Uncertainty quantification (UQ) in complex multiphase computational fluid dynamics (CFD) codes is needed to determine the effect of uncertainty in input parameters, boundary conditions, and theoretical sub-models on the numerical results provided by these codes. One of the most often applied and successful methods to quantify uncertainty from a probabilistic point of view, is the polynomial chaos (PC) method.
Polynomial chaos methods (PC) have been developed both by reformulating a set of equations in order to obtain a system of coupled equations to evaluate the strength of the PC modes (the so-called intrusive approach), and by using deterministic or random sampling of the original deterministic model to evaluate the PC modes from the outputs of an existing numerical implementation of the model (the non-intrusive approach). The application of intrusive UQ to multiphase codes such as MFIX (Multiphase Flow with Interphase eXchanges) for gas-solids flows is prohibitive due to the complexity of the underlying model equations and the time-dependent nature of the output.
This project will develop a PC non-intrusive approach to implement UQ in MFIX. This methodology will generate a set of samples from the output results of the original model. For each sample, a PC expansion as a function of the uncertain parameter is determined, and the expectation for the Galerkin projection is determined by considering all the samples under consideration.
The goal of the University Coal Research (UCR) Program within the Department of Energy (DOE) National Energy Technology Laboratory (NETL) is to further the understanding of coal utilization. Since the program’s inception in 1979, its primary objectives have been to (1) improve understanding of the chemical and physical processes involved in the conversion and utilization of coal in an environmentally acceptable manner, (2) maintain and upgrade the coal research capabilities of and facilities at U.S. colleges and universities, and (3) support the education of students in the area of coal science.
The National Energy Technology Laboratory’s (NETL) Office of Coal and Power Systems supports the development of innovative, cost-effective technologies for improving the efficiency and environmental performance of advanced coal and power systems. One current focus area facilitates research to simulate the complex processes that occur within a coal gasifier or across an entire coal based chemical or power plant. This research helps scientists and engineers better understand the fundamental steps in these processes so they can more efficiently optimize coal and power system design.
Iowa State University has won a competitive award through the UCR program and will partner with NETL to develop uncertainty quantification (UQ) tools for multiphase gas-solid flow simulations using the open source code Multiphase Flow with Interphase eXchanges (MFIX) developed by NETL.
Multiphase flow is prevalent in fossil-fuel processes such as coal gasifiers and reactors used for sorbent-based carbon dioxide (CO2) capture. In spite of widespread use and success of computer simulation for design and optimization of multiphase reactors, the current state-of-the-art in computer simulation approaches usually fall short in the crucial aspect of providing objective or statistically meaningful confidence levels for the predicted results. This project will develop and implement an efficient non intrusive UQ method for gas-solids flow simulations, allowing for error estimation and sampling requirements for UQ analysis. These studies and the new UQ procedure will contribute to the design and deployment of more efficient and environmentally benign power generation systems, by reducing the amount of uncertainty that must currently be factored into the design of multiphase coal fired power generation equipment and systems. Lowering design uncertainty factors will result in lower equipment and operating costs of these systems.
Goals and Objectives
The overall objective of the project is to develop a non-intrusive UQ approach based on the PC methodology together with reconstruction of the multivariate probability density function required by the approach, and to apply it to the uncertainty quantification in multiphase gas-solids flow simulations. The work is further divided into the following specific objectives:
Formulate a robust, non-intrusive, quadrature-based UQ approach and develop an efficient, multivariate, quadrature algorithm to reconstruct the probability density function required to evaluate the PC expansion.
Implement the quadrature-based procedure into MFIX, and develop the automation tools to prepare the UQ test-cases and process the results.
Apply the developed quadrature-based UQ procedure to investigate the propagation of uncertainty from selected input parameters onto relevant quantities computed in the simulation of bubbling fluidized beds and riser flows using the MFIX code.
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