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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Feynman path integrals for discrete-variable systems: Walks on Hamiltonian graphs

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is the Hamiltonian. By working out expressions for the partition function and transition amplitudes of discretized versions of continuous-variable quantum systems, and then taking the continuum limit, we explicitly recover Feynman's continuous-variable path integrals. We also discuss the implications of our result.

Feynman diagrams↗
DOE OSTI2024

UNIFI Specifications for Grid-Forming Inverter-Based Resources (V. 2)

The UNiversal Interoperability for grid-Forming Inverters (UNIFI) Consortium is addressing fundamental challenges facing the integration of grid-forming (GFM) inverters in electric grids alongside rotating machines and other inverter-based resources (IBRs). This document defines a set of UNIFI Specifications for GFM IBRs that provides requirements from both a power system-level as well as functional requirements at the inverter level that are intended to provide means for vendor-agnostic operation of GFM IBRs at any scale in electric power systems. The specifications are clearly identified and attributed to an IBR plant or an IBR unit throughout the document, where applicable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2023

Compliant heat exchangers, heat pipes and methods for making same

A method for fabricating heat exchangers using additive manufacturing technologies. Additive manufacturing enables the manufacture of heat exchangers with complex geometries and/or with internal and external integral surface features. Additive manufacture also facilitates the manufacture of heat exchangers with regional variations, such as changes in size, shape and surface features. In one embodiment, the present invention provides a heat exchanger with a helicoidal shape that provides axial elastic compliance. In one embodiment, the internal channel of the heat exchanger varies along its length. The internal channel may have a cross-sectional area that increases progressively from one end to the other. In one embodiment, the external shape of the tubular structure may be non-circular to optimize heat transfer with an external heat transfer fluid. In one embodiment, the present invention provides a heat pipe with an internal wicking structure formed as an integral part of the additive manufacturing process.

Lara-Curzio, Edgar↗
DOE OSTI2024

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods, are disclosed. A representative method for forming a nuclear-powered steam generator includes forming an instrumented support, the instrumented support including a carrier portion and a retainer portion, with at least one of the carrier portion or the retainer portion being integrally formed with a sensor via an additive manufacturing process. The method can further include coupling the sensor to a communication link, supporting a helical steam conduit on the instrumented support, and installing the helical steam conduit and the instrumented support in a nuclear reactor. The helical steam conduit is positioned along a primary flow path, which is in turn positioned to circulate a heated primary flow in thermal communication with the helical steam conduit.

Welter, Kent↗
DOE OSTI2021

leapR: An R Package for Multiomic Pathway Analysis

A generalized goal of many high-throughput data studies is to identify functional mecha-nisms that underlie observed biological phenomena, whether disease outcomes or metabolic out-put. Increasingly, studies that rely on multiple sources of high-throughput data (genomic, tran-scriptomic, proteomic, metabolomic) are faced with a challenge of utilizing the data in a way that maximizes utility. However, methods for integration of multiple forms of molecular data into a biolog-ically coherent frameworks are needed. Furthermore, we have developed a framework to assess biological pathway activity that relates to phenotypic outcome using multi-source data. Availability and implementation: The leapR package with user manual and example workflow is available for download from GitHub (https://github.com/biodataganache/leapR).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structural Impact of Grid-Forming Inverters on Power System Coherency

This paper addresses the following fundamental research question: how does the integration of grid-forming inverters (GFMs) replacing conventional synchronous generators (SGs) impact the slow coherent eigen-structure and the low frequency oscillatory behavior of future power systems? Due to time-scale separated dynamics, generator states inside a coherent area synchronize over a fast time-scale due to stronger coupling, while the areas themselves synchronize over a slower time scale. Our mathematical analysis shows that due to the large-scale integration of GFMs, the weighted Laplacian structure of the frequency dynamics is preserved, however, the entries of the Laplacian may be significantly modified based on the location and penetration levels of the GFMs. This can impact and potentially significantly alter the coherency structure of the system. We have validated our findings with numerical results using the IEEE 68-bus test system.

Mukherjee, Sayak [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2022

Adaptive experimental design for multi-fidelity surrogate modeling of multi-disciplinary systems

We present an adaptive algorithm for constructing surrogate models of multi-disciplinary systems composed of a set of coupled components. With this goal we introduce “coupling” variables with a priori unknown distributions that allow surrogates of each component to be built independently. Once built, the surrogates of the components are combined to form an integrated-surrogate that can be used to predict system-level quantities of interest at a fraction of the cost of the original model. The error in the integrated-surrogate is greedily minimized using an experimental design procedure that allocates the amount of training data, used to construct each component-surrogate, based on the contribution of those surrogates to the error of the integrated-surrogate. Here, the multi-fidelity procedure presented is a generalization of multi-index stochastic collocation that can leverage ensembles of models of varying cost and accuracy, for one or more components, to reduce the computational cost of constructing the integrated-surrogate. Extensive numerical results demonstrate that, for a fixed computational budget, our algorithm is able to produce surrogates that are orders of magnitude more accurate than methods that treat the integrated system as a black-box.

42 ENGINEERING↗
DOE OSTI2023

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Non-local model for surface tension in fluid-fluid simulations

We propose a non-local model for surface tension obtained in the form of an integral of a molecular-force-like function with support 3.5e added to the Navier-Stokes momentum conservation equation. We demonstrate analytically and numerically that with the non-local model interfaces with a radius of curvature larger than the support length behave macroscopically and microscopically, otherwise. For static droplets, the pressure difference Pe,in - Pe,out satisfies the Young-Laplace law for droplet radius greater than 3.5e and other- wise deviates from the Young-Laplace law. The latter indicates that the surface tension in the proposed model decreases with decreasing radius of curvature, which agrees with molecular dynamics and experimental studies of nanodroplets. Using the non-local model we perform numerical simulations of droplets under dynamic conditions, including a rising droplet, a droplet in shear flow, and two colliding droplets in shear flow, and compare results with a standard Navier-Stokes model subject to the Young-Laplace boundary condition at the fluid-fluid interface implemented via the Conservative Level Set (CLS) method. We find good agreement with existing numerical methods and analytical results for a rising macroscopic droplet and a droplet in a shear flow. For colliding droplets in shear flow, the non- local model converges (with respect to the grid size) to the correct behavior, including sliding, coalescence, and merging and breaking of two droplets depending on the capillary number. In contrast, we find that the results of the CLS model are highly grid-size dependent.

Howard, Amanda A.↗
DOE OSTI2024

The Use of High-Density UN Fuel in Heat-Pipe Microreactors

Heat-pipe microreactors (HPMRs) are very small-scale nuclear reactors that employ heat pipes (HPs) for heat removal. HPMRs can be easily integrated with other forms of renewable energies, can be used for emergency responses to disaster relief zones, can be deployed in remote locations not connected to the grid, and can be removed from sites and replaced by new ones. HPMRs can also be used for space missions as HPs do not rely on gravity for heat transfer. Conventional fuel materials, such as uranium oxide (UO 2 ) and uranium oxycarbide (UCO), are currently considered in most existing HPMR designs, but ceramic uranium nitride (UN) fuel that has high uranium density, high thermal conductivity, and high melting point may become a better fuel candidate. Through neutronics calculations, this paper assesses the impact of using UN fuel in HPMRs with two different neutron spectra (fast and thermal) and two different fuel forms [traditional solid fuel pellets and TRi-structural-ISOtropic (TRISO) fuel compacts]. It was concluded that retrofitting HPMRs with UN fuel has the potential to reduce the initial 235 U enrichment requirement by ~3 wt% (to keep the same cycle length) or increase the cycle length (by keeping the same initial 235 U enrichment), which enables more compact and transportable HPMR core designs. However, using UN fuel decreases the control element worth [by up to 20% for the Special Purpose Reactor (SPR) and 5% for HP-MR] and is up to 80% more costly. Increasing 15 N enrichment can further decrease the initial 235 U enrichment requirement and increase the control element worth but is more costly. In conclusion, compared to fast-spectrum HPMRs fueled with solid pellet fuels, retrofitting UN fuel is more suitable for thermal-spectrum HPMRs fueled with TRISO fuel compacts, where the neutron spectrum hardening caused by using UN is less significant.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Domain-decomposition nonlinear manifold reduced order model

This software combines nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD) techniques. NM-ROMs, which utilize a shallow, sparse autoencoder trained with full order model (FOM) snapshot data, approximate the FOM state on a nonlinear manifold. These models offer advantages over linear-subspace ROMs (LS-ROMs) particularly in scenarios with slowly decaying Kolmogorov n-width. However, the training of NM-ROMs involves a number of parameters that scale with the size of the FOM, and storing high-dimensional FOM snapshots can significantly increase the cost of ROM training for extreme-scale problems. To mitigate these costs, the software employs DD to partition the FOM into smaller subdomains, computes NM-ROMs for each, and then integrates these to form a global NM-ROM. This strategy offers multiple benefits: it enables parallel training of subdomain NM-ROMs, reduces the number of parameters needed, decreases the dimensional requirements of subdomain FOM training data, and allows for customization to the unique characteristics of each FOM subdomain. The use of a shallow, sparse autoencoder architecture in each subdomain NM-ROM facilitates the application of hyper-reduction (HR), simplifying the nonlinear complexities and enhancing computational speed. This software marks the inaugural application of NM-ROM combined with HR to a DD problem. It features an algebraic DD reformulation of the FOM, training of NM-ROMs with HR for each subdomain, and employs a sequential quadratic programming (SQP) solver for the evaluation of the coupled global NMROM. The effectiveness of the DD NM-ROM with HR is numerically demonstrated on the 2D steady-state Burgers' equation, showing an order of magnitude improvement in accuracy over the DD LS-ROM with HR.

Diaz, AlejandroN↗
DOE OSTI2025

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗
DOE OSTI2021

Full Vorticity Budget of the Arabian Sea from a 0.1° Ocean Model: Sverdrup Dynamics, Rossby Waves, and Nonlinear Eddy Effects

Abstract The Arabian Sea, influenced by the Indian monsoon, has many unique features, including its basin-scale seasonally reversing surface circulation and the Great Whirl, a seasonal anticyclonic system appearing during the southwest monsoon close to the western boundary. To establish a comprehensive dynamical picture of the Arabian Sea, we utilize numerical model output and design a full vorticity budget that includes a fully decomposed nonlinear term. The ocean general circulation model has 0.1° resolution and is mesoscale eddy-resolving in the region. In the western boundary current system, we highlight the role of nonlinear eddies in the life cycle of the Great Whirl. The nonlinear eddy term is of leading-order importance in this feature’s vorticity balance. Specifically, it contributes to the Great Whirl’s persistence in boreal fall after the weakening of the southwesterly winds. In the open ocean, Sverdrup dynamics and annual Rossby waves are found to dominate the vorticity balance; the latter is considered as a key factor in the formation of the Great Whirl and the seasonal reversal of the western boundary current. In addition, we discuss different forms of vertically integrated vorticity equations in the model and argue that the bottom pressure torque term can be interpreted analogously as friction in the western boundary and vortex stretching in the open ocean.

58 GEOSCIENCES↗
DOE OSTI2021

Impact Mapping for Geospatial Reasoning and Decision Making

Objective The reported study evaluated a novel approach to aiding geospatial reasoning and decision making. Background Impact mapping aims to alleviate the cognitive demands of geospatial tasks in part by externalizing data in the form of an integrated decision surface. This is achieved by aggregating data across multiple sources of information and visualizing their combined utility rather than objective measurements or individual utility. Previous research has shown that geospatial decisions improve when aided in this manner, but it remains unknown if dynamic decision making, often plagued by fatigue and anchoring bias, would benefit similarly. Method The experiment implemented a systematic manipulation of the presence of a composite impact map and the number of attributes present in a two-stage disaster relief, resource allocation task to investigate when and how impact mapping is beneficial or deleterious to decision makers. Results The presence of the composite impact map increased the utility of selected sites, increased re-planning decisions, reduced information display views, and reduced workload. Generally, the effect of the composite impact map was greater when participants were asked to evaluate more attributes. Conclusion Composite impact maps appear to improve repeated geospatial reasoning and minimize anchoring bias because they alleviate the cognitive demands otherwise necessary to interpret and maintain information from multiple attributes. Application Data visualization techniques, such as impact mapping, can improve repeated geospatial decision making in environments that include high cognitive demand.

Illingworth, David A.↗
DOE OSTI2025

SDA: a symbolic differential algebra package in C++

Truncated Power Series Algebra (TPSA), or Differential Algebra (DA), is a well-established tool in accelerator physics, commonly used for generating high-order maps of dynamic systems, as well as in symplectic tracking, normal form analysis, verified integration, optimization, and fast multipole methods. This package is the first to perform symbolic DA computations, enabling traceability of initial condition contributions and runtime reduction for repeated DA calculations, potentially expanding DA’s applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

MARVEL Fuel Fabrication Strategy

The purpose of this document is to document the strategy to fabricate nuclear fuel for the Microreactor Applications Research Validation and Evaluation (MARVEL) Reactor. The fabrication method and location, fuel and material forms for transport, integration with programs and facilities, and a high level, integrated schedule are included.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

The Use of the High-density UN Fuel in Heat-pipe Microreactors

Heat-pipe microreactors (HPMRs) are very small-scale nuclear reactors that employ heat pipes for heat removal. HPMRs can be easily integrated with other forms of renewable energies, used for emergency responses to disaster relief zones, deployed in remote locations not connected to the grid, and removed from sites and replaced by new ones. HPMRs can also be used for space missions as heat pipes do not rely on gravity for heat transfer. Conventional fuel materials, such as UO 2 and UCO, are currently considered in most existing HPMR designs, but ceramic UN fuel that has high uranium density, high thermal conductivity, and a high melting point may become a better fuel candidate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