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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Open library of g-functions for 34,321 configurations

Thermal response functions, known as g-functions, are commonly used in ground heat exchanger design tools and whole building energy simulation programs to simulate the ground heat exchanger performance. Calculation of g-functions can be quite computationally time-consuming, particularly as the number of boreholes gets large. However, once the g-function is computed, the actual simulation time can be quite short, particularly if a hybrid time-step (Cullin and Spitler 2011) approach is used. Because of this, pre-computed g-function libraries are commonly used in design tools and building simulation tools. This paper describes development of a new, publicly available library containing g-functions for 34,321 borehole field configurations; for each configuration, gfunctions are provided for 5 depths to allow interpolation between different borehole-to-height ratios. The available configurations include configurations in standard shapes: lines, rectangles, open rectangles, L-shapes, and U-shapes. It also includes new configurations: C-shapes, lopsided-U-shapes, and zoned rectangles, which are rectangular configurations with different interior and perimeter spacing of the boreholes.

Spitler, Jeffery↗
DOE OSTI2018

A computational thrombus formation model: application to an idealized two-dimensional aneurysm treated with bare metal coils

Cardiovascular implantable devices alter the biofluid dynamics and biochemistry of the blood in which they are placed. These perturbations can lead to thrombus formation which may or may not be desired, depending on the application. In this work, a computational model is developed that couples biofluid dynamics and biochemistry to predict the clotting response of blood to such devices. The model consists of 28 advection–diffusion–reaction partial differential equations to track proteins in the blood involved in clotting and utilizes boundary flux terms to model the initiation of the intrinsic clotting pathway at thrombogenic device surfaces. We use this model to simulate the transient clot growth within a 2D idealized bifurcation aneurysm filled with various distributions of bare metal coils with similar packing densities. The clot model predicts initial clot formation to occur in areas along coil surfaces where flow is minimal and where time-averaged shear rates are the smallest. Among the six coil-filled aneurysm cases simulated, maximum thrombus occlusion ranged between 80.8 and 92.2% of the post-treatment aneurysm volume and was achieved 325–450 s after treatment. Finally, with further refinement and validation, the computational clotting model will be a valuable engineering tool for evaluating and comparing the relative performance of cardiovascular implantable devices.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Hyper-Heuristics to Automatically Target Code to Computer Architectures

With each new generation of High Performance Computing (HPC) architecture, the gap between peak theoretical performance and the observed performance is growing. The goal of this research is to develop a tool to utilize hyper-heuristics to target code to a computational environment. In order to test this, sorting algorithms will be evolved on several different architectures. The final solutions will then migrate to all other architectures and their fitnesses compared. If the natively-evolved algorithms out-perform all others, then it can be concluded that the tool successfully targeted its solutions to the architecture of origin. This is the first step towards creating a program-agnostic tool for optimizing code to the native environment. The results are pending testing on the high performance cluster. If it can be shown that the tool is able to optimize solutions for the environment, then the door opens to automatically optimizing entire programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Summarizing the interoperabilities between xSDK members

Rapid, efficient production of high-quality, sustainable extreme-scale scientific applications is best accomplished using a rich ecosystem of state-of-the art reusable libraries, tools, lightweight frameworks, and defined software methodologies, developed by a community of scientists who are striving to identify, adapt, and adopt best practices in software engineering. The vision of the xSDK is to provide infrastructure for and interoperability of a collection of related and complementary software elements — developed by diverse, independent teams throughout the high-performance computing (HPC) community — that provide the building blocks, tools, models, processes, and related artifacts for rapid and efficient development of high-quality applications. A primary component, and challenge, of the xSDK is to improve interoperability among software libraries and domain components. This document summarizes the current and planned interoperabilities of the twenty-three xSDK member packages as of March 2021. Additionally, the status of the xSDK example codes that demonstrate and test the interoperabilities within the xSDK is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

