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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Modeling the Resilience of Nuclear Power Plant for Unexpected Reactor Trip

Resilience can be defined as the intrinsic ability of a system to adjust to its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under both expected and unexpected conditions. Resilience engineering is a relatively new paradigm for safety management that focuses on how to cope with complexity under pressure or disturbance to achieve success. A resilient system combines inherent human abilities with engineered safety features and organizational features in a controlled and flexible manner both in expected and in unexpected situations. The concept of resilience has been suggested to complement conventional safety analyses. Conventional safety analysis methods such as PSA have several limitations: 1) they primarily focus on technical dimension, 2) the analysis are linear and sequential, 3) they are dominated by static models, 4) they do not take a systemic view into account, and 5) they focus primarily on why accidents happen and not how success is achieved. The concept of resilience provides a more integrated view for the safety analysis in safety-critical systems, e.g., nuclear power plants. The concept of resilience in the organization of NPPs has been highlighted since the Fukushima Daiichi Nuclear Power Plant accident. An IAEA report addresses that a resilient organization is one that quickly realizes deviation from normal operations and has the ability to make even the toughest and least popular decisions and to manage the margins in which it can maneuver. While traditional strategy to safety in NPPs is to identify what could go or has gone wrong, the concept of resilience is focused on what the organization does well and what it does to maintain its successful operation and to capitalize on those processes in the event of an unexpected situation. This study attempts to model the resilience of NPP dynamically, based on the operating experiences in Korean NPPs. First, this study revised the characterization of NPP. Then, a survey on the literature was conducted to identify the influences between the elements in the model of resilience in NPPs. These works provide a qualitative model for the resilience in NPPs. Then, this study reviewed 168 licensee events reports submitted to the Korean regulatory body since 2004 and quantified the relation between the attributes in the model by performing a Pearson correlation analysis. Finally, a few simulations using the System Dynamics were conducted to discuss which factors are most influencing the resilience. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Enabling the broader adoption of fusion simulation on complex geometry

This project addressed a key barrier to advanced fusion and nuclear simulation: the difficulty of performing high-fidelity Monte Carlo neutronics directly on complex, real-world CAD geometry. Traditional workflows require engineers to rebuild CAD models as simplified constructive solid geometry, a time-consuming and error-prone process that limits design iteration and broader adoption of simulation tools. The goal of this Phase I SBIR was to make CAD-based neutronics practical, accessible, and robust for industrial and research users. During the project, Coreform significantly enhanced the Direct Accelerated Geometry Monte Carlo (DAGMC) workflow and fully integrated it into Coreform Cubit as a first-class capability. Major achievements include optimized material assignment and surface meshing workflows, substantial performance improvements to geometry imprinting and preparation, native export of DAGMC models, and new visualization tools to support OpenMC source definition and lost-particle debugging. Coreform also expanded Cubit’s capabilities as a full OpenMC preprocessor, including the ability to convert OpenMC constructive solid geometry models back into CAD for visualization, multiphysics coupling, and debugging. In collaboration with Argonne National Laboratory, the project delivered comprehensive new DAGMC documentation and training materials, transforming DAGMC from a research-oriented tool into a production-ready workflow. Results were disseminated through tutorials, conference training, and multiple well-attended webinars demonstrating integrated CAD-based neutronics and multiphysics workflows. Overall, this project demonstrated that high-fidelity Monte Carlo simulations can be performed directly on complex CAD geometry, reducing setup time, improving usability, and enabling faster, more informed design decisions for fusion and nuclear energy systems.

42 ENGINEERING↗
DOE OSTI2016

A priori filtered chemical source term modeling for LES of high Karlovitz number premixed flames

Assumptions behind closure models for the filtered source term are studied a priori using results from DNS of turbulent n-heptane/air premixed flames at varying Karlovitz numbers. Simulations with both detailed chemistry and tabulated chemistry, as well as unity and non-unity Lewis numbers, are used to determine if finite-rate chemistry and differential diffusion effects affect the filtered chemical source terms. While the unfiltered source term shows large fluctuations, the filtered source terms from detailed chemistry and tabulated chemistry are in good agreement at sufficiently large filter widths (Δ ≳ l F ). Using the concept of optimal estimators, it is shown that a tabulation approach using the filtered progress variable and its variance can predict accurately the filtered chemical source terms. Finally, the filtered source terms from the DNS are compared to predictions from two commonly assumed sub-filter probability density function models. Both models show deviations from the filtered DNS source terms but predict accurately the mean turbulent flame speed. In conclusion, the results illustrate the potential of using simple tabulated chemistry approaches based on presumed PDFs for LES of premixed flames in the thin and distributed reaction zones regimes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is maximizing the supply of electricity, water, and gas to critical customers after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. Additionally, the characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to non convex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on an electricity-water-gas integrated system, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗
DOE OSTI2018

