Session P05: Reacting Flows: Computational Methods (3:10pm - 3:55pm CST)

A Discrete Adjoint-Based Method for High-Fidelity Simulations of Turbulent Reacting Flows

In recent years, direct numerical simulation (DNS) and large-eddy simulation (LES) have gained in popularity for simulating turbulent reacting flows within the scientific and engineering community. However, due to their high computational cost, they have mainly been employed to investigate micro-scale physics or develop new sub-grid scale models. Meanwhile, using such approaches for design or optimization requires performing many simulations. Adjoint-based methods provide local sensitivity to a quantity of interest to a potentially large number of parameters without requiring repeated simulations. However, special care needs to be taken when employing adjoint methods to turbulent reacting flows. In this talk, we present a discrete adjoint method with attention paid to ensure the method retains desirable properties of the forward solution, i.e. boundedness, accuracy, and robustness. The method is implemented using high-order finite difference operators coupled with tabulated chemistry. An adaptive discretization scheme is presented to ensure scalar boundedness. Tabulated chemistry allows for chemical mechanisms to be varied without requiring reformulation and implementation of the adjoint equations. The approach is demonstrated on a series of cases with varying complexity.   

Prediction method for ignition delay time of liquid spray combustion in constant volume chamber

A prediction method, known as the Coupled Time Scale (CTS) method, is proposed in the current work to estimate the ignition delay time (IDT) of liquid spray combustion by performing an inert spray simulation and a zero-dimensional (0-D) homogeneous reactor (HR) simulation. The method builds upon the assumption that if the majority of the vapor regions in a spray has composition close to the most reactive mixture fraction, then these regions will have a high probability to undergo high-temperature ignition and ultimately leading to autoignition in spray. The proposed method is applied to estimate high-temperature IDT of \textit{n}-dodecane sprays at three ambient temperatures ($T_\mathrm{am}$) of 800, 900, and 1000K, as well as for two nozzle diameters ($D_\mathrm{noz}$) of $90$ and $186\mu$m. The fidelity of the proposed CTS method is verified by comparing the predicted IDT against CFD simulated IDT and measured IDT. Comparison of the estimated IDT from the CTS method to measured IDT yields a maximum relative difference of 24\%. Meanwhile, a maximum relative difference of 33\% is obtained between the IDT computed from the CTS method and the computed IDT from the large eddy simulations of the associated reacting sprays across the different $T_\mathrm{am}$ and $D_\mathrm{noz}$   

Hidden Species in Passive and Reactive Transport Equations: An On-the-fly Reduced Order Modeling Strategy

This presentation addresses one of the principal barrier in developing accurate and tractable predictive models in turbulent reactive flows which is solving large number of chemical species that can be computationally impracticable. We present an \emph{on-the-fly} reduced order model, inspired by the dynamically bi-orthonormal decomposition (DBO) to solve reactive flow as well as passive scalar problems. The presented approach seeks a low-rank decomposition of the species to three time-dependent components: (i) a set of orthonormal spatial modes, (ii) a low-rank factorization of the instantaneous species correlation matrix, and (iii) a set of uncorrelated species. In the proposed approach, unlike data-driven dimension reduction techniques, there is no need to solve the full-dimensional species to generate high-fidelity data. Instead, the low-rank components are directly extracted from the species transport equation and closed-form evolution equations for the three components are derived. The time-dependence of the three components enables an on-the-fly adaptation of the low-rank approximation to transient changes in the species.