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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Convergence Criteria for Multiphysics Simulations

The behavior of engineered systems is often influenced by multiple physical phenomena, such as mechanical deformation, heat transfer, and chemical species transport and reactions. There are often strong interactions between these phenomena, and there is increasing interest in applying coupled-physics models to improve understanding of physical behavior under complex environmental conditions. Multiple simulation frameworks that facilitate coupled-physics simulations are in widespread use, and these employ a variety of techniques to account for interactions between those physics. Many frameworks solve the physics models independently and transfer results between them. Alternatively, a single monolithic system of equations for every physics model can be formed and solved. Each of these approaches has its benefits and drawbacks, and the optimal approach varies depending on the nature of the problem. The open-source MOOSE framework was developed targeting solution of large-scale multiphysics problems. Although it provides options for all these coupling approaches, its standard approach for multiphysics solutions is to form and solve a single monolithic system of equations containing the unknowns for all physics models. MOOSE provides a streamlined approach for users to define the solution variables, the terms in the partial differential equations pertaining to each variable, and interactions between solution variables. One aspect of the monolithic solution approach that can be problematic, however, is defining appropriate convergence criteria for the nonlinear system. A standard approach is to determine convergence is to simply take a norm of the residual vector corresponding to the full vector of unknowns. However, if the residual vector contains variables for multiple physics models, the magnitudes of those variables can differ significantly, and the variables can converge at significantly different rates from each other. It is important to ensure that the variables for each of the physics are converged, and also ensure that the convergence criteria are not excessively stringent in cases when there is little change in the solution. This talk presents representative multiphysics problems to highlight these issues, and shows strategies for convergence criteria in MOOSE that are robust for multiphysics models under a variety of conditions.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Large deformation and brittle failure calculated using the dual-domain material point method

The dual domain material point (DDMP) method is explored as a candidate to be implemented in a general purpose code to perform simulations of materials with complex geometry that undergo large history-dependent deformation and failure. To test its candidacy, we study its mesh convergence, its sensitivity to mesh orientation, and its ability to handle softening and failure of a material. Simulations of large deformation and simulations of mechanical failure are performed using both DDMP and the material point method (MPM). When cell-crossing of material points is not an issue and when there are a sufficient number of material points in each computation cell, the numerical error decreases with the square of the cell size as expected for both MPM and DDMP. DDMP has reduced error compared with MPM when there are many instances of material points crossing cell boundaries due to the continuous nature of the modified gradient of the shape functions. Simulations of a specimen under tension are also performed where the background mesh is aligned and misaligned with the tension direction. MPM displays a significant mesh-dependent stress field, DDMP shows negligible mesh dependency. Despite a mesh orientation-dependent stress field from MPM, the critical tension and failure mode from both MPM and DDMP calculations have negligible mesh dependency when using a non-local failure model. If only the failure mode is important (i.e., local stresses are unimportant), MPM with a non-local failure model is a suitable method for modeling failure with small deformations. However, if local stresses are also important or if there are large deformations with many cell-crossings before failure, DDMP should be the method that is used. A needed improvement for DDMP is identified from our numerical simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

LLNL Automized Surface Titration Model

The LLNL Automized Surface Titration Model (L-ASTM) is a community data-driven surface complexation modeling workflow for simulating potentiometric titration of mineral surfaces. The model accepts raw experimental potentiometric titration data formatted in a findable, accessible, interoperable, and reusable (FAIR) structure. The workflow was coded in Python and coupled to PHREEQC for surface complexation modeling and PEST for data fitting and parameter estimation.

Solchan, Han↗
NASA NTRS2008

Microwave Extraction of Lunar Water for Rocket Fuel

Nearly 50% of the lunar surface is oxygen, present as oxides in silicate rocks and soil. Methods for reduction of these oxides could liberate the oxygen. Remote sensing has provided evidence of significant quantities of hydrogen possibly indicating hundreds of millions of metric tons, MT, of water at the lunar poles. If the presence of lunar water is verified, water is likely to be the first in situ resource exploited for human exploration and for LOX-H2 rocket fuel. In-Situ lunar resources offer unique advantages for space operations. Each unit of product produced on the lunar surface represents 6 units that need not to be launched into LEO. Previous studies have indicated the economic advantage of LOX for space tugs from LEO to GEO. Use of lunar derived LOX in a reusable lunar lander would greatly reduce the LEO mass required for a given payload to the moon. And Lunar LOX transported to L2 has unique advantages for a Mars mission. Several methods exist for extraction of oxygen from the soil. But, extraction of lunar water has several significant advantages. Microwave heating of lunar permafrost has additional important advantages for water extraction. Microwaves penetrate and heat from within not just at the surface and excavation is not required. Proof of concept experiments using a moon in a bottle concept have demonstrated that microwave processing of cryogenic lunar permafrost simulant in a vacuum rapidly and efficiently extracts water by sublimation. A prototype lunar water extraction rover was built and tested for heating of simulant. Microwave power was very efficiently delivered into a simulated lunar soil. Microwave dielectric properties (complex electric permittivity and magnetic permeability) of lunar regolith simulant, JSC-1A, were measured down to cryogenic temperatures and above room temperature. The microwave penetration has been correlated with the measured dielectric properties. Since the microwave penetration depth is a function of temperature and frequency, an extraction system can be designed for water removal from different depths.

