Simulations of combustion and reacting flows often encounter stiffness in the equations governing chemical kinetics. Explicit solvers for these ordinary differential equations offer low computational expense, but typically cannot efficiently handle stiff systems. In contrast, implicit methods demand greater expense but offer unconditional stability—as a result, most reactive-flow solvers rely...
We develop the theory of degenerate and nonlinear evolution systems in mixed formulation.
It will be shown that many of the well-known results for the stationary problem extend to
the nonlinear case and that the dynamics of a degenerate Cauchy problem is governed by a nonlinear
semigroup. The results are...
Heterogeneous porous material represents a persistent challenge in the field of engineering. Microscale properties such as the porosity and microchannel torturosity significantly control the macroscale transport characteristics of homogeneous porous medium. Additional complexity is introduced when these small-scale features vary in space. Examples of heterogeneous porous systems include artificial body...
Accurately predicting key combustion phenomena in reactive-flow simulations, e.g., lean blow-out, extinction/ignition limits and pollutant formation, necessitates the use of detailed chemical kinetics. The large size and high levels of numerical stiffness typically present in chemical kinetic models relevant to transportation/power-generation applications make the efficient evaluation/factorization of the chemical kinetic...
Aqueous, two-phase systems (ATPSs) may form upon mixing two solutions of independently water-soluble compounds. Many separation, purification, and extraction processes rely on ATPSs. Predicting the miscibility of solutions can accelerate and reduce the cost of the discovery of new ATPSs for these applications. Whereas previous machine learning approaches to ATPS...
Small hydrocarbon particles such as soot and soot precursors pose a serious threat to human health and Earth's climate. Understanding the mechanisms by which soot particles form and grow is the first step to reducing the prevalence of these particles. Computational simulations are used to investigate combusting systems which are...
Null networks are a type of random graph that is favored for the analysis of a wide variety of real-world networks, including gene-regulatory networks, food webs, and species co-occurrence matrices. As a hypothesis-generating tool, null networks are invaluable because they can reveal network motifs and unusual large-scale properties of networks...
Intensified diurnal tides are found along portions of the Oregon shelf (U.S. West Coast) based on analyses
of high-frequency (HF) radar surface current data and outputs of a 1-km resolution ocean circulation model.
The K₁ tidal currents with magnitudes near 0.07 m s⁻¹ over a wider part of the shelf...
A variety of important machine learning applications require predictions on test data with different characteristics than the data on which a model was trained and validated. In particular, test data may have a different relative frequency of positives and negatives (i.e., class distribution) and/or different mislabeling costs of false positive...