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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerator Physics at NSLS-II: Research Accomplishments in 2024

NSLS-II accelerator physicists advanced the operational performance and scientific capabilities of NSLS-II, providing regular lattice characterization and correction, injec tion optimization, vertical emittance control, and beam dynamics reports with corre lation analysis. We further developed advanced lattice characterization techniques and studies on impedance, beam-induced heating, and higher-harmonic RF cavity effects to support NSLS-II and its high-brightness upgrade. The assessment of free-electron laser options for the NSLS-II upgrade has been completed. We carried out comprehensive studies focused on complex bend magnets and novel efficient injection schemes for next-generation low-emittance synchrotrons. We contributed to the Electron-Ion Collider project, including Electron Storage Ring lattice design, beam diagnostics, and injector studies. The physicists participated in international collaborations, including the development of Python-based Middle Layer software, and participated in key accel erator physics workshops and scientific meetings. The main research accomplishments achieved in 2024 are summarized in this report.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

LLM Benchmarking with LLaMA2: Evaluating Code Development Performance Across Multiple Programming Languages

The rapid evolution of large language models (LLMs) has opened new possibilities for automating various tasks in software development. This paper evaluates the capabilities of the LLaMA 2-70B model in automating these tasks for scientific applications written in commonly used programming languages. Using representative test problems, we assess the model's capacity to generate code, documentation, and unit tests, as well as its ability to translate existing code between commonly used programming languages. Our comprehensive analysis evaluates the compilation, runtime behavior, and correctness of the generated and translated code. Additionally, we assess the quality of automatically generated code, documentation, and unit tests. Here, our results indicate that while LLaMA 2-70B frequently generates syntactically correct and functional code for simpler numerical tasks, it encounters substantial difficulties with more complex, parallelized, or distributed computations, requiring considerable manual corrections. We identify key limitations and suggest areas for future improvements to better leverage AI-driven automation in scientific computing workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Tale from the Trenches: Applying Metamorphic and Differential Testing to Bioinformatics Software

Metamorphic and differential testing have been proposed as best practices for testing software that is difficult to test, such as for programs in scientific domains. An assumption is that these approaches can be easily customized and applied to almost any domain. However, scientific software is often data-driven, and metamorphic relations may require significant domain knowledge to develop. In addition, tools are often written for ad-hoc experimentation by the scientists and often embed many assumptions about the importance and representation of different natural phenomena. In this paper, we present our experience applying both metamorphic and differential testing to a set of four computational biology tools that predict the growth of an organism. While our original goal was to evaluate these techniques to improve our system-level testing, we encountered multiple roadblocks along the way. Although we did find faults (some confirmed by developers), we also uncovered a set of challenges, including the considerable manual effort required for (a) defining domain-specific tests, (b) validating correctness, and (c) distinguishing between issues stemming from poor data and those arising from incorrect software.

Marsh, Alexis L [Iowa State University/Ames Labora↗
DOE OSTI2024

Introducing NOODLES: Collaborative Visualization in a Flavorful Package

We introduce NOODLES, a lightweight collaborative visualization and analysis protocol. NOODLES was developed to enable new scientific workflows while enhancing existing pipelines. Using a technology-minimal approach to strengthen applicability, this protocol allows researchers to tie disparate software together as well as making domain specific visualizations accessible across various platforms and form factors. In this talk we discuss background, challenges, and gaps in the current tool landscape that lead to the development of the protocol. We then describe the design of the protocol and present several use cases to demonstrate the efficacy of NOODLES in addressing complex visualization challenges and how it co-exists with existing tools. We conclude by outlining in-progress work and potential avenues for future development within the NOODLES framework.

collaborative analysis↗
DOE OSTI2023

Good Practices for High-Quality Scientific Computing

Experimental and observational sciences have developed robust practices for conducting experiments, maintaining their instruments, and record keeping for provenance. Computational science has only recently begun to confront the issue of quality of their instrument, the software, and the credibility of their scientific output. Most of the available literature in software engineering relates to enterprise software. While it can inform practices in scientific software, adjustments are usually needed. From time to time quality conscious practitioners have published collections of best practices for scientific software. Here, this article provides one more such list but with updated suggestions, motivated by the need to keep up with the rapid changes in the computing industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The Power and Energy Storage Systems Toolbox–PSTess (V1.0)

This document describes the Power and Energy Storage Systems Toolbox for MATLAB, abbreviated as PSTess. This computing package is a fork of the Power Systems Toolbox (PST). PST was originally developed at Rensselaer Polytechnic Institute (RPI) and later upgraded by Dr. Graham Rogers at Cherry Tree Scientific Software. While PSTess shares a common lineage with PST Version 3.0, it is a substantially different application. This document supplements the main PST manual by describing the features and models that are unique to PSTess. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m , and it serves the dual role of representing ESS operational constraints and the generator/converter interface. As in the WECC REGC_A model, the generator/converter interface is modeled as a controllable current source with the ability to modulate both real and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, Type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources or FACTS devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Reimagining Codesign

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Reimagining Codesign (ReCoDe). Codesign is the process of jointly designing interoperating components of a computing system—in particular: applications, algorithms, system software, programming models, and the hardware on which they run. The goal is to maximize the overall performance, efficiency, and other desirable qualities of the system as a whole. Codesign is a standard methodology in the embedded-systems community, where space, power, and cost constraints are commonly pitted against execution speed for a tightly constrained feature set. Over the last decade, the DOE has invested in codesign efforts to foster the development of exascale computing systems for broad classes of scientific and engineering applications. The ReCoDe workshop hopes to explore how scientific applications of interest to the DOE can be accelerated through close interactions with hardware designers and software-stack developers, in which all components adapt to each other’s requirements and constraints. We want to answer the question of what are the key tools and methodologies for accomplishing codesign in today’s computing landscape, and what will be the highest impact targets for meeting DOE’s emerging mission requirements. This workshop aims to bring together DOE, industry, and academia to identify opportunities to build on past codesign successes and identify new areas that are either emerging or that may need reimagining for the future. We want to continue to find opportunities that can be pursued as a joint effort and continue to break down the traditional customer/vendor dichotomy with true partnerships. From this work, DOE will benefit from increased application performance relative to what stock hardware or existing general-purpose roadmaps can provide, and vendors will benefit from expanding their hardware’s capabilities to address needs they might have not otherwise anticipated and thereby create more widespread interest in their products. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees—from DOE, industry, and academia—will produce a report for ASCR that summarizes the findings made during the workshop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Benchmark Suite for Evaluating Scientific AI Workloads on GPUs

AI applications have been steadily increasing in the allocation portfolio among leadership computing facilities. These applications depend on deep learning frameworks with hardware acceleration and underlying software systems. With the rapid development of applications, software stacks, and hardware devices, it is essential to evaluate the performance of core operations in AI workloads for direction of optimizations and procurement of next-generation high-performance computing (HPC) infrastructures. Currently, most benchmarks lack scientific AI workloads. So, we present DeepKernelBench and the experimental results of evaluating the benchmark suite for early observations and performance comparisons on datacenter GPUs using representative workloads for scientific AI, including Attentions, General matrix multiplications, Geometrics and Fourier neural operations.

Jin, Zheming [Advanced Micro Devices (AMD)]↗
DOE OSTI2022

Code Verification and Solution Verification framework in pin-resolved neutron transport code MPACT

Program verification in scientific computing encompasses the application of formal and mathematical techniques to a scientific computing code for its credibility, accuracy, and validity. Code Verification identifies bugs and performance issues in the software development stage. Solution Verification assesses the applicability of the code and the accuracy of the solution to problems of interest. Both activities utilize application cases and quantify the error against prescribed acceptance criteria. However, simply executing more application cases does not guarantee stronger or more comprehensive credibility. Here, we establish a verification framework that involves Code Verification and Solution Verification, both of which work together such that the overarching goal of “converge to the correct answer for the intended application” can be reasonably inferred. The application of such a verification framework is demonstrated using the pin-resolved neutron transport code MPACT, where standard unit tests and regression tests are covered, and where the Method of Exact Solutions and the Method of Manufactured Solutions are successfully used. Additionally, the applicability of Method of Manufactured Solutions is extended to the OECD/NEA C5G7 benchmark problems of practical material and geometric configurations. Solution Verification activities are demonstrated on a practical hierarchy of application models of increasing complexity ranging from 2D pin cell problems to 3D assembly problems. The convergence behavior and rate of convergence with respect to each individual variable are studied and provided. This framework can be adapted broadly to other fields involving scientific computing codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting?

In theory, the same sea-ice models could be used for both research and operations, but in practice, differences in scientific and software requirements and computational and human resources complicate the matter. Although sea-ice modeling tools developed for climate studies and other research applications produce output of interest to operational forecast users, such as ice motion, convergence, and internal ice pressure, the relevant spatial and temporal scales may not be sufficiently resolved. For instance, sea-ice research codes are typically run with horizontal resolution of more than 3 km, while mariners need information on scales less than 300 m. Certain sea-ice processes and coupled feedbacks that are critical to simulating the Earth system may not be relevant on these scales; and therefore, the most important model upgrades for improving sea-ice predictions might be made in the atmosphere and ocean components of coupled models or in their coupling mechanisms, rather than in the sea-ice model itself. This paper discusses some of the challenges in applying sea-ice modeling tools developed for research purposes for operational forecasting on short time scales, and highlights promising new directions in sea-ice modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Abstracts of the 2025 51st Annual NATAS Conference

The North American Thermal Analysis Society (NATAS) is pleased to announce its 51st Annual Conference, held jointly with the IX International Baekeland Symposium. This premier event unites scientists, practitioners, and students from academia, industry, and government to explore the forefront of materials science. The NATAS conference provides a dynamic forum for attendees to delve into the latest advancements in thermal analysis, rheology, and materials characterization. The technical program will highlight new developments in instrumentation and software, alongside practical applications across a wide range of industries. Concurrently, the Baekeland Symposium will showcase cutting-edge scientific, technical, and industrial innovations in the field of high-performance thermosetting polymers. The synergy of this joint meeting creates a unique platform for cross-disciplinary collaboration, fostering the exchange of novel ideas and sparking new research opportunities. Featuring technical presentations, poster sessions, and plenary lectures from renowned experts and emerging graduate students, the conference offers an ideal environment for networking and professional development. We invite you to join us to discover state-of-the-art techniques, discuss groundbreaking research, and connect with peers and leaders in the thermal and materials community.

batteries↗
DOE OSTI2022

Ideas and perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries

Carbon (C) and greenhouse gas (GHG) research has traditionally required data collection and analysis using advanced and often expensive instruments, complex and proprietary software, and highly specialized research technicians. Partly as a result, relatively little C and GHG research has been conducted in resource-constrained developing countries. At the same time, these are often the same countries and regions in which climate change impacts will likely be strongest and in which major science uncertainties are centered, given the importance of dryland and tropical systems to the global C cycle. Increasingly, scientific communities have adopted appropriate technology and approach (AT&A) for C and GHG research, which focuses on low-cost and low-technology instruments, open-source software and data, and participatory and networking-based research approaches. Adopting AT&A can mean acquiring data with fewer technical constraints and lower economic burden and is thus a strategy for enhancing C and GHG research in developing countries. However, AT&A can have higher uncertainties; these can often be mitigated by carefully designing experiments, providing clear protocols for data collection, and monitoring and validating the quality of obtained data. For implementing this approach in developing countries, it is first necessary to recognize the scientific and moral importance of AT&A. At the same time, new AT&A techniques should be identified and further developed. All these processes should be promoted in collaboration with local researchers and through training local staff and encouraged for wide use and further innovation in developing countries.

Kim, Dong-Gill↗
DOE OSTI2024

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities

Scientific user facilities, such as synchrotron beamlines, are equipped with a wide array of hardware and software tools that require a codebase for human-computer-interaction. This often necessitates developers to be involved to establish connection between users/researchers and the complex instrumentation. The advent of generative AI presents an opportunity to bridge this knowledge gap, enabling seamless communication and efficient experimental workflows. Here we present a modular architecture for the Virtual Scientific Companion by assembling multiple AI-enabled cognitive blocks that each scaffolds large language models (LLMs) for a specialized task. With VISION, we performed LLM-based operation on the beamline workstation with low latency and demonstrated the first voice-controlled experiment at an x-ray scattering beamline. The modular and scalable architecture allows for easy adaptation to new instruments and capabilities. Development on natural language-based scientific experimentation is a building block for an impending future where a science exocortex—a synthetic extension to the cognition of scientists—may radically transform scientific practice and discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Topical Group on Application and Industry Community Engagement Frontier Snowmass 2021 (Summary Report)

HEP community leads and operates cutting-edge experiments for the DOE Office of Science which have challenging sensing, data processing, and computing requirements that far surpass typical industrial applications. To make necessary progress in the energy, material, and fundamental sciences, development of novel technologies is often required to enable these advanced detector and accelerator programs. Our capabilities include efficient co-design, which is a prerequisite to enable the deployment of advanced techniques in a scientific setting where development spans from rapid prototyping to robust and reliable production scale. This applies across the design spectrum from the low level fabrication techniques to the high level software development. It underpins the requirement for a holistic approach of innovation that accelerates the cycle of technology development and deployment. The challenges set by the next generation of experiments requires a collaborative approach between academia, industry and national labs. Just a single stakeholder will be unable to deliver the technologies required for the success of the scientific goals. Tools and techniques developed for High Energy Physics (HEP) research can accelerate scientific discovery more broadly across DOE Office of Science and other federal initiatives and also benefit industry applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence (University of Delaware)

This report summarizes the activities, technical accomplishments, and outcomes of the RAPIDS2 Institute project at the University of Delaware (UD). The RAPIDS2 Institute was a large multi-institution project with the objective of assisting SciDAC and Office of Science application teams in the use of DOE supercomputing resources to achieve scientific breakthroughs. The UD team contributed to this effort through work on formal software verification. This thrust aims to reduce software developer time and effort, especially regarding debugging and testing, and to increase confidence in the correctness of the results computed by the software.

97 MATHEMATICS AND COMPUTING↗