High-Fidelity Accelerated Design of High-performance Electrochemical Systems

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical materials will be critical, but their development currently relies heavily on human-time-intensive experimental trial and error and computationally expensive first-principles, meso-scale and continuum simulations. To accelerate this process, our team has developed the AutoMat platform. AutoMat can accelerate development of new electrochemical materials along two avenues: first, automated input generation and management of simulations at multiple lengthscales as well as “handoff” of outputs from one lengthscale as inputs to the next; and second, replacement of the most computationally intensive simulation processes with machine-learned surrogate models. The crux of our team’s effort was not “reinventing the wheel” by developing entirely new techniques, but rather building a “superhighway” that allows existing state-of-the-art techniques to run faster and more smoothly than before. AutoMat can utilize tools spanning from first-principles quantum chemistry computations to automated robotic experimentation, and is driven by design space search techniques to reduce the number of iterations through the full simulation loop by rapidly targeting promising regions of design spaces such as single-atom alloy catalysts or blends of liquid electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2015

mdtmFTP

To address the high-performance challenges of data transfer in big data era, we research, develop, and implement mdtmFTP: a High-performance Data Transfer Tool in Bigdata Era. DOE’s Advanced Scientific Computing Research (ASCR) office has funded Fermilab and Brookhaven National Laboratory to collaboratively work on the Multicore-Aware Data Transfer Middleware (MDTM) project. MDTM aims to accelerate data movement toolkits on multicore systems. mdtmFTP is the latest outcome of this continued research effort. mdtmFTP is a high-performance data transfer tool that builds upon the MDTM middleware. Initial tests show that mdtmFTP performs better than existing data transfer tools

Zhang, L.↗
DOE OSTI2025

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Input-Output Model for MACCS Nuclear Accident Imp Acts Estimation

Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Toward a Seamless Integration of Computing, Experimental, and Observational Science Facilities: A Blueprint to Accelerate Discovery

The Department of Energy, Office of Science operates world-leading facilities for experimental, observational, and computational science. DOE supercomputing facilities will reach performance at the scale of ExaFLOPs in the coming years, enabling new vistas of scale and precision for large scale simulations and data analysis. Experimental scientific facilities are undergoing similar upgrades that will lead to higher data rates and correspondingly larger computational demands, and will increase the need for near-real-time processing and resilient support for more complex workflows. A transformation of science is underway, with workloads at supercomputing facilities increasingly driven by this explosion of data from instruments and experimental facilities, as well as the accelerating use of Artificial Intelligence (AI) as a tool for scientific discovery. A seamless integration of computing, networking, instruments, and experimental facilities is required to support these emerging workloads and open up a new frontier of U.S. leadership in scientific discovery. We propose to accomplish this by providing frictionless access to the ASCR supercomputing facilities. We describe our vision of combining the power of ASCR supercomputers and networking infrastructure into an integrated scalable fabric, available to end user scientists via interfaces that aim to automate and simplify access to high performance computing systems. This will enable unprecedented computational science capabilities for experimental and observational facilities, and will create new opportunities to combine large simulations and modeling with experimental facility data analysis. This blueprint for creating an integrated network of computational and experimental facilities will provide an enriched discovery environment and open doors for new scientific communities to access the DOE’s world-leading computing and networking capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving Milling Performance on New Computer Numerical Control Machining Centers with Machining Dynamics

This project is directed at improving the efficiency and productivity of the existing installed US machine tool base by correcting a fundamental system-wide flaw in the existing programmable machine tool infrastructure. The project will catalyze a shift from a geometry-only mindset to a geometry -and-machine -performance mindset. The project will lead to a dramatic overhaul of the existing ecosystem for programming of Computer Numerically Controlled (CNC) machine tools, and will result in energy savings, cost savings, reduced scrap, and improved competitiveness of US manufacturers.

42 ENGINEERING↗
DOE OSTI2015

Radio-guided occult lesion localisation using iodine 125 Seeds “ROLLIS” to guide surgical removal of an impalpable posterior chest wall melanoma metastasis

Cancer screening and surveillance programmes and the use of sophisticated imaging tools such as positron emission tomography-computed tomography (PET-CT) have increased the detection of impalpable lesions requiring imaging guidance for excision. A new technique involves intra-lesional insertion of a low-activity iodine-125 ({sup 125}I) seed and detection of the radioactive signal in theatre using a hand-held gamma probe to guide surgery. Whilst several studies describe using this method to guide the removal of impalpable breast lesions, only a handful of publications report its use to guide excision of lesions outside the breast. We describe a case in which radio-guided occult lesion localisation using an iodine 125 seed was used to guide excision of an impalpable posterior chest wall metastasis detected on PET-CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗
DOE OSTI2013

The OpenMC Monte Carlo particle transport code

A new Monte Carlo code called OpenMC is currently under development at the Massachusetts Institute of Technology as a tool for simulation on high-performance computing platforms. Given that many legacy codes do not scale well on existing and future parallel computer architectures, OpenMC has been developed from scratch with a focus on high performance scalable algorithms as well as modern software design practices. The present work describes the methods used in the OpenMC code and demonstrates the performance and accuracy of the code on a variety of problems.

Nuclear Science & Technology↗
DOE OSTI2025

Record acceleration of the two-dimensional Ising model using a high-performance wafer-scale engine

The versatility and wide-ranging applicability of the Ising model, originally introduced to study phase transitions in magnetic materials, have made it a cornerstone in statistical physics and a valuable tool for evaluating the performance of emerging computer hardware. Here, we present a novel implementation of the two-dimensional Ising model on Cerebras Wafer-Scale Engine (WSE) – a revolutionary processor that is opening new frontiers in computing. In our deployment of the checkerboard algorithm, we optimized the Ising model to take advantage of the unique WSE architecture. Specifically, we employed a compressed bit representation storing 16 spins on each int16 word, and efficiently distributed the spins over the processing units enabling seamless weak scaling and limiting communications to only immediate neighboring units. Our implementation can handle up to 754 simulations in parallel, achieving an aggregate of over 61.8 trillion flip attempts per second for Ising models with up to 200 million spins. This represents a gain of up to 148 times over previously reported single-devices with a highly optimized implementation on NVIDIA V100 and up to 88 times in productivity compared to NVIDIA H100. Our findings highlight the significant potential of the WSE in scientific computing, particularly in the field of materials modeling.

Ising model↗
DOE OSTI2015

The dark side of photovoltaic — 3D simulation of glare assessing risk and discomfort

Photovoltaic (PV) systems form an important force in the implementation of renewable energies, but as we all know, the force has always its dark side. Besides efficiency considerations and discussions about architectures of power distribution networks, the increasing numbers of installations of PV systems for implementing renewable energies have secondary effects. PV systems can generate glare due to optical reflections and hence might be a serious concern. On the one hand, glare could affect safety, e.g. regarding traffic. On the other hand, glare is a constant source of discomfort in vicinities of PV systems. Hence, assessment of glare is decisive for the success of renewable energies near municipalities and traffic zones for the success of solar power. Several courts decided on the change of PV systems and even on their de-installation because of glare effects. Thus, location-based assessments are required to limit potential reflections and to avoid risks for public infrastructure or discomfort of residents. The question arises on how to calculate reflections accurately according to the environment's topography. Our approach is founded in a 3D-based simulation methodology to calculate and visualize reflections based on the geometry of the environment of PV systems. This computational model is implemented by an interactive tool for simulation and visualization. Hence, project planners receive flexible assistance for adjusting the parameters of solar panels amid the planning process and in particular before the installation of a PV system. - Highlights: • Solar panels cause glare that impacts neighborhoods and traffic infrastructures. • Glare might cause disability and discomfort. • 3D environment for the calculation of glare • Interactive tool to simulate and visualize reflections • Impact assessment of solar power plant farms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling and Verification of Lumped-Parameter, Multibody Structural Dynamics for Offshore Wind Turbines

This paper presents the modeling and verification of multibody structural dynamics for offshore wind turbines. The flexible tower and support structure of a monopile-based offshore wind turbine are modeled using an acausal, lumped-parameter, multibody approach that incorporates structural flexibility, soil-structure interaction, and hydrodynamic models. Simulation results are benchmarked against alternative modeling approaches, demonstrating the model's ability to accurately capture both static and dynamic behaviors under various wind and wave conditions while maintaining computational efficiency. This work provides a valuable tool for analyzing key structural characteristics of wind turbines, including eigenfrequencies, mode shapes, damping, and internal forces.

17 WIND ENERGY↗

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