inspired by stochastic logics. It extends SMT by randomized quantifiers, facilitating capture of stochastic game properties in the logic, like reachability analysis of hybrid-state Markov decision processes. Solving SSMT formulae with quantification over finite and thus discrete ...

A computational methodology is developed to efficiently perform uncertainty quantification for fluid transport in porous media in the presence of both stochastic permeability and multiple scales. In order to capture the small scale heterogeneity, a new mixed multiscale finite element method is developed within the framework of the heterogeneous multiscale method (HMM) in the spatial domain. Thi...

This paper evaluates the economic feasibility of a small/medium-scale cosmetic initiative in typical Brazilian city. The sector is very promising for investors, particularly when e-commerce platforms are designed, as virtual sales new trend sector. Therefore, required costs to implement an platform considered guarantee demand factory’s productive capacity. While deterministic analysis might pro...

In this paper, a physics-oriented stochastic kinetic scheme will be developed that includes random inputs from both flow and electromagnetic fields via hybridization of Galerkin collocation methods. Based on the BGK-type relaxation model multi-component Boltzmann equation, scale-dependent central-upwind flux function is designed in physical particle velocity space, governing equations discrete ...

Gaseous flows show a diverse set of behaviors on different characteristic scales. Given the coarse-grained modeling in theories fluids, considerable uncertainties may exist between flow-field solutions and real physics. To study emergence, propagation evolution from molecular to hydrodynamic level poses great opportunities challenges develop both sound reliable multi-scale numerical algorithms....