Pronghorn: A Porous Media Thermal-Hydraulics Core Simulator and its Validation with the SANA Experiments

Pebble bed High Temperature Reactors (HTRs) are characterized by many advantageous design features, such as excellent passive heat removal in accidents, large margins to fuel failure, and online refueling potential. However, a significant challenge in the core modeling of pebble bed reactors is the complex fuel-coolant structure. This paper presents a new porous media simulation code, Pronghorn, that aims to alleviate modeling challenges for pebble bed reactors by providing a fast-running, medium- fidelity core simulator. Pronghorn is intended to accelerate the design and analysis cycle for pebble bed and prismatic HTRs by permitting fast scoping studies and providing boundary conditions for systems-level analysis. Pronghorn is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) using modern software practices and a thorough testing framework. This paper describes the physical models used in Pronghorn and demonstrates Pronghorn’s capability for modeling gas-cooled pebble bed HTRs by presenting simulation results obtained for the German SANA pebble bed decay heat experiments. Within the limitations of the porous media approximation and existing available closure relationships, Pronghorn predicts the SANA experimental pebble temperatures well, expanding the code’s validation base. A brief code-to-code comparison shows a similar level of accuracy with other porous media simulation tools; this enhances Pronghorn’s advantages of an arbitrary equation of state, unstructured mesh capabilities, compressible flow models, high coupling potential to MOOSE fuels performance and systems-level thermal-hydraulics codes, and modern software design.

42 ENGINEERING↗
DOE OSTI2020

Resiliency of Degraded Built Infrastructure

Infrastructure resiliency depends on the ability of infrastructure systems to withstand, adapt, and recover from chronic and extreme stresses. In this white paper, we address the resiliency of infrastructure assets and discuss improving infrastructure stability through development of our understanding of cement and concrete degradation. The resiliency of infrastructure during extreme events relies on the condition, adaptability, and recoverability of built infrastructure (roads, bridges, dams), which serves as the backbone of existing infrastructure systems. Much of the built infrastructure in the US has consistently been rated D+ by the American Society of Civil Engineers (ASCE). Aged infrastructure introduces risk to the system, since unreliable infrastructure increases the likelihood of failures under chronic and extreme stress and are particularly concerning when extreme events occur. To understand and account for this added risk from poor infrastructure quality, more research is needed on (i) how the changing environment alters the aging of new and existing built infrastructure and (ii) how degradation causes unique failure mechanisms. The aging of built infrastructure is based on degradation of the structural materials, such as concrete and steel supports, which causes failure. Current work in cement/concrete degradation is based on (i) the development of high strength and degradation resistance concrete mixtures, (ii) methods of assessing the age and reliability of existing structures, and (3) modeling of structural stability and the microstructural evolution of concrete/cement from degradation mechanisms (sulfide attack, carbonation, decalcification). Sandia National Laboratories (SNL) has made several investments in studying the durability and degradation of cement based materials, including using SNL-developed codes and methodologies (peridynamics, PFLOTRAN) to focus on chemo-mechanical fracture of cement for energy applications. Additionally, a recent collaboration with the University of Colorado Boulder has included fracture of concrete gravity dams, scaling the existing work to applications in full sized infrastructure problems. Ultimately, SNL has the experience in degradation of cementitious materials to extend the current research portfolio and answer concerns about the resilience of aging built infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Meta-Level Design Guidance and Operator Performance Measures for Hybrid Control Rooms

The purpose of this grant was to refine and test methods to evaluate digital human system interfaces (HSI) for existing largely analog nuclear power plant (NPP) control rooms (CRs). We hypothesized that CR operator performance (CROP) in hybrid NPP CRs will be improved if future digital HSI is designed based on: 1) more robust design guidelines for operator situation awareness (SA) and decision-making (DM); 2) enhanced CROP metrics during HSI evaluation; 3) an ontology for selecting simulation scenarios to evaluate digital HSI; and 4) a model to predict optimal HSI design attributes given CROP objectives. The team conducted numerous nuclear power plant site visits (e.g., to Brown’s Ferry, Palo Verde, Sequoyah and Vogtle) to study control room operations and crisis management and 3 visits to the NRC Chattanooga Training Center. We observed research studies at DC Cook and NRC Chattanooga in collaboration with the Halden Reactor Project. We collected operator performance and workload data in one NPP simulator. A comprehensive human (i.e., CROP) performance literature review was published in Applied Ergonomics. We obtained operator team performance data from CAER to produce our data fusion model and a paper delineating the results have been accepted (revision submitted) in Resilience Engineering and System Safety. We analyzed interview data related to scenario ontology development; a manuscript is still in preparation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

