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At least 613 records · Page 34

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NASA NTRS1992

FOCUS - An experimental environment for fault sensitivity analysis

FOCUS, a simulation environment for conducting fault-sensitivity analysis of chip-level designs, is described. The environment can be used to evaluate alternative design tactics at an early design stage. A range of user specified faults is automatically injected at runtime, and their propagation to the chip I/O pins is measured through the gate and higher levels. A number of techniques for fault-sensitivity analysis are proposed and implemented in the FOCUS environment. These include transient impact assessment on latch, pin and functional errors, external pin error distribution due to in-chip transients, charge-level sensitivity analysis, and error propagation models to depict the dynamic behavior of latch errors. A case study of the impact of transient faults on a microprocessor-based jet-engine controller is used to identify the critical fault propagation paths, the module most sensitive to fault propagation, and the module with the highest potential for causing external errors.

Choi, Gwan S.↗

NASA NTRS2016

Using CubeSats to Monitor Debris Flux

Recent updates to NASA's Orbital Debris Engineering Model (ORDEM 3.0) include a population of small particles (1-2 mm in size) composed of high-density materials (e.g., steel) that drive much of the predicted risk for satellites in the 700-1000 km altitude regime. This modeled population was based on the analysis of returned surfaces of the Shuttle, which flew below 600 km altitude. The cessation of Shuttle missions, plus the lack of in situ data above 600 km means that a data source is being sought to either confirm or modify this high-density population. One possible data source would be a database of anomalous sporadic changes in spacecraft orbit/orientation that might be due to momentum transfer from small particles too small to seriously damage the spacecraft. Because the momentum imparted from an impact would be tiny, it would most likely show up in the orbital behavior of cubesats and other small satellites. While such small satellites were few in number, this was not a particularly attractive option, but now with the proliferation of cubesats in multiple orbit planes and altitudes, the possible collecting area has increased significantly. This presentation will discuss the physics of momentum-transferring impacts from hypervelocity collisions, and make predictions about rates, directions, and locations of such impacts. In addition, it will include recommendations for satellite users on what kind of data might be worth archiving and investigating.

Matney, Mark↗

DOE OSTI2023

Cloud Atlas: An Interactive Apparatus for Air Quality Awareness

This paper introduces a research project of a kinetic apparatus that translates collected air quality data to users. The kinetic mechanical skeleton is embedded with processors and electronics, and constantly changes its form according to air quality data collected online via a web crawler. By translating invisible environmental conditions, such as air quality data into morphological, colorful, and acoustic changes for the device, the participants can be aware of the phenomenon of air pollution in real time. The interac- tions between participants' movements and the changes of the device imply how human behaviors can affect the state of the atmosphere. As a result, the device evokes public awareness and participation in environmental issues through tangible experiences. This research aims to explore a new kind of responsive architecture that acts as a medium between invisible environments and inhabitants.

Zhao, Xiaoxiao↗

DOE OSTI2023

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗

DOE OSTI2025

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗

NASA NTRS1995

Intelligent automated surface grid generation

The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.

Yao, Ke-Thia↗

NASA NTRS2013

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Cheung, Kar-Ming↗

DOE OSTI2025

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRSDate not supplied

From Partial to Global Assume-Guarantee Contracts: Compositional Realizability Analysis in FRET

Realizability checking refers to the formal procedure that aims to determine whether an implementation exists, always complying to a set of requirements, regardless of the stimuli provided by the system’s environment. Such a check is essential to ensure that the specification does not allow behavior that can force the system to violate safety constraints. In this paper, we present an approach that decomposes realizability checking into smaller, more tractable problems. More specifically, our approach automatically partitions specifications into sets of non-interfering requirements. We prove that checking whether a specification is realizable reduces to checking that each partition is realizable.We have integrated realizability checking and implemented our decomposition approach within the open-source Formal Requirements ElicitationTool (FRET). A FRET user may check the realizability of a specification monolithically or compositionally. We evaluate our approach by comparing monolithic and compositional checking and showcase the strengths of our decomposition approach on a variety of industrial-level case studies

Anastasia Mavridou↗

NASA NTRS1999

The Aviation System Analysis Capability Air Carrier Cost-Benefit Model

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. Therefore, NASA is developing the ability to evaluate the potential impact of various advanced technologies. By thoroughly understanding the economic impact of advanced aviation technologies and by evaluating how the new technologies will be used in the integrated aviation system, NASA aims to balance its aeronautical research program and help speed the introduction of high-leverage technologies. To meet these objectives, NASA is building the Aviation System Analysis Capability (ASAC). NASA envisions ASAC primarily as a process for understanding and evaluating the impact of advanced aviation technologies on the U.S. economy. ASAC consists of a diverse collection of models and databases used by analysts and other individuals from the public and private sectors brought together to work on issues of common interest to organizations in the aviation community. ASAC also will be a resource available to the aviation community to analyze; inform; and assist scientists, engineers, analysts, and program managers in their daily work. The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. Commercial air carriers, in particular, are an important stakeholder in this community. Therefore, to fully evaluate the implications of advanced aviation technologies, ASAC requires a flexible financial analysis tool that credibly links the technology of flight with the financial performance of commercial air carriers. By linking technical and financial information, NASA ensures that its technology programs will continue to benefit the user community. In addition, the analysis tool must be capable of being incorporated into the wide-ranging suite of economic and technical models that comprise ASAC. This report describes an Air Carrier Cost-Benefit Model (CBM) that meets these requirements. The ASAC CBM is distinguished from many of the aviation cost-benefit models by its exclusive focus on commercial air carriers. The model considers such benefit categories as time and fuel savings, utilization opportunities, reliability and capacity enhancements, and safety and security improvements. The model distinguishes between benefits that are predictable and those that occur randomly. By making such a distinction, the model captures the ability of air carriers to reoptimize scheduling and crew assignments for predictable benefits. In addition, the model incorporates a life-cycle cost module for new technology, which applies the costs of nonrecurring acquisitions, recurring maintenance and operation, and training to each aircraft equipment type independently.

Gaier, Eric M.↗

NASA NTRS1977

Industrial Productivity

NASTRAN is an offshoot of the computer-design technique used in construction of airplanes and spacecraft. [n this technique engineers create a mathematical model of the aeronautical or space vehicle and "fly" it on the ground by means of computer simulation. The technique enables them to study performance and structural behavior of a number of different designs before settling on the final configuration and proceeding with construction. From this base of aerospace experience, NASA-Goddard developed the NASTRAN general purpose computer program, which offers an exceptionally wide range of analytic capability with regard to structures. NASTRAN has been applied to autos, trucks, railroad cars, ships, nuclear power reactors, steam turbines, bridges, and office buildings. NASA-Langley provides program maintenance services regarded as vital by many NASTRAN users. NASTRAN is essentially a predictive tool. It takes an electronic look at a computerire$.dedgn and reports how the structure will react under a great many different conditions. It can, for example, note areas where high stress levels will occur-potential failure points that need strengthening. Conversely, it can identify over-designed areas where weight and material might be saved safely. NASTRAN can tell how pipes stand up under strong fluid flow, how metals are affected by high temperatures, how a building will fare in an earthquake or how powerful winds will cause a bridge to oscillate. NASTRAN analysis is quick and inexpensive. It minimizes trial-and-error in the design process and makes possible better, safe, lighter structures affording large-scale savings in development time and materials. Some examples of the broad utility NASTRAN is finding among industrial firms are shown on these pages.

Source record↗

DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Materials Science↗

DOE OSTI2026

ReachNow EV Driving Data From Seattle, WA, Portland, OR, and New York, NY

ReachNow provided Idaho National Laboratory (INL) with a dataset describing approximately 49,000 trips taken by customers and employees in approximately 100 BMW i3 EVs operating in ReachNow's free-floating car-sharing fleets in Seattle, WA, Portland, OR, and New York, NY between May 2016 and February 2017. Data fields include vehicle rental period start and end timestamps, the location where vehicles were parked at the start and end of rental periods, and distance driven during rental periods. A field categorizing the user during each rental period is also included. This field makes it possible to identify when vehicles were rented by customers and when vehicles were driven by fleet management team employees to reposition, charge, or service the vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

How Many Trip Requests Could We Support? An Activity-Travel Based Vehicle Scheduling Approach

In a world of ever-changing travel behavior and ever-increasing modal options, is vital to have integrated models that could capture the interactions between supply and demand layers of travel. Addressing this need, we propose three different versions of network representation and mathematical models for the activity-based vehicle routing problem to connect activity-travel graphs of passengers (demand layer) to spatio-temporal networks of vehicles (supply layer). Versions I and II are arc-based, while version III is path-based. In version I, we introduce the concept of activity-travel graphs for passengers. For vehicles, we construct space–time networks and add a new dimension, called “under-service state”, to track the execution status of trip requests at any location and time. In version II, we reduce the complexity of the network structure by eliminating the state dimension and some other modifications in the structure of the passengers’ and vehicles’ network. Although both versions can capture various behavioral constraints of the activity-based vehicle routing problem (e.g., mandatory and optimal activities, duration of activities, chain of activities, preferred starting and ending times of activities), due to the high level of complexity of the network structure, both versions can only solve small-sized problems. To tackle the computational complexity, we propose a path-based network representation in version III, and to make a balance between the disutility of passengers and vehicles, we present a tolled user equilibrium problem. Mathematical models are coded in C and GAMS and implemented on real-world Phoenix regional transportation network with more than 39 million trip requests, which demonstrate the effectiveness of the proposed solution for the original and restricted master problems.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗

DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