Ethridge, Edwin C.↗
NASA NTRS2025

Evolving the SpaceFOM: Lessons Learned and Future Development

For over fifty years, simulation has been a cornerstone technology for space missions. In many cases, one single simulator, developed by one team, is not enough to meet the simulation objectives. Astronaut crew training, docking, vehicle testing and complex mission planning all require several simulations to be connected and to interoperate, in order to achieve the goal of the simulation. To facilitate the development of interoperable simulations, an open standard, the SISO SpaceFOM was developed in collaboration between government, industry and academia. The standard was released in 2020. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. A number of requirements for the next version of SpaceFOM have been identified and proposed solutions are already under development. One key area is the object classes used for data exchange, where a richer set of classes have been proposed, based on practical use cases. For time management, the use of variable time resolutions and variable time steps is also proposed. For execution control, save and restore of simulations is considered as well as improved robustness, to handle failing components. A number of clarifications are also under consideration. This paper provides both a forward-looking view of the technical developments underway and a retrospective on the standard's evolution. The authors emphasize that prioritizing core challenges and delivering a practical first version were crucial steps. While not every idea was implemented in the initial release, the timely delivery of a functional standard enabled real-world applications, the growth of a user community, and the collection of valuable insights to shape future versions. The authors look forward to working with the next version of SpaceFOM together with the growing user community.

Simulation Interoperability↗
NASA NTRSDate not supplied

Evolving the SpaceFOM: Lessons Learned and Future Development

For over fifty years, simulation has been a cornerstone technology for space missions. In many cases, one single simulator, developed by one team, is not enough to meet the simulation objectives. Astronaut crew training, docking, vehicle testing and complex mission planning all require several simulations to be connected and to interoperate, in order to achieve the goal of the simulation. To facilitate the development of interoperable simulations, an open standard, the SISO SpaceFOM was developed in collaboration between government, industry and academia. The standard was released in 2020. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. A number of requirements for the next version of SpaceFOM have been identified and proposed solutions are already under development. One key area is the object classes used for data exchange, where a richer set of classes have been proposed, based on practical use cases. For time management, the use of variable time resolutions and variable time steps is also proposed. For execution control, save and restore of simulations is considered as well as improved robustness, to handle failing components. A number of clarifications are also under consideration. This paper provides both a forward-looking view of the technical developments underway and a retrospective on the standard's evolution. The authors emphasize that prioritizing core challenges and delivering a practical first version were crucial steps. While not every idea was implemented in the initial release, the timely delivery of a functional standard enabled real-world applications, the growth of a user community, and the collection of valuable insights to shape future versions. The authors look forward to working with the next version of SpaceFOM together with the growing user community.

FOMs↗
NASA NTRS2019

Introducing NASA Ames' New Infrared Optical Constant Facility. Determinations of Complex Refractive Indices for Titan Aerosol Analogs and Other Applications

A new optical constant facility has been developed at NASA Ames that will allow the determination of optical constants in the infrared of various materials, analogs of (exo)planetary hazes and cloud particles. Our facility is composed of a Fourier Transform Infrared (FTIR) spectrometer continuously covering the Near-IR to Far-IR range (from 0.74 to 200 μm), coupled to variable angle transmittance and reflectance accessories that allow the characterization of the scattering properties of non-homogeneous samples (laboratory (exo)planetary aerosol analogs, films, slabs of material, crystals, powders, etc.) over a wide incidence and emittance angle range (0-90 degrees). This new experimental setup allows the characterization of angular light distribution in both transmission and reflection measurements, and enables the determination of the complex indices of refraction, n and k, over the full NIR-FIR range via modeling of the laboratory measurements. The resulting refractive indices are critical input parameters in radiative transfer models, microphysical models, cloud models, protoplanetary disk simulations and other models used for the interpretation of observational data from past, current and future (exo)planetary NASA missions. Here we present a description of the facility along with the first determination of optical constants for Titan aerosol analogs produced in the Titan Haze Simulation (THS) experiment on COSmIC, a unique experimental setup developed at NASA Ames that allows the simulation of Titan’s complex atmospheric chemistry at Titan-like temperature (200 K). We also introduce a new study of the optical properties of ammonium-bearing phosphates, potential cloud particles forming in temperate exoplanets and brown dwarfs.