MAGNET Scaling and Methodology

The purpose of this study was to analyze the heat transfer of the Microreactor Agile Non-nuclear Experimental Testbed (MAGNET) within the Dynamic Energy Transport and Integration Laboratory (DETAIL) and develop scaling equations and models to couple with other systems. Hierarchical Two-Tiered Scaling (H2TS) methodologies were applied to DETAIL’s MAGNET facility to scale and project data sets while conserving the observed behavior based on first principles. The MAGNET system was successfully scaled using H2TS and multiple system parameters were determined or calculated from experimental data including steady state and transient data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

An experimental system for high temperature X-ray diffraction studies with in situ mechanical loading

An experimental system with in situ thermomechanical loading has been developed to enable high energy synchrotron x-ray diffraction studies of crystalline materials. The system applies and maintains loads of up to 2250 N in uniaxial tension or compression at a frequency of up to 100 Hz. The furnace heats the specimen uniformly up to a maximum temperature of 1200 Degree-Sign C in a variety of atmospheres (oxidizing, inert, reducing) that, combined with in situ mechanical loading, can be used to mimic processing and operating conditions of engineering components. The loaded specimen is reoriented with respect to the incident beam of x-rays using two rotational axes to increase the number of crystal orientations interrogated. The system was used at the Cornell High Energy Synchrotron Source to conduct experiments on single crystal silicon and polycrystalline Low Solvus High Refractory nickel-based superalloy. The data from these experiments provide new insights into how stresses evolve at the crystal scale during thermomechanical loading and complement the development of high-fidelity material models.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A servo controlled gradient loading triaxial model test system for deep-buried cavern

A servo controlled gradient loading model test system is developed to simulate the gradient geostress in deep-buried cavern. This system consists of the gradient loading apparatus, the digital servo control device, and the measurement system. Among them, the gradient loading apparatus is the main component which is used for exerting load onto the model. This loading apparatus is placed inside the counterforce wall/beam and is divided to several different loading zones, with each loading zone independently controlled. This design enables the gradient loading. Hence, the “real” geostress field surrounding the deep-buried cavern can be simulated. The loading or unloading process can be controlled by the human-computer interaction machines, i.e., the digital servo control system. It realizes the automation and visualization of model loading/unloading. In addition, this digital servo could control and regulate hydraulic loading instantaneously, which stabilizes the geostress onto the model over a long term. During the loading procedure, the collision between two adjacent loading platens is also eliminated by developing a guide frame. This collision phenomenon is induced by the volume shrinkage of the model when compressed in true 3D state. In addition, several accurate measurements, including the optical and grating-based method, are adopted to monitor the small deformation of the model. Hence, the distortion of the model could be accurately measured. In order to validate the performance of this innovative model test system, a 3D geomechanical test was conducted on a simulated deep-buried underground reservoir. The result shows that the radial convergence increases rapidly with the release of the stress in the reservoir. Moreover, the deformation increases with the increase of the gas production rate. This observation is consistence with field observation in petroleum engineering. The system is therefore capable of testing deep-buried engineering structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Development of building energy asset rating using stock modelling in the USA

The US Building Energy Asset Score helps building stakeholders quickly gain insight into the efficiency of building systems (envelope, electrical and mechanical systems). A robust, easy-to-understand 10-point scoring system was developed to facilitate an unbiased comparison of similar building types across the country. The Asset Score does not rely on a database or specific building baselines to establish a rating. Rather, distributions of energy use intensity (EUI) for various building use types were constructed using Latin hypercube sampling and converted to a series of stepped linear scales to score buildings. A score is calculated based on the modelled source EUI after adjusting for climate. A web-based scoring tool, which incorporates an analytical engine and a simulation engine, was developed to standardize energy modelling and reduce implementation cost. This paper discusses the methodology used to perform several hundred thousand building simulation runs and develop the scoring scales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case

solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.

