Abstract: The increase of computing capabilities promises to address many scientific and engineering problems by enabling simulations to reach new levels of accuracy and scale. The field of uncertainty quantification (UQ) has recently been receiving an increasing amount of attention as it enables reliability study of modelled systems. However, performance of UQ analysis for high-fidelity simulations remains challenging due to exceedingly high complexity of computational workflows. In this paper, we present a UQ study on a complex workflow targeting a thermally stratified flow. We discuss different models that can be used to enable it. We then propose an abstraction at the level of the workflow specification that enables the modeller to quickly switch between UQ models and manage underlying compute infrastructure in a completely transparent way. We show that we can keep the workflow description almost unchanged while benefitting of all the insight the UQ study provides.

Abstract: We propose methods to eliminate redundant utility assessments in decision analysis applications. We abstract a set of utility assessments such that the set is represented as a matrix of ternary arrays. To achieve efficiency, arrays converted to decimal numbers for further processing. The resulting approach demonstrates excellent performance on random sets of utility assessments. The method eliminates the redundant questions for the decision maker and can serve for consistency check.

Abstract: In this paper, we propose an algorithm for designing a cryptosystem, in which the derivative disproportion functions are used. The symbols to be transmitted are encoded with the sum of at least two of these functions combined with random coefficients. A new algorithm is proposed for decoding the received messages by making use of important properties of the derivative disproportion functions. Numerical experiments are demonstrating the algorithm’s reliability and robustness.

Abstract: We study the effects of merging two separate markets each originally monopolized by a producer into a globalized duopoly market. We consider a linear inverse demand with cap price and quadratic cost functions. After globalization, we find the consistent conjectural variations equilibrium (CCVE) of the duopoly game. Unlike in the Cournot equilibrium, a complete symmetry (identical cost functions parameters of both firms) does not imply the strongest coincident profit degradation. For the situation where both agents are low-marginal cost firms, we find that the company with a technical advantage over her rival has a better ratio of the current and previous profits. Moreover, as the rival becomes ever weaker, that is, as the slope of the rival’s marginal cost function increases, the profit ratio improves.

Abstract: The element of the epistemic uncertainty quantification concerning the estimation of the approximation error is analyzed from the viewpoint of the ensemble of numerical solutions obtained via independent numerical algorithms. The analysis is based on the geometry considerations: the triangle inequality and measure concentration in spaces of great dimension. In result, the feasibility for nonintrusive postprocessing appears that provides the approximation error estimation on the ensemble of the solutions. The ensemble of numerical results obtained by five OpenFOAM solvers is analyzed. The numerical tests were made for the inviscid compressible flow around a cone at zero angle of attack and demonstrated the successful estimation of the approximation error.