This project sets out to resolve the existing challenges in predictive capabilities of two-phase flow and heat transfer by utilizing interface capturing methods and direct numerical simulation to perform state-of-the-art large-scale simulations two-phase flows.

To resolve the difference between lattice and data-driven theory values and compute the total, additional lattice calculations are needed. This team set to attain this goal through two independent groups, Fermilab/MILC and RBC/UKQCD.

Through this INCITE project, a team of researchers proposes to apply quantum Monte Carlo (QMC) methods to provide reliable materials predictions for several classes of quantum materials of tremendous topical interest.

With this INCITE project, the researchers will lead to improvements in the simulation capabilities of atomic nuclei and nuclear matter, and their reactions with neutrinos and electrons.

This INCITE project uses the team's Castro code to carry out high-performance, robust, and accurate simulations to advance our understanding ofXRBs and SN Ia, pushing to model a larger fraction of the neutron star surface.

With this INCITE project, the researchers aim to address the above-mentioned limitations of currently available computational materials databases by vastly extending the range of materials properties such databases contain.

The work in this INCITE project takes a critical step toward understanding the behavior of black holes in the universe.

With this INCITE project, the team will perform the first calculations of radiation-dominated accretion on black holes using full transport methods and realistic opacities.

With this INCITE project, researchers are using new advancements in real-time time-dependent density functional theory (RT-TDDFT) to reliably study high-impact scientific questions associated with the dynamics of electrons and ions in complex heterogeneous systems.

This INCITE project will use and further develop methods of grand canonical global optimization for the discovery of dynamic ensembles in realistic reaction conditions and of global activity sampling, for the determination of the most active configurations of the catalyst.

The work in this INCITE project , directly validated byXFEL, UED and neutron experiments at DOE facilities, will enable future production of high-quality custom quantum material architectures for broad and critical applications to continued U.S. leadership in technology development, thereby addressing DOE Basic Research Needs for Transformative Manufacturing and Quantum Materials.

The researchers from this INCITE project will extract structurally and functionally important relationships among genomic elements from experimental data based on physical principles of 3D chromatin folding, and will generate maps of driver interactomes of 3D chromatin folding for each locus along all chromosomes, providing a concise shortened list of putative causal interactions that can drive 3D chromatin folding.

The high-fidelity data generated with this INCITE allocation will reveal the spectral behaviors of turbulent kinetic energy (TKE) as functions of fluid speed, the strength and direction of the magnetic field, and the wall-normal distances.

With this INCITE project, researchers will use very high spatial-resolution regional-scale climate models to explore the physics underlying the formation and evolution of extremes in precipitation and temperature in the current and future climates under various greenhouse gas emission scenarios

This team utilizes large-scale computational tools to help understand how adequately reduced-order formulations can capture the strong coupling between the fluid mechanics of the gas flow and the transport properties of the high-temperature gas.

The approach for this INCITE project is to characterize the effects of pressure gradient and wall cooling on boundary-layer turbulence and perform a thorough evaluation of the existing turbulence models as well as the models that are currently under development.

Coupling machine learning and physics-based methods, with this work researchers aim to accelerate the slow process of drug discovery, which typically lasts many years and costs billions of dollars—a major weakness in public health emergencies.

With this new INCITE project, this team will conduct not only a full suite of 3D simulations for the spectrum of progenitor stars, but plan to double this long-term effort because of code speed-ups and improvements.

With this INCITE project, the team involved has enhanced the particle-in-cell code OSIRIS to launch lasers with arbitrary spatial-temporal profiles.