14 SOLAR ENERGY↗
DOE OSTI2021

Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case

SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2015

Center for Advanced Biofuel Systems (CABS) Final Report

One of the great challenges facing current and future generations is how to meet growing energy demands in an environmentally sustainable manner. Renewable energy sources, including wind, geothermal, solar, hydroelectric, and biofuel energy systems, are rapidly being developed as sustainable alternatives to fossil fuels. Biofuels are particularly attractive to the U.S., given its vast agricultural resources. The first generation of biofuel systems was based on fermentation of sugars to produce ethanol, typically from food crops. Subsequent generations of biofuel systems, including those included in the CABS project, will build upon the experiences learned from those early research results and will have improved production efficiencies, reduced environmental impacts and decreased reliance on food crops. Thermodynamic models predict that the next generations of biofuel systems will yield three- to five-fold more recoverable energy products. To address the technological challenges necessary to develop enhanced biofuel systems, greater understanding of the non-equilibrium processes involved in solar energy conversion and the channeling of reduced carbon into biofuel products must be developed. The objective of the proposed Center for Advanced Biofuel Systems (CABS) was to increase the thermodynamic and kinetic efficiency of select plant- and algal-based fuel production systems using rational metabolic engineering approaches grounded in modern systems biology. The overall strategy was to increase the efficiency of solar energy conversion into oils and other specialty biofuel components by channeling metabolic flux toward products using advanced catalysts and sensible design:1) employing novel protein catalysts that increase the thermodynamic and kinetic efficiencies of photosynthesis and oil biosynthesis; 2) engineering metabolic networks to enhance acetyl-CoA production and its channeling towards lipid synthesis; and 3) engineering new metabolic networks for the production of hydrocarbons required to meet commercial fuel standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

New Structural-Dynamics Module for Offshore Multimember Substructures within the Wind Turbine Computer-Aided Engineering Tool FAST: Preprint

FAST, developed by the National Renewable Energy Laboratory (NREL), is a computer-aided engineering (CAE) tool for aero-hydro-servo-elastic analysis of land-based and offshore wind turbines. This paper discusses recent upgrades made to FAST to enable loads simulations of offshore wind turbines with fixed-bottom, multimember support structures (e.g., jackets and tripods, which are commonly used in transitional-depth waters). The main theory and strategies for the implementation of the multimember substructure dynamics module (SubDyn) within the new FAST modularization framework are introduced. SubDyn relies on two main engineering schematizations: 1) a linear frame finite-element beam (LFEB) model and 2) a dynamics system reduction via Craig-Bampton's method. A jacket support structure and an offshore system consisting of a turbine atop a jacket substructure were simulated to test the SubDyn module and to preliminarily assess results against results from a commercial finite-element code.

17 WIND ENERGY↗
DOE OSTI2016

TOUGH3 v1.0

TOUGH3 V1.0 capabilities to simulate multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media, with applications geosciences and reservoir engineering and other application areas. TOUGH3 V1.0 supports a number of different combinations of fluids and components (updated equation-of-state (EOS) modules from previous versions of TOUGH, including EOS1, EOS2, EOS3, EOS4, EOS5, EOS7, EOS7R, EOS7C, EOS7CA, EOS8, EOS9, EWASG, TMVOC, ECO2N, and ECO2M). This upgrade includes (a) expanded list of updated equation-of-state (EOS) modules, (b) new hysteresis models, (c) new implementation of parallel and solver functionalities, (d) new linear solver options based on PETSc libraries, (e) new automatic build system that automatically downloads and builds third-party libraries and TOUGH3, (f) new printout in CSV format, (g) dynamic memory allocation, (h) various user features, and (i) bug fixes.

PAU, GEORGE↗
DOE OSTI2012

A Soft-Switching Inverter for High-Temperature Advanced Hybrid Electric Vehicle Traction Motor Drives

The state-of-the-art hybrid electric vehicles (HEVs) require the inverter cooling system to have a separate loop to avoid power semiconductor junction over temperatures because the engine coolant temperature of 105°C does not allow for much temperature rise in silicon devices. The proposed work is to develop an advanced soft-switching inverter that will eliminate the device switching loss and cut down the power loss so that the inverter can operate at high-temperature conditions while operating at high switching frequencies with small current ripple in low inductance based permanent magnet motors. The proposed tasks also include high-temperature packaging and thermal modeling and simulation to ensure the packaged module can operate at the desired temperature. The developed module will be integrated with the motor and vehicle controller for dynamometer and in-vehicle testing to prove its superiority. This report will describe the detailed technical design of the soft-switching inverters and their test results. The experiments were conducted both in module level for the module conduction and switching characteristics and in inverter level for its efficiency under inductive and dynamometer load conditions. The performance will be compared with the DOE original specification.

33 ADVANCED PROPULSION SYSTEMS↗