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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Griffin Software Development Plan

Griffin is a MOOSE-based reactor physics application for advanced reactor multiphysics modeling and simulation. The application is developed in a consistent multiphysics environment with strong software quality assurance. Griffin inherited most of the capabilities of MAMMOTH/Rattlesnake and is adopting the capabilities from PROTEUS that are needed in the code. The toolset includes a variety of deterministic radiation transport solvers for fixed source, k-eigenvalue, ad-joint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code contains the cross-section preparation capabilities applicable to fast and thermal reactors, including TRISO-fueled reactors. Core management capabilities include core performance, fuel depletion and shuffling, equilibrium core calculation, pebble-bed reactor run-in and equilibrium core, molten-salt reactor delayed neutron precursor drift, and control rod and drum movement with cusping correction. This software development plan presents the current and future capabilities and features in Griffin for the design and analysis of non-light-water reactor systems in steady-state and transient conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

H420 Imager Calibration Procedure: Field of View Scan

Gamma-ray imagers with coded apertures have a finite field of view (FOV) within which an image of a source can be generated. A “FOV scan” is a facet of imager calibration procedure that involves collecting specialized data for a range of source locations filling the FOV in order to understand and correct for differences in imager performance. Systematic distortions reveal relative displacements between internal imager components, which can be accounted for in data analysis. The success of this scan requires a stable imager position during the full measurement duration (~hours). This document summarizes the hardware and software tools required to conduct a FOV calibration scan of an H3D H420 Coded Aperture Gamma-Ray Imager.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

PixelStorm: A Remote Display for Remote Sensing Ground Stations

PixelStorm is a software application for displaying native high-performance applications from remote cloud environments. It is tailored for remote sensing missions that require high framerates, high resolutions, and minimal loss of quality. PixelStorm utilizes hardware-accelerated video compression on graphics processing units and a Sandia-developed streaming network protocol. Using our architecture, we can demonstrate interactive native applications running across two 4K monitors at 60 frames per second while maintaining the visual fidelity required by our missions. This technology allows for the migration of mission critical desktop applications to cloud environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Uncertainty Analysis and Software Verification

Uncertainty analyses are an important part of calibrations and testing. They allow researchers insight on how to reduce and mitigate errors in testing. Each device used in testing introduces error in a system, as well as other sources such as environmental conditions, electronics, analog to digital, and random errors. Each source is carefully examined to identify how much error it introduces to a system. These sources are then combined using various methods of uncertainty calculations. To verify and validate software, a manual calculation is required to ensure the software is performing as intended. Using Excel to verify the calculations, we can identify discrepancies within the software. The root of the sum of the squares uncertainty (RSS) is used to find the combined uncertainty of a device at one and two standard deviations of the mean. Calibrations on accelerometers are performed using a vibration system along with a back-toback reference accelerometer. The vibration system takes a reference point at 100Hz frequency at 10g amplitude. The sensitivities are collected at each dialed in frequency. The sensitivity of the device represents the electrical output of the UUT (mV, pC, etc.) per unit of acceleration (g). The full history of sensitivities of selected accelerometers are used to find the averaged, standard deviation, and uncertainty of the device at each frequency tested. The uncertainty calculations from excel and the software are then compared.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

The integration of Non-Energy Benefits (NEBs) into energy efficiency initiatives is essential for operational excellence in manufacturing. This presentation and software demonstration explore how quantifying NEBs such as improved safety, increased quality, and enhanced productivity, can strengthen business cases for energy investments, leading to better payback periods and alignment with organizational goals. We introduce JUSTIFI, a free, open-source software by the U.S. Department of Energy that aids in the measurement of NEBs and enhances understanding of their impact on Key Performance Indicators (KPIs) and return on investment (ROI). JUSTIFI features an intuitive interface for identifying NEBs, customizable reporting tools, and comprehensive system cataloging, empowering companies to effectively communicate the value of energy efficiency projects. By leveraging this innovative tool, organizations can better navigate energy efficiency assessments and drive support for their energy management initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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 OSTI2023

Encoding integers and rationals on neuromorphic computers using virtual neuron

Abstract Neuromorphic computers emulate the human brain while being extremely power efficient for computing tasks. In fact, they are poised to be critical for energy-efficient computing in the future. Neuromorphic computers are primarily used in spiking neural network–based machine learning applications. However, they are known to be Turing-complete, and in theory can perform all general-purpose computation. One of the biggest bottlenecks in realizing general-purpose computations on neuromorphic computers today is the inability to efficiently encode data on the neuromorphic computers. To fully realize the potential of neuromorphic computers for energy-efficient general-purpose computing, efficient mechanisms must be devised for encoding numbers. Current encoding mechanisms (e.g., binning, rate-based encoding, and time-based encoding) have limited applicability and are not suited for general-purpose computation. In this paper, we present the virtual neuron abstraction as a mechanism for encoding and adding integers and rational numbers by using spiking neural network primitives. We evaluate the performance of the virtual neuron on physical and simulated neuromorphic hardware. We estimate that the virtual neuron could perform an addition operation using just 23 nJ of energy on average with a mixed-signal, memristor-based neuromorphic processor. We also demonstrate the utility of the virtual neuron by using it in some of the μ -recursive functions, which are the building blocks of general-purpose computation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

SIDIS-RC EvGen: A Monte-Carlo event generator of semi-inclusive deep inelastic scattering with the lowest-order QED radiative corrections

SIDIS-RC EvGen is a C++ standalone Monte-Carlo event generator for studies of semi-inclusive deep inelastic scattering (SIDIS) processes at medium to high lepton beam energies. In particular, the generator contains binary and library components for generating SIDIS events and calculating cross sections for unpolarized or longitudinally polarized beam and unpolarized, longitudinally or transversely polarized target. The structure of the generator incorporates transverse momentum-dependent parton distribution and fragmentation functions, whereby we obtain multi-dimensional binned simulation results, which will facilitate the extraction of important information about the three-dimensional nucleon structure from SIDIS measurements. In order to build this software, we have used recent elaborate QED calculations of the lowest-order radiative effects, applied to the leading order Born cross section in SIDIS. Here, in this paper, we provide details on the theoretical formalism as well as the construction and operation of SIDIS-RC EvGen, e.g., how we handle the event generation process and perform multi-dimensional integration. We also provide example programs, flowcharts, and numerical results on azimuthal transverse single-spin asymmetries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cyber-Attack Detection and Accommodation for the Energy Delivery System

The goals of this project were to create a software system with a suite of key algorithms for cyber-attack detection and accommodation providing domain layer protection for critical power generation assets. Example assets included gas and steam turbines, heat recovery steam generators, and electrical generators. The aggressive algorithm goals were aimed at reducing the false positive rates in threat detection to <1% using learnings from many evolving disciplines (power turbine and generator physics, power system modeling, modern control theory, system identification, machine learning, deep learning, mathematics and data science). Additional goals for the algorithms involved localizing threats on-the-fly to know in which monitoring node the effects of attacks are present, and then providing accommodation to keep the system running uninterrupted much of the time in the presence of the attack. Accommodation had a performance goal of providing resiliency when up to 50% of monitoring nodes are in an attack state.

cybersecurity, cyber-physical↗
DOE OSTI2023

Software Defined Architectures for Portability and Performance

The Software Defined Architectures for Portability and Performance (SODAPOP) project developed a co-design framework to partition and map converged applications on specialized heterogeneous architectures. We started from key domain applications that combine scientific simulation with data analytics and machine learning as drivers to integrate our framework. The framework includes high-level compilers that interfaces with high-level programming frameworks, domain-specific optimization passes, and hardware-oriented optimizations. The framework leverages hardware generators to enable specialization and facilitate exploration of custom system designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimal experimental design using eigenvalue-based criteria with Pyomo.DoE

New developments in automated optimal experimental design within the PSE+ software ecosystem. Advancements in user experience (to reduce the time taken to perform optimal experiment design) and computational capabilities (allowing more diverse experimental design) are shown with an example relevant to critical minerals and materials. Also, a small tutorial on science-based optimal experimental design and novel contributions therein are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology for pin lattice models is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. The user can alternatively provide their own geometry and power profile instead of inheriting it from DIF3D. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and a sufficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Machine Learning Software for Cylindrical Battery Design and Performance Prediction

A software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from micro batteries to EV batteries, is developed. The Cylindrical battery design V1.0 is comprised of three types of cylindrical batteries, Micro battery (Primary), Micro battery (Secondary) and 18650/21700/xxxxx cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping to accelerate energy storage research, development, and manufacturing.

25 ENERGY STORAGE↗
DOE OSTI2022

PyOECP: A flexible open-source software library for estimating and modeling the complex permittivity based on the open-ended coaxial probe (OECP) technique

Here, we present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on three different methods. The software library contains the dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) in the field of science and engineering are required only so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov Chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, electrode polarization, a typical measurement artifact for interpreting dielectric spectra, can be incorporated into the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem), is also included. This open-source software enables users to freely adjust the physical parameters to obtain physical insight into their materials under test and will be consistently updated for more accurate measurement and interpretation of dielectric spectra in an automated manner. This work describes the theoretical and mathematical background of the software, lays out the workflow, and validates the software functionality based on both synthetic and empirical data included in the software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Poisson equation method for prescribing fully developed non-Newtonian inlet conditions for computational fluid dynamics simulations in models of arbitrary cross-section

Prescribing inlet boundary conditions for computational fluid dynamics (CFD) simulations of internal flow in complex geometries such as anatomical vascular models is challenging. In the absence of patient-specific inlet velocity data, a common approach for long blood vessels is to assume that the inlet flow is fully developed. In vessels of irregular cross section, however, prescribing fully developed conditions is complicated due to the lack of a general closed-form analytical solution. In this study, we develop a simple Poisson equation method for prescribing fully developed inlet conditions for the flow of either Newtonian or non-Newtonian fluids in CFD models of arbitrary cross-section. We first derive the generalized Poisson equation for fully developed flow of a non-Newtonian fluid and we then develop and verify a methodology for numerically computing the solution on any planar boundary domain. In addition, we develop a simple extension of the method for prescribing a non-orthogonal inlet velocity that represents fully developed flow from an upstream tube that is connected to the CFD inlet at a non-orthogonal angle. This may be used to investigate a common source of uncertainty in CFD simulations of internal flow that is due to a lack of information concerning the exact streamwise flow direction at the inlets. Comparison to several Newtonian and non-Newtonian benchmark verification solutions shows the method to be extremely accurate. As a practical demonstration case, we use the method to prescribe fully developed conditions on multiple non-circular inlets for the non-Newtonian flow of blood in a patient-specific model of the inferior vena cava (IVC). Finally, we further demonstrate the utility of the method by performing a sensitivity study using the patient-specific IVC model, wherein we investigate the influence of inlet velocity flow direction on the non-Newtonian IVC hemodynamics. Given its simplicity and computational efficiency, the method is shown to be far superior to alternative approaches for prescribing fully developed inlet conditions in such complicated geometries. In conclusion, to facilitate the adoption of our Poisson equation method, we have distributed our OpenFOAM source code and the associated test cases from this study as open-source software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Image processing tools for petabyte-scale light sheet microscopy data

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Assessing DER Network Cybersecurity Defences in a Power-Communication Co-Simulation Environment

Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface. Maloperation or malicious control of DER equipment can now cause substantial disturbances to grid operations. Fortunately, many options exist to defend and limit adversary impact on these newly-created DER communication networks, which typically traverse the public internet. However, implementing these security features will increase communication latency, thereby adversely impacting real-time DER grid support service effectiveness. In this work, a collection of software tools called SCEPTRE were used to create a co-simulation environment where SunSpec-compliant PV inverters were deployed as virtual machines and interconnected to simulated communication network equipment. Network segmentation, encryption, and moving target defence security features were deployed on the control network to evaluate their influence on cybersecurity metrics and power system performance. The results indicated that adding these security features did not impact DER-based grid control systems but improved the cybersecurity posture of the network when implemented appropriately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Next-Generation Marine Energy Software Needs Assessment

The U.S. Department of Energy (DOE) Water Power Technologies Office’s (WPTO) initial investment in marine energy software was driven by needs identified over a decade ago. WPTO-funded research was first launched because of a U.S. congressional mandate that called for the DOE to officially research marine energy technologies, which also established the DOE WPTO in 2008. A congressional mandate requested the WPTO to evaluate a variety of marine energy devices, establish baseline levelized cost of energy estimates, and provide an overall report to Congress. This congressional mandate led to the Reference Model Project (RMP), for which WPTO funded a national multi-laboratory team to develop these reference models, based on state-of-the-art designs of six marine energy converter archetypes that consisted of three current energy converters and three wave energy converters (WEC). Each device was designed to operate for a specific marine resource, thus allowing the devices to serve as reference models for future studies. The RMP congressional report cited the need for improved marine energy software to handle a variety of device designs, as well as a need to standardize performance outputs. Without validated software packages and established metrics, information presented to the WPTO by technology developers could be incorrect or inaccurate and result in misleading conclusions. The recommendation to coordinate WPTO investment in software for numerical modeling and analysis was given a high priority because it would directly fill needs at the time, and focused funding would amplify impact. By sponsoring software development, WPTO would provide industry developers, university researchers, and national laboratories software that could be used, customized, and advanced, thus supporting the overall advancement of marine energy.

16 TIDAL AND WAVE POWER↗