Sciamma-O'Brien, Ella M.↗
NASA NTRS1995

Large-eddy simulation of flow past a circular cylinder

Some of the most challenging applications of large-eddy simulation are those in complex geometries where spectral methods are of limited use. For such applications more conventional methods such as finite difference or finite element have to be used. However, it has become clear in recent years that dissipative numerical schemes which are routinely used in viscous flow simulations are not good candidates for use in LES of turbulent flows. Except in cases where the flow is extremely well resolved, it has been found that upwind schemes tend to damp out a significant portion of the small scales that can be resolved on the grid. Furthermore, it has been found that even specially designed higher-order upwind schemes that have been used successfully in the direct numerical simulation of turbulent flows produce too much dissipation when used in conjunction with large-eddy simulation. The objective of the current study is to perform a LES of incompressible flow past a circular cylinder at a Reynolds number of 3900 using a solver which employs an energy-conservative second-order central difference scheme for spatial discretization and compare the results obtained with those of Beaudan & Moin (1994) and with the experiments in order to assess the performance of the central scheme for this relatively complex geometry.

Mittal, R.↗
DOE OSTI2023

Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior

The increasing incidence and severity of wildfires underscores the necessity of accurately predicting their behavior. While high-fidelity models derived from first principles offer physical accuracy, they are too computationally expensive for use in real-time fire response. Low-fidelity models sacrifice some physical accuracy and generalizability via the integration of empirical measurements, but enable real-time simulations for operational use in fire response. Machine learning techniques have demonstrated the ability to bridge these objectives by learning first-principles physics while achieving computational speedups. While deep learning approaches have demonstrated the ability to predict wildfire propagation over large time periods, time-resolved fire-spread predictions are needed for active fire management. Here, in this work, we evaluate the ability of deep learning approaches in accurately modeling the time-resolved dynamics of wildfires. We use an autoregressive process in which a convolutional recurrent deep learning model makes predictions that propagate a wildfire over 15 min increments. We apply the model to four simulated datasets of increasing complexity, containing both field fires with homogeneous fuel distribution as well as real-world topologies sampled from the California region of the United States. We show that even after 100 autoregressive predictions representing more than 24 h of simulated fire spread, the resulting models generate stable and realistic propagation dynamics, achieving a Jaccard score between 0.89 and 0.94 when predicting the resulting fire scar. The inference time of the deep learning models are examined and compared, and directions for future work are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Application of community data to surface complexation modeling framework development: Iron oxide protolysis

This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pK a1 decreased with increasing SSD while the opposite tendency was observed for pK a2 . This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2019

The New NASA Ames Infrared Optical Constant Facility. Determinations for Titan Aerosol-, and Exoplanet and Brown Dwarf Cloud Particle Analogs

Here we present a new optical constant facility developed at NASA Ames that will allow the determination of optical constants in the infrared of various materials, analogs of hazes and cloud particles in (exo)planet atmospheres and brown dwarfs. Our facility is composed of a Fourier Transform Infrared (FTIR) spectrometer continuously covering the Near-IR, mid-IR and Far-IR range (from 0.74 to 200 µm), coupled to variable angle transmittance and reflectance accessories that allow the characterization of the scattering properties of nonhomogeneous samples (laboratory planetary aerosol analogs, films, slabs of material, crystals, powders...) over a wide incidence and emittance angle range (0-90 degrees). This permits the angular light distribution in both transmission and reflection measurements to be characterized, enabling the determination of the complex indices of refraction, n and k, over the full NIR-FIR range via modeling of the laboratory observations. The resulting refractive indices are critical input parameters in radiative transfer models, exoplanet and brown dwarf cloud models, protoplanetary disk simulations and other models used for the interpretation of observational data from past, current and future (exo)planetary NASA missions. We will present preliminary data obtained on Titan aerosol analogs produced in the Titan Haze Simulation (THS) experiment on COSmIC, a unique experimental platform developed at NASA Ames that allows the simulation of Titan's complex atmospheric chemistry at Titan-like temperature (200 K). We will also introduce a new study of the optical properties of ammonium-bearing phosphates, potential cloud particles forming in temperate exoplanets and brown dwarfs.

