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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Model Reduction for Compressible Cavity Simulations Towards Uncertainty Quantification of Structural Loading

This report summarizes FY16 progress towards enabling uncertainty quantification for compressible cavity simulations using model order reduction (MOR). The targeted application is the quantification of the captive-carry environment for the design and qualification of nuclear weapons systems. To accurately simulate this scenario, Large Eddy Simulations (LES) require very fine meshes and long run times, which lead to week-long runs even on parallel state-of-the-art super- computers. MOR can reduce substantially the CPU-time requirement for these simulations. We describe two approaches for model order reduction for nonlinear systems, which can yield significant speed-ups when combined with hyper-reduction: the Proper Orthogonal Decomposition (POD)/Galerkin approach and the POD/Least-Squares Petrov Galerkin (LSPG) approach. The implementation of these methods within the in-house compressible flow solver SPARC is discussed. Next, a method for stabilizing and enhancing low-dimensional reduced bases that was developed as a part of this project is detailed. This approach is based on a premise termed "minimal subspace rotation", and has the advantage of yielding ROMs that are more stable and accurate for long-time compressible cavity simulations. Numerical results for some laminar cavity problems aimed at gauging the viability of the proposed model reduction methodologies are presented and discussed.

42 ENGINEERING↗
DOE OSTI2017

A Review of Permanent Magnet Stirring During Metal Solidification

Rather than using conventional electromagnetic stirring (EMS) with three-phase alternating current, permanent magnet stirring (PMS), based on the use of sintered NdFeB material which has excellent magnetic characteristics, can be employed to generate a magnetic field for the stirring of liquid metal during solidification. Recent experience with steel casting indicates that PMS requires less than 20 pct of the total energy compared with EMS. Despite the excellent magnetic density properties and low power consumption, this relatively new technology has received comparatively little attention by the metal casting community. This paper reviews simulation modeling, experimental studies, and industrial trials of PMS conducted during recent years. With the development of magnetic simulation software, the magnetic field and associated flow patterns generated by PMS have been evaluated. Based on the results obtained from laboratory experiments, the effects of PMS on metal solidification structures and typical defects such as surface pinholes and center cavities are summarized. The significance of findings obtained from trials of PMS within the metals processing sector, including the continuous casting of steel, are discussed with the aim of providing an overview of the relevant parameters that are of importance for further development and industrial application of this innovative technology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Capacitor Voltage Ripple Reduction of A 4-Level Hybrid Clamped Converter Using Switching State Redundancy for Medium-Voltage Drive

Abstract—A four-level Hybrid Clamped Converter (4LHCC) is a novel promising DC/AC multilevel converter for high-efficiency medium-voltage drives. This paper presents a new control method of the 4L-HCC using the switching state redundancy to reduce the DC-link capacitor voltage ripples at low frequencies (<=30 Hz). The new switching state selection algorithm and flying capacitor balancing method are introduced and analyzed.Both of a3.6 kV 1MW 4L-HCC simulation model and a SiC-based 4L-HCC prototype is established to verify the proposed method. Simulation and experimental result shows that the maximum DC-link capacitor ripple can be reduced effectively from over 50% to less than 5% at low frequencies with the new method. Meanwhile, load voltage and currentdistortion caused by the excessive capacitor rippleisalso mitigatedsignificantly.

hybrid clamped converter, motor drive, voltage bal↗
DOE OSTI2022

HOMP (Hybrid Operation and Maintenance Platform) [SWR-22-81]

The HOMP software module is contained within NREL's Hybrid Optimization and Performance Platform (HOPP) at this URL: https://github.com/NREL/HOPP/tree/feature/HOMP. HOMP is a python-based software module which can be used concurrently with the Hybrid Optimization and Performance Platform (HOPP) to model, simulate, and optimize degradation, reliability, and operations and maintenance of hybrid power plant components. The program currently models lithium ion battery, PEM electrolyzer, wind turbine, and solar PV array components, which enables users to understand the design and operation tradeoffs of hybrid power plants. For instance, HOMP enables users to answer questions like: how large does a battery bank need to be to achieve optimal charge/discharge rates for performance and reliability? How does plant design change for different objectives (e.g., profit versus resilience)? Under what conditions is it better to produce electricity versus hydrogen? How do we optimally control hybrid power plants to reduce downtime and increase performance?

Clark, Caitlyn↗
DOE OSTI2024

Earth System Reanalysis in Support of Climate Model Improvements

Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales. Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty. Generally, there will be advantages and complementarities of adjoint-based smoother approaches, ensemble-based filter approaches, or new ML-inspired approaches. Yet, the ever-increasing model resolution will present growing challenges arising from computational cost, calling for new ways of performing data assimilation and model optimization. Using the complementarity in a hybrid approach, blending tools and concepts from variational, ensemble and ML methods might be what is required in the future. In this context ML could be important to handle non-linear responses, and to better approximate non-Gaussian distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Parametric Thermal Models of the Transient Reactor Test Facility (TREAT)

This work supports the restart of transient testing in the United States using the Department of Energy’s Transient Reactor Test Facility at the Idaho National Laboratory. It also supports the Global Threat Reduction Initiative by reducing proliferation risk of high enriched uranium fuel. The work involves the creation of a nuclear fuel assembly model using the fuel performance code known as BISON. The model simulates the thermal behavior of a nuclear fuel assembly during steady state and transient operational modes. Additional models of the same geometry but differing material properties are created to perform parametric studies. The results show that fuel and cladding thermal conductivity have the greatest effect on fuel temperature under the steady state operational mode. Fuel density and fuel specific heat have the greatest effect for transient operational model. When considering a new fuel type it is recommended to use materials that decrease the specific heat of the fuel and the thermal conductivity of the fuel’s cladding in order to deal with higher density fuels that accompany the LEU conversion process. Data on the latest operating conditions of TREAT need to be attained in order to validate BISON’s results. BISON’s models for TREAT (material models, boundary convection models) are modest and need additional work to ensure accuracy and confidence in results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Atomic kinetics of laboratory photoionized plasmas relevant to astrophysics. Final report

The major goal of this project was to study the atomic and radiation physics of photoionized plasmas driven by a broadband x-ray flux and its impact on plasma x-ray heating and ionization, emissivity and opacity, and radiation-hydrodynamics. This problem is relevant to the physics of accretion disks surrounding black holes, x-ray binaries, and active galactic nuclei in astrophysics. In addition, it is also important for understanding non-equilibrium laboratory plasmas driven by a distribution of photons. To this end, and motivated by previous and ongoing gas-cell experiments performed by the PI at the Z facility of Sandia National Laboratories, we developed a new experimental platform at the 1MA Zebra pulsed power accelerator of the University of Nevada, Reno based on using a gas jet produced by a supersonic nozzle. The gas jet is turned into a photoionized plasma driven by the x- ray flux from a wire-array z-pinch. Establishing this new experimental platform at Zebra was a major goal of this project. In addition, we have also dedicated effort to continue complementary experiments at the Z facility using the gas-cell photoionized plasma set up with support from the Fundamental Science Program at Z as well as to perform data processing and analysis, and theory and modeling simulations, including electron kinetics and radiation-hydrodynamics. Since we seek to test and establish what physics models are needed to describe photoionized plasma guided by experimental observation, these complementary experimental efforts were central to achieving the goals of this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Volatility basis-set approach simulation of organic aerosol formation in East Asia: implications for anthropogenic-biogenic interaction and controllable amounts

Organic aerosol (OA) simulations using the volatility basis-set approach were made for East Asia and its outflow region. Model simulations were evaluated through comparