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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Scattering Processes from Quantum Simulation Algorithms for Scalar Field Theories

We provide practical simulation methods for scalar field theories on a quantum computer that yield improved asymptotics as well as concrete gate estimates for the simulation and physical qubit estimates using the surface code. We achieve these improvements through two optimizations. First, we consider a finite volume approach for estimating the elements of the S-matrix. This approach is appropriate in general for 1+1D and for certain low-energy elastic collisions in higher dimensions. Second, we implement our approach using a series of different fault-tolerant simulation algorithms for Hamiltonians formulated both in the field occupation basis and field amplitude basis. Our algorithms are based on either second-order Trotterization or qubitization. The cost of Trotterization in occupation basis scales as O ( λ N 7 | Ω | 3 / ( M 5 / 2 ϵ 3 / 2 ) ) where λ is the coupling strength, N is the occupation cutoff, | Ω | is the volume of the spatial lattice, M is the mass of the particles and ϵ is the uncertainty in the energy calculation used for the S -matrix determination. Qubitization in the field basis scales as O ( | Ω | 2 ( k 2 Λ + k M 2 ) / ϵ ) , where k is the cutoff in the field and Λ is a scaled coupling constant. We find in both cases that the bounds suggest physically meaningful simulations can be performed using on the order of 4 × 10 6 physical qubits and 10 12 T -gates which corresponds to roughly one day on a superconducting quantum computer with surface code and a cycle time of 100 ns. This places the simulation of scalar field theory within striking distance of the gate counts for the best available chemistry simulation results.

Hardy, Andrew [Toronto U.] (ORCID:0000000235817382↗

Investigating Resilience of Loops in HPC Programs: A Semantic Approach with LLMs

Soft errors have become one of the major concerns for the error resilience of the HPC applications as those errors may cause HPC applications to generate serious outcomes such as silent data corruptions (SDCs). Protecting the applications from soft errors is an essential while challenging task. Among different approaches, obtaining a profound understanding of the resilience proneness of an application is very important to devise efficient error detection and recovery strategies. Given the scale of the HPC applications both in the code size and execution time, there are often cases that the error propagation analysis on such applications would produce a massive volume of unstructured data, which requires a significant amount of efforts, to process and to obtain indicating actions towards error protection. In this paper, we present a control-flow based visual analysis framework to help the users conduct error propagation analysis and identify the critical sections of a program that may have a higher likelihood of leading to erroneous outcomes when affected by the control flow related errors. We also design and implement the scalable visualization framework - ResilienceVis that efficiently and effectively visualizes the affected program states under errors and the propagation traces for an application in a user-friendly manner, and eventually, we combine the analysis and visualization to exhibit the error-proneness of the different sections of applications.

Jiang, Hailong↗

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗

Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method

Development and application of the open-source GPU-based fluid-thermal simulation code, NekRS, are described. Time advancement is based on an efficient kth-order accurate timesplit formulation coupled with scalable iterative solvers. Spatial discretization is based on the high-order spectral element method (SEM), which affords the use of fast, low-memory, matrix-free operator evaluation. Further, recent developments include support for nonconforming meshes using overset grids and for GPU-based Lagrangian particle tracking. Results of large-eddy simulations of atmospheric boundary layers for wind-energy applications as well as extensive nuclear energy applications are presented.

42 ENGINEERING↗

Kinetic Simulations of Microstructural Evolution (KSOME)

"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects

Nandipati, Giridhar [Pacific Northwest National La↗

PhyML

Python scripts for physics informed machine learning for time-dependent problems. The code implements hard constrained sequential physics-informed neural networks (HCSPINNs) using JAX library. The details of the method and implementation can be found in the following paper: Roy, P., & Castonguay, S. (2024). Exact Enforcement of Temporal Continuity in Sequential Physics- Informed Neural Networks. arXiv preprint arXiv:2403.03223. (https://arxiv.org/abs/2403.03223)

Roy, Pratanu↗

Electric Grid Simulator For Human Factor Research

The developed code simulates real-time monitor and control for west area of IEEE 118-bus system. The 24-hour load profile for each bus is derived by scaling the system’s rated load in the PSSE sav file according to the California Independent System Operator’s Day-ahead load forecast for May 1, 2024. This simulator performs several critical functions: (1) Calculating time-series power flow every 4 seconds; (2) Updating and dispatching AGC signals every minute; (3) Conducting N-1 contingency analysis every 5 minutes. Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.

Huang, Jianqiao [Idaho National Laboratory (INL), ↗

PyPTkinetics

This basic research code computes the time-dependent phase transition between two solid crystalline phases under dynamic conditions.

Blaschke, Daniel N.↗

Incorporating Full Elastodynamic Effects and Dipping Fault Geometries in Community Code Verification Exercises for Simulations of Earthquake Sequences and Aseismic Slip (SEAS)

ABSTRACT Numerical modeling of earthquake dynamics and derived insight for seismic hazard relies on credible, reproducible model results. The sequences of earthquakes and aseismic slip (SEAS) initiative has set out to facilitate community code comparisons, and verify and advance the next generation of physics-based earthquake models that reproduce all phases of the seismic cycle. With the goal of advancing SEAS models to robustly incorporate physical and geometrical complexities, here we present code comparison results from two new benchmark problems: BP1-FD considers full elastodynamic effects, and BP3-QD considers dipping fault geometries. Seven and eight modeling groups participated in BP1-FD and BP3-QD, respectively, allowing us to explore these physical ingredients across multiple codes and better understand associated numerical considerations. With new comparison metrics, we find that numerical resolution and computational domain size are critical parameters to obtain matching results. Codes for BP1-FD implement different criteria for switching between quasi-static and dynamic solvers, which require tuning to obtain matching results. In BP3-QD, proper remote boundary conditions consistent with specified rigid body translation are required to obtain matching surface displacements. With these numerical and mathematical issues resolved, we obtain excellent quantitative agreements among codes in earthquake interevent times, event moments, and coseismic slip, with reasonable agreements made in peak slip rates and rupture arrival time. We find that including full inertial effects generates events with larger slip rates and rupture speeds compared to the quasi-dynamic counterpart. For BP3-QD, both dip angle and sense of motion (thrust versus normal faulting) alter ground motion on the hanging and foot walls, and influence event patterns, with some sequences exhibiting similar-size characteristic earthquakes, and others exhibiting different-size events. These findings underscore the importance of considering full elastodynamics and nonvertical dip angles in SEAS models, as both influence short- and long-term earthquake behavior and are relevant to seismic hazard.

Geochemistry & Geophysics↗

Dissertation Proposal: Innovations in Pulsed Power and Plasma Science Theory Simulation and Experiment

Pulsed power and plasma physics are topics of great study at both Sandia National Laboratories (SNL or Sandia) and the University of New Mexico (UNM). The goal of this research is to further knowledge and understanding of these fields using the resources of both SNL and UNM in three ways. The first way is through the comprehension, application, and testing of theory. Reading and analytically deriving theoretical solutions of problems both real-world and simplified will allow for a fresh perspective and the furthering of the theory. One such theory is Ottinger's generalized theory for voltage measurement in magnetically insulated transmission lines (MITLs). By working through the math, a deeper understanding of the theory is gained from which one may add more physically accurate and/or more detailed physics into the theory. Additionally, understanding the theory lays a good foundation from which one can analyze, test, and compare results to the theory in the following two ways that will advance the fields of pulsed power and plasma physics. The second way is through the modeling and simulation of real-world and simplified problems that utilize and test the afore mentioned theories. Theory can be applied to a simulation domain by using the unstructured time-domain electromagnetic (UTDEM) codes EMPHASIS and EMPIRE as well as the physical modeling software CUBIT, all of which were developed at SNL. Problems such as the modeling and design of the extended MITL on HERMES III, the understanding of space-charge-limited emission from vacuum cathodes, and the interaction between a relativistic electron beam and an ideal gas can all be modeled, simulated, and analyzed with this set of codes. Here the advantage is three-fold. Firstly, theory that describes our understanding of these problems can be put to the test and advanced through iterative simulation and analysis. Secondly, the understanding of these problems will have a positive impact on national security through the advancement of the technological capability of the United States of America. Thirdly, and not unrelated to the prior advantage, is the validation and verification of EMPIRE and EMPHASIS. This segues into the third way, which is through experiment and the comparison of experiment to simulated and theoretical results. Performing experimental comparisons completes the scientific method and grounds all of the work in reality. Being able to physically test theory and simulation is necessary for any real conclusions to be drawn. Another advantage for carrying out experimental work is to advance the physical testing capabilities of SNL. Several systems will be developed and tested through the course of this work that positively impact technological advancement of Sandia National Labs. Lastly, all of the above work will converge to yield a well-rounded perspective that ties the three categories of research together.

42 ENGINEERING↗

MPACT Theory Manual (V.4.3)

This manual presents the theory underlying the three-dimensional (3D) whole-core, pin-resolved neutron transport calculation methodologies employed in the MPACT code. MPACT’s primary goal is to provide accurate sub-pin power distributions in a computationally efficient manner. To accomplish this, MPACT offers several different transport method options. The 2D/1D method, in which 3D problems are decomposed into an axial stack of radial “slices,” is currently the most commonly used. In this option, two-dimensional (2D) planar solutions are provided by the method of characteristics (MOC), and axial solutions are provided via one-dimensional (1D) approximate diffusion, or P3 solutions. The radial and axial solutions are coupled by (i) axial and radial transverse leakages, and (ii) a global 3D coarse mesh finite difference (CMFD) solve, which provides both acceleration and stability to the solution iteration scheme. The subsequent chapters of this manual present a range of topics, including MOC, CMFD, axial nodal transport solvers, 2D/1D, self-shielding, depletion, thermal-hydraulics, and transient methods. Development of the underlying theory of the 2D/1D method is presented, diagrams are included to highlight important algorithmic flow, and important concepts are discussed as appropriate. This manual is intended to be self-sufficient, but references to published articles and other materials are included for further reading. MPACT is a relatively new code, with new capabilities and many computational methods that did not exist until recently. This manual is an even newer document, with chapters written by several different code contributors working under time constraints. For these reasons, the manual is not yet complete and finalized. Future versions of this manual will address current deficiencies.

97 MATHEMATICS AND COMPUTING↗

3D modeling of the Staged Z-pinch with the FLASH code

The Staged Z-pinch (SZP) fusion concept is a magneto-inertial compression scheme developed by Magneto-Inertial Fusion Technologies, Inc. (MIFTI), in which small amounts of fusion fuel are brought to fusion-relevant conditions by passing multi-million amperes strong current through a cylindrical shell of high atomic number material. One- and two-dimensional modeling performed by MIFTI with the MACH2 code, suggests that net fusion energy gain can be achieved when currents in the 10 million amperes range compress a 50%-50% mixture of deuterium and tritium gas. In this project we enhance and use the FLASH code to execute high-fidelity, simulations of various SZP configurations, a collaboration between the Flash Center for Computational Science at the University of Rochester and the Laboratory for Laser Energetics, and MIFTI. FLASH is a high-performance computing, multi-physics, radiation magnetohydrodynamic (MHD) code with extended physics capabilities, which is developed at the Flash Center. The goal of this project is to assess the shell/fuel stability of the pinch to two- and three-dimensional MHD instabilities and to utilize FLASH’s extended physics capabilities to understand how extended-MHD effects impact implosion dynamics and plasma conditions at stagnation. The project is a natural extension of an ongoing collaborative effort between MIFTI and the Flash Center through the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) BETHE program and can provide MIFTI with simulation capabilities that are currently beyond their reach with MACH2. Ultimately, MIFTI wants FLASH to become one of their simulation workhorses for reliable, high-fidelity SZP platform design. During the project, the Flash Center team developed a suite of in one- and two-dimensional FLASH simulations to model different variants of the SZP platform, performed code-to-code comparisons with MACH2, and used the FLASH code to design and model SZP experiments like the Double Eagle experiments that MIFTI recently performed. Also, the Flash Center team developed the capabilities of FLASH to be able to do three-dimensional simulations of pulsed-power experiments with the code for the first time. Two publications from this effort are currently under review and two more are in preparation. MIFTI has also committed to the use of FLASH for future SZP simulation efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FullWave — A Full Wave Parallel Code for Modeling RF Fields in Hot Tokamak Plasma

FullWave is a computer code that simulates how radio-frequency (RF) waves travel and deposit energy in the hot plasma inside a fusion reactor. RF waves are used to heat the plasma and drive electrical current, which is essential for sustaining fusion reactions. The code uses a new algorithm that can handle much finer spatial detail than previous codes — more than 100 times finer — while running efficiently on national supercomputers. It incorporates a detailed physics model that captures subtle kinetic effects important for accurate prediction of wave behavior. Under this project, FullWave was extended to cover multiple RF frequency ranges relevant to present and future tokamaks, and validated against experimental parameters from the DIII-D tokamak at General Atomics. Results were published in peer-reviewed journal articles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often require thousands of rollouts to learn new tasks. We argue that the interpretable nature of language often provides a much richer learning medium for LLMs, compared to policy gradients derived from sparse, scalar rewards. To test this, we introduce GEPA (Genetic-Pareto), a prompt optimizer that thoroughly incorporates natural language reflection to learn high-level rules from trial and error. Given any AI system containing one or more LLM prompts, GEPA samples trajectories (e.g., reasoning, tool calls, and tool outputs) and reflects on them in natural language to diagnose problems, propose and test prompt updates, and combine complementary lessons from the Pareto frontier of its own attempts. As a result of GEPA's design, it can often turn even just a few rollouts into a large quality gain. Across six tasks, GEPA outperforms GRPO by 6% on average and by up to 20%, while using up to 35x fewer rollouts. GEPA also outperforms the leading prompt optimizer, MIPROv2, by over 10% (e.g., +12% accuracy on AIME-2025), and demonstrates promising results as an inference-time search strategy for code optimization. We release our code at https://github.com/gepa-ai/gepa.

97 MATHEMATICS AND COMPUTING↗

FEOTS v0.0.0: a new offline code for the fast equilibration of tracers in the ocean

Abstract. In this paper we introduce a new software framework for the offline calculation of tracer transport in the ocean. The Fast Equilibration of Ocean Tracers Software (FEOTS) is an end-to-end set of tools to efficiently calculate tracer distributions on a global or regional sub-domain using transport operators diagnosed from a comprehensive ocean model. To the best of our knowledge, this is the first application of a transport matrix model to an eddying ocean state. While a Newton–Krylov-based equilibration capability is still under development and not presented here, we demonstrate in this paper the transient modeling capabilities of FEOTS in an application focused on the Argentine Basin, where intense eddy activity and the Zapiola Anticyclone lead to strong mixing of water masses. The demonstration illustrates progress in developing offline passive tracer simulation capabilities, while highlighting the challenges of the impulse response functions approach in capturing tracer transports by a non-linear advection scheme. Our future work will focus on improving the computational efficiency of the code to reduce time-to-solution, using different basis functions to better represent non-linear advection operators, applying FEOTS to a parent model with unstructured grids (Ocean Model for Prediction Across Scales, MPAS-Ocean), and fully implementing a Newton–Krylov steady-state solver.

54 ENVIRONMENTAL SCIENCES↗

From PeleC to PeleACC, to PeleC++

PeleC is an Exascale Computing Project application for simulating compressible combustion in complex geometries. It has been built on top of the popular AMReX library. In the beginning of the Exascale Computing Project, PeleC was focused on KNL. It uses a mixture of C++, C, and kernels written in Fortran to obtain performance by focusing on vectorization. Recently we have taken two approaches in deciding PeleC's future for obtaining performance on exascale GPU machines. In the first programming model, we decorated the Fortran kernels with OpenACC directives. This expedited our ability to run at large scales on Summit's GPUs, where we achieved a significant speedup over the CPUs on Summit. The second programming model involved rewriting the Fortran kernels in C++ and using AMReX's Kokkos-like lambda abstractions for running on the GPU. This resulted in similar speedups on Summit's GPUs over merely utilizing the CPUs. Both approaches involved AMReX's management of memory transfers between the device and host. In this work, we compare and contrast the benefits and pitfalls to both programming approaches regarding performance, performance portability, and productivity. We also discuss advantages we have found in taking the time to modernize our code and why have chosen a specific pathway to prepare our code for the future DOE exascale machines.

exascale computing↗