Planetary Science↗
DOE OSTI2025

A staged deep learning approach to spatial refinement in 3D temporal atmospheric transport

High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume dispersion in complex terrain. However, their high computational cost makes them impractical for applications requiring rapid responses or iterative processes, such as optimization, uncertainty quantification, or inverse modeling. To address this challenge, this work introduces the Dual-Stage Temporal Three-dimensional UNet Super-resolution (DST3D-UNet-SR) model, a highly efficient deep learning model for plume dispersion predictions. DST3D-UNet-SR is composed of two sequential modules: the temporal module (TM), which predicts the transient evolution of a plume in complex terrain from low-resolution temporal data, and the spatial refinement module (SRM), which subsequently enhances the spatial resolution of the TM predictions. We train DST3D-UNet-SR using a comprehensive dataset derived from high-resolution large eddy simulations (LES) of plume transport. We propose the DST3D-UNet-SR model to significantly accelerate LES of three-dimensional (3D) plume dispersion by three orders of magnitude. Additionally, the model demonstrates the ability to dynamically adapt to evolving conditions through the incorporation of new observational data, substantially improving prediction accuracy in high-concentration regions near the source.

3D temporal sequences↗
NASA NTRS2011

Lockout/Tagout (LOTO) Simulator

The Lockout/Tagout (LOTO) Simulator is a portable training aid, or demonstration tool, designed to physically illustrate real-time critical-safety concepts of electrical lockout/tagout. The objective is to prevent misinterpretations of what is off and what is on during maintenance and repair of complex electrical systems. The simulator is designed in the form of a hinged box that opens up and stands on its own as an easel for demonstrations. On the outer face of the unit is a simulated circuit breaker box housing the switches. The breakers control the main power to the unit, a light bulb, and an electrical control cabinet. The light bulb is wired so that either of two breakers can provide power to it. When power is sent to the electrical control cabinet, a red indicator light illuminates. Inside the cabinet is the power supply from a personal computer. The power supply produces a 12-V dc output that is sent over to a small fan next to it, also from a computer, and an amber light on the front of the cabinet illuminates. A separate switch powers the fan on and off. The power supply is behind a plastic shield to protect against exposure to live conductors. Electrical banana jacks are mounted in the plastic shield to allow a voltmeter to be connected safely when opening the cabinet and taking a meter reading to verify de-energization as part of a simulation exercise. This LOTO simulator prototype is designed and fabricated as an all-in-one unit. All accessories can be stored inside the hinged case, and there is a handle on top for ease of transport. The circuit breaker labels attach with hook and loop fasteners so that they may be moved and changed to fit the training or demonstration scenario. The warning signs and labels on the electrical control box are magnetic, allowing for easy reconfiguration to emulate different equipment setups. A specially designed magnetic cover was made to disguise the indicator lights for demonstrations when these indicators are not used. The cover is disguised as an arc flash safety label that would typically be found on such a cabinet. One indicator light has a separate switch that can take it offline. This is to allow for demonstration to trainees on why it is important not to completely rely on indicator lights, but that they should always take a meter reading at the exposed conductors to absolutely verify de-energization before exposure. A clear plastic barrier and banana jacks inside the cabinet provide a safe way to plug in a voltmeter for demonstrations without exposure to the hazards of energized equipment. A small remote control unit is wired into the fan circuit. The remote allows the demonstrator to turn the fan on and off, provided that all of the breakers and switches leading to it are configured on as well. The remote feature was added in order to demonstrate the importance of starting the lockout/tagout task with energized equipment, then powering it down, isolating it, and locking it out to ensure that the correct breakers have been locked out.

Scheer, Jennifer↗
DOE OSTI2026

Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area

Pushing global climate models to large-eddy simulation (LES) scales over complex terrain has remained a major challenge. This study presents the first known implementation of a global model – SCREAM (Simple Cloud-Resolving E3SM Atmosphere Model) – at 100 m horizontal resolution using a regionally refined mesh (RRM) over the San Francisco Bay Area. Two hindcast simulations were conducted to test performance under both strong synoptic forcing and weak, boundary-layer-driven conditions. We demonstrate that SCREAM can stably run at LES scales while realistically capturing topography, surface heterogeneity, and coastal processes. The 100 m SCREAM-RRM substantially improves near-surface wind speed, temperature, humidity, and pressure biases compared to the baseline 3.25 km simulation, and better reproduces fine-scale wind oscillations and boundary-layer structures. These advances leverage SCREAM's scale-aware SHOC turbulence parameterization, which transitions smoothly across scales without tuning. Performance tests show that while CPU-only simulations remain costly, GPU acceleration with SCREAMv1 on NERSC's Perlmutter system enables two-day hindcasts to complete in under two wall-clock days. Our results open the door to LES-scale studies of orographic flows, boundary-layer turbulence, and coastal clouds within a fully comprehensive global modeling framework.

Geosciences↗
DOE OSTI2026

Simulation-Based Validation of An Open-Source, Scalable Framework for Building Energy Management in Small and Medium-Sized Commercial Buildings

Abstract: Small and medium-sized commercial buildings (SMCBs) represent 94% of U.S. commercial buildings but encounter substantial obstacles in adopting Building Energy Management (BEM) systems. Current approaches exhibit fundamental limitations: vendor-specific API platforms restrict interoperability through proprietary ecosystems; commercial automation software demands extensive technical expertise and licensing costs; open-source IoT solutions lack native support for building automation protocols and semantic models. This paper introduces a configuration-driven web interface framework addressing the gap between smart device advancements and accessible BEM software infrastructure for SMCBs. The framework leverages VOLTTRON middleware integrated with an automated converter that processes unified YAML configurations into heterogeneous system files, reducing required configuration artifacts from six separate files to a single unified specification. The system architecture enables vendor-agnostic operation through BACnet and Modbus protocols while supporting semantic building model integration via automated Brick Schema parsing. Configuration-driven interfaces automatically adapt to diverse HVAC types without custom development. Simulation-based validation using BOPTEST demonstrates automatic interface generation between fan coil and hydronic systems, with the automated converter successfully generating all platform-specific outputs from the single YAML input. The result demonstrates the framework's capability to streamline BEM system deployment through reduced configuration complexity. This work bridges simulation capabilities with operational deployment, demonstrating how virtual testbeds validate generalizable software frameworks for real-world building automation.

Chung, Jihoon [ORNL] (ORCID:0000000184880815)↗
DOE OSTI2023

QUOTAS: A New Research Platform for the Data-driven Discovery of Black Holes

We present QUOTAS, a novel research platform for the data-driven investigation of supermassive black hole (SMBH) populations. While SMBH data—observations and simulations—have grown in complexity and abundance, our computational environments and tools have not matured commensurately to exhaust opportunities for discovery. To explore the BH, host galaxy, and parent dark matter halo connection—in this pilot version—we assemble and colocate the high-redshift, z > 3 quasar population alongside simulated data at the same cosmic epochs. As a first demonstration of the utility of QUOTAS, we investigate correlations between observed Sloan Digital Sky Survey (SDSS) quasars and their hosts with those derived from simulations. Leveraging machine-learning algorithms (ML), to expand simulation volumes, we show that halo properties extracted from smaller dark-matter-only simulation boxes successfully replicate halo populations in larger boxes. Next, using the Illustris-TNG300 simulation that includes baryonic physics as the training set, we populate the larger LEGACY Expanse dark-matter-only box with quasars, and show that observed SDSS quasar occupation statistics are accurately replicated. First science results from QUOTAS comparing colocated observational and ML-trained simulated data at z3 are presented. QUOTAS demonstrates the power of ML, in analyzing and exploring large data sets, while also offering a unique opportunity to interrogate theoretical assumptions that underpin accretion and feedback models. QUOTAS and all related materials are publicly available at the Google Kaggle platform. (The full data set—observational data and simulation data—are available at: https://www.kaggle.com/ and the codes are available at:https://www.kaggle.com/datasets/quotasplatform/quotas)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Programming approaches for scalability, performance, and portability of combustion physics codes

Here, this paper presents the process, strategy, and results associated with porting a typical combustion physics flow solver to current state-of-the-art and future massively-parallel computer architectures. Major focus is placed on the distinct algorithmic structure of these types of codes and how it can be integrated with modern programming paradigms for heterogeneous platforms (i.e., distributed many-core systems with accelerators). An end-to-end case study is presented that exemplifies the process in a generic manner, which then serves as a clear guide with respect to the strategy and best practices leading to a robust and adaptable framework that performs well, is durable over time, is portable, and requires minimal human-effort. This end is accomplished beginning with the use of a mature, validated, structured, multiblock code framework optimized for application of both Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). This code has been ported to a variety of platforms over the past decade, including most recently the Oak Ridge Leadership Computing Facility’s “Summit” Platform. The experience gained on these multiple platforms provides general insights and thus the results presented are not specific to any one code or platform other than the overarching trend toward distributed many-core systems with accelerators in order to move toward exascale performance. The resultant performance and scalability of the ported code is demonstrated on a real-world application; a state-of-the-art rotating detonation rocket engine simulation that matches the complex geometry and boundary conditions imposed as part of a companion experimental campaign.

97 MATHEMATICS AND COMPUTING↗