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DOE OSTI2026

Physics basis for the reference flat-top plasma scenario in the ST–E1 fusion power plant

As part of the U.S. Department of Energy’s Milestone-Based Fusion Energy Development Program, Tokamak Energy has completed the pre-concept design of the ST–E1 fusion power plant. ST–E1 is envisaged to operate in two phases: a pilot plant phase, targeting sustained net power production of 300 - 500 MWe for a duration >1 hr, followed by a commercial power plant phase targeting steady-state operations and a normalised overnight capital cost of ⩽12 000 $\$$/kWe. The design process adopted was highly iterative, integrating all major plant systems and progressing in a phased fidelity approach. At the pre-conceptual stage, the emphasis has been on exploring the design space, identifying the main system-level trade-offs, and making the key decisions that define the overall plant concept, rather than optimising a single operating point. This paper, part of a focused collection detailing the ST–E1 pre-concept design, addresses the development of a series of reference flat-top plasma operating points for the pilot plant phase. A modelling workflow was established to develop and assess candidate plasma design points and explore key dependencies. The workflow includes integrated core plasma modelling, magnetohydrodynamic (MHD) stability assessment, equilibrium generation, scrape-off-layer and exhaust modelling, heating & current drive design and optimisation, and turbulent transport modelling. Using this framework, the impact of several key parameters on the flat-top operating space was investigated, including the density limit, core radiation fraction and divertor power loading, level of external heating and curent drive power and assumed pedestal characteristics. The MHD stability, controllability and micro-stability characteristics of these plasmas were also analysed. These investigations informed the definition of a set of fully non-inductive, flat-top reference operating points that satisfy the high-level ST–E1 mission, including a low and high density case, a case that is stable to resistive wall modes and a case with reduced divertor power loading.

ST–E1↗

DOE OSTI2023

Investigation of SF6 Alternatives in Spark Gap Switches for GWP Reduction

This primary purpose of this project was to evaluate alternative gas mixtures to sulfur hexafluoride (SF6) developed for high voltage power delivery applications for use in high voltage spark gap switches. These SF6 alternatives lower global warming potential emissions and enable improvements to the pressure-voltage design space. A combined experimental, computational, and theoretical study was used to quantify the impact of persistent breakdown products on the breakdown distribution of SF6-replacement gas mixtures. Viable SF6 replacements suitable for use in spark gap switches were studied to enable performance and agility improvements for next-generation pulsed power research relevant to national security missions. Experimental campaign included establishing parameters of switch gases as function of concentration. Various concentrations and pressures were tested for trends in breakdown voltage, repeatability, and durability, and breakdown constituents. A zero-dimensional plasma global model was used to simulate the plasma arc decay and recombination process in spark-gap switches relevant to the Z machine. Finally, a complete and consistent set of electron-neutral collision cross-sections for the novel insulating gas C4F7N is reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

An introduction to neuromorphic computing and its potential impact for unattended ground sensors

Neuromorphic computers are hardware systems that mimic the brain’s computational process phenomenology. This is in contrast to neural network accelerators, such as the Google TPU or the Intel Neural Compute Stick, which seek to accelerate the fundamental computation and data flows of neural network models used in the field of machine learning. Neuromorphic computers emulate the integrate and fire neuron dynamics of the brain to achieve a spiking communication architecture for computation. While neural networks are brain-inspired, they drastically oversimplify the brain’s computation model. Neuromorphic architectures are closer to the true computation model of the brain (albeit, still simplified). Neuromorphic computing models herald a 1000x power improvement over conventional CPU architectures. Sandia National Labs is a major contributor to the research community on neuromorphic systems by performing design analysis, evaluation, and algorithm development for neuromorphic computers. Space-based remote sensing development has been a focused target of funding for exploratory research into neuromorphic systems for their potential advantage in that program area; SNL has led some of these efforts. Recently, neuromorphic application evaluation has reached the NA-22 program area. This same exploratory research and algorithm development should penetrate the unattended ground sensor space for SNL’s mission partners and program areas. Neuromorphic computing paradigms offer a distinct advantage for the SWaP-constrained embedded systems of our diverse sponsor-driven program areas.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

High Flux Isotope Reactor Low Enriched Uranium U-10Mo Fuel Design Parameters

Activities to convert the HFIR from HEU to LEU are ongoing as part of the US Department of Energy (DOE) National Nuclear Security Administration (NNSA) nuclear nonproliferation mission. Design activities to study the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a uranium-molybdenum (U-10Mo) monolithic alloy fuel. This high-density alloy contains 90 wt % uranium and 10 wt % molybdenum and has a uranium density of 15.318gU/cm 3 . The goal of these studies is to generate several candidate HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. Recent advancements in modeling and simulation tools and design methods enabled a thorough analysis of the available design space with U-10Mo fuel. A surrogate model used this analysis as training data to quickly determine the performance of a design given specific design parameters. An optimization module used this surrogate model to quickly search this multidimensional search space given specific desired performance characteristics. This approach was made possible by the large available design space with U-10Mo fuel. Shift, a Monte Carlo tool optimized for high-performance computing (HPC) architectures, was used for faster calculation and better data management for reactor physics simulations. Once most of these design studies were complete, a new suite called the Python HFIR Analysis and Measurement Engine (PHAME) was developed to connect all fuel design analysis steps, making design studies more efficient and reproducible. The post-processing capabilities of these new tools are leveraged for the information provided herein. Leveraging these tools, several candidate fuel designs were selected with varying levels of feature complexity and reactor performance. This report provides design feature details for four selected HFIR LEU U-10Mo fuel designs and their corresponding performance and safety metrics. Nominal best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities, are provided. Simulations show that the high uranium density of U-10Mo fuel provides a large potential design space that enables various LEU designs to meet HEU core performance metrics and safety requirements with a power increase from 85 MW (HEU) to 95 MW or 100 MW (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Proliferated Resilient Economical Half-Meter Aperture Space Telescopes (PREEMPT)

The PREEMPT LDRD was motivated by a major national need for better space-based imaging systems that are both high performing and affordable for the US Government. Current optical payloads for intelligence, surveillance and reconnaissance (ISR) and space domain awareness (SDA) missions can cost hundreds of millions of dollars and take years to develop, which makes it difficult to build the large constellations required for persistent, world-wide coverage. To address this, the team aimed to advance a different kind of large-aperture (>25 cm) telescope, called a monolithic telescope, in which key optical surfaces are built into a single piece of fused silica. This design greatly reduces payload and spacecraft complexity, the need for precision focus actuators, improves mechanical and thermal robustness, and lowers cost when compared with traditional Cassegrain telescopes that rely on many precisely aligned components. The project focused on five primary thrusts. The first thrust was to advance the concept of a V10, 25 cm, monolithic telescope forward from optical design to flight-ready stage. This was accomplished in partnership with Optimax, who delivered the first test unit in the early stages of the LDRD. The team developed several technologies necessary for this optic to be integrated into a flight demonstration. These include carbon fiber housings, highly detailed structural and thermal models and stress-reducing elastic averaging Hirth groove designs. These technologies resulted in a successful maturation of the optic, which is now slated to fly in late 2026/early 2027 for a demonstration mission. The second thrust was to advance the manufacturability of these optics. In collaboration with NIF’s optical manufacturing shop, we reduced polishing time from 480 hours to 65 hours through the implementation of optimized processes and new tools. The NIF team utilized a conceptual V8 (18 cm) optic to demonstrate this optimization, though it can be applied to the rest of the monolithic optic portfolio. Third, the team developed the first conceptual V20 (50 cm) payload, which is slated to be the next generation of LLNL optical payload systems. A set of structural, dynamic and thermal simulations were performed to identify potential challenges in the future development of this payload. Early-stage simulations suggest the payload is feasible, though thermal management will be the key focus area to maintain optimal performance. Fourth, a non-linear model of Viton was developed, to further enhance the reliability of our structural and dynamic models for future payloads. Viton acts as the primary interface material between the optic and its housing. Lastly, the team focused on successfully displaying the feasibility of using additively manufactured metal composites for optical space payloads. The team successfully demonstrated layer by layer deposition of Al-SiC composites, which have highly tunable structural and coefficient of thermal expansion (CTE) properties. These are crucial for optical payloads because CTE mismatch is one of the causes for degraded optical performance for telescopes in orbit. Overall, the work showed that monolithic telescopes could become a practical, lower-cost path to high-resolution space imaging for both national security and scientific missions.

42 ENGINEERING↗

DOE OSTI2021

Modeling of Am-241 as an alternative fuel source in a radioisotope thermoelectric generator

Radioisotope thermoelectric generators (RTGs) have been utilized in the USA to power satellites and space exploration equipment for over half a century. In our preceding paper, Dustin and Borrelli (2021), we assessed the performance of 241 Am as an alternative to 238 Pu by modeling the specific decay-heat and gamma spectra of several potential radioisotopes in SCALE-ORIGEN, and comparing these with 238 Pu An analysis of heat output, heat stability, safety, availability and required mass showed that of the isotopes reviewed, 241 Am had the greatest potential for replacing 238 Pu, with additional design considerations. In our current work, we have assessed radiation transport for two configurations of an 241 Am powered Multi-Mission Radioisotope Thermoelectric Generator (MMRTG), due to the potential health effects for operators, fabricators, and others with the potential to be exposed to neutrons and lower energy gamma rays. We have modeled the use of americium as a fuel source replacement for plutonium in current MMRTG designs. The assessment has been performed using MCNP6, in terms of neutron and gamma emissions that might interfere with sensitive equipment and power system production. The radiation transport behavior in terms of dose rate of the 241 Am fueled models is compared with that of a 238 Pu fueled model. Finally, additional work was performed to validate modeling simplifications with regards to thermocouple material configurations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Toward a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Toward Complete Characterization: Prospects for Directly Imaging Transiting Exoplanets

High-contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure planet radius or mass. Our future understanding of directly imaged exoplanets will therefore rely on extrapolated models of planetary atmospheres and bulk composition, which need robust calibration. We estimate the population of extrasolar planets that could serve as calibrators for these models. Critically, this population of “standard planets” must be accessible to both direct imaging and the transit method, allowing for radius measurement. We show that the search volume of a direct imaging mission eventually overcomes the transit probability falloff with semimajor axis, so that as long as cold planets are not exceedingly rare, the population of transiting planets and directly imageable planets overlaps. Using current extrapolations of Kepler occurrence rates, we estimate that ∼8 standard planets could be characterized shortward of 800 nm with an ambitious future direct imaging mission like LUVOIR-A and several dozen could be detected at the V band. We show the design space that would expand the sample size and discuss the extent to which ground- and space-based surveys could detect this small but crucial population of planets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Conceptual design of HTS magnets for fusion nuclear science facility

Second-generation high temperature superconductors (HTS) are available for producing >20 T at the magnet bore compared to 13–16 T for lower temperature superconducting (LTS) toroidal field magnets proposed in recent fusion energy systems studies (FESS) of Fusion Nuclear Science Facility (FNSF). HTS may enable higher fusion power density and smaller device size. High current density cables of multi-layered REBCO tapes have achieved >10 kA at 4–20 K operation in short sample tests for fusion. High current density cables are required for engineering design of FNSF to allow space for interior plasma components. High current density HTS magnets are particularly attractive in reducing the size of a fusion device, beneficial for compact tokamaks, due to their space constraints. Successful HTS magnet development may enable the design of smaller and cheaper fusion pilot plants with a mission of demonstrating net electricity. It may also offer significant cost and performance advantages in non-fusion applicants such as nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI). Furthermore, we developed HTS magnet design concepts for a compact FNSF radial build in order to define the coil size, winding pack mechanical loading and engineering requirements. Partnering with vendors in the US, PPPL is also testing high current cable prototypes aiming at enabling low cost cable technology toward 100 A/mm 2 engineering current density over the winding pack desired in high field model coil development for compact fusion pilot plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Advancing Theory and Modeling Efforts in Heliophysics

Heliophysics theory and modeling build understanding from fundamental principles to motivate, interpret, and predict observations. Together with observational analysis, they constitute a comprehensive scientific program in heliophysics. As observations and data analysis become increasingly detailed, it is critical that theory and modeling develop more quantitative predictions and iterate with observations. Advanced theory and modeling can inspire and greatly improve the design of new instruments and increase their chance of success. In addition, in order to build physicsbased space weather forecast models, it is important to keep developing and testing new theories, and maintaining constant communications with theory and modeling. Maintaining a sustainable effort in theory and modeling is critically important to heliophysics. We recommend that all funding agencies join forces and consider expanding current and creating new theory and modeling programs–especially, 1. NASA should restore the HTMS program to its original support level to meet the critical needs of heliophysics science; 2. a Strategic Research Model program needs to be created to support model development for next-generation basic research codes; 3. new programs must be created for addressing mission-critical theory and modeling needs; and 4. enhanced programs are urgently required for training the next generation of theorists and modelers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Trajectory design via unsupervised probabilistic learning on optimal manifolds

Abstract This article illustrates the use of unsupervised probabilistic learning techniques for the analysis of planetary reentry trajectories. A three-degree-of-freedom model was employed to generate optimal trajectories that comprise the training datasets. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. We find that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. Using the diffusion coordinates on the graph of training samples, the probabilistic framework subsequently augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path planning algorithm. In this framework, the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time.

42 ENGINEERING↗

DOE OSTI2025

Efficient and Selective Chemical Transformations in Highly Charged and Confined Nanodroplets

The acceleration of chemical reaction rates and the increased product selectivity in microdroplets compared to that in bulk solutions has become a topic of increasing interest that has been extensively characterized by electrospray ionization mass spectrometry (ESI-MS). However, the sources of this acceleration and the detailed relationships between droplet properties and resulting reaction rate acceleration are still under debate. Moreover, droplet properties are governed by multiple interrelated experimental parameters, i.e., electrospray voltage, solution flow rate, etc., which makes it difficult and time-consuming to explore this diverse parameter space using traditional manual experimental or computational approaches. In this work, we developed an automated experimental platform integrating reactions in controlled charged microdroplet environments with ESI-MS characterization and sequential hybrid Bayesian modeling, as well as an optimal experimental design framework, to achieve multidimensional parameter optimization for higher reaction turnover rates, based on a model reaction of tetraethylenepentamine (TEPA) with carbon dioxide. With the current platform, we have achieved automated scans with a range of electrospray voltages and solution flow rates, and determined and optimized parameter settings to achieve increased reaction turnovers. We have also linked this platform to the underlying properties of droplets via a hybrid model incorporating physics, high-level theoretical calculations, and machine learning (ML) approaches. The autonomous platform is broadly applicable to a range of chemical reactions relevant to DOE’s mission in chemical separations, catalysis, and materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Combined Heat Shield and Solar Thermal Propulsion System for an Oberth Maneuver

As humanity continues its exploration of space, many space missions are enabled by increases in speed. Examples include outer planet and dwarf planet exploration missions and missions that travel through our solar system into interstellar space. For many of these applications speeds of >10 astronomical units per year (AU/yr) are desired. A powered gravity assist around the Sun may offer the best option for reaching this goal; however, current heat shields and kick stages are too heavy or generate too little thrust. Solar thermal propulsion overcomes this tradeoff by converting the heat of the Sun into thrust. By tripling the specific impulse relative to chemical propulsion and by enabling a smaller perihelion through active cooling, this approach nearly doubles the escape velocity. Our team has designed and built working solar thermal propulsion prototypes out of materials that can survive 2700 K at a 30 x 30 cm scale. These benchtop-scale demonstrations have thus far validated the simplifying assumptions that underlie our thermal and propulsion models. Despite growing confidence that a full-scale heat shield/heat exchanger can survive an Oberth maneuver, many questions remain regarding the feasibility of long-term cryogenic storage of hydrogen propellant.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Galactic cosmic ray simulation at the NASA space radiation laboratory – Progress, challenges and recommendations on mixed-field effects

For missions beyond low Earth orbit to the moon or Mars, space explorers will encounter a complex radiation field composed of various ion species with a broad range of energies. Such missions pose significant radiation protection challenges that need to be solved in order to minimize exposures and associated health risks. An innovative galactic cosmic ray simulator (GCRsim) was recently developed at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL). The GCRsim technology is intended to represent major components of the space radiation environment in a ground analog laboratory setting where it can be used to improve understanding of biological risks and serve as a testbed for countermeasure development and validation. The current GCRsim consists of 33 energetic ion beams that collectively simulate the primary and secondary GCR field encountered by humans in space over the broad range of particle types, energies, and linear energy transfer (LET) of interest to health effects. A virtual workshop was held in December 2020 to assess the status of the NASA baseline GCRsim. Workshop attendees examined various aspects of simulator design, with a particular emphasis on beam selection strategies. Experimental results, modeling approaches, areas of consensus, and questions of concern were also discussed in detail. This report includes a summary of the GCRsim workshop and a description of the current status of the GCRsim. This information is important for future advancements and applications in space radiobiology.

79 ASTRONOMY AND ASTROPHYSICS↗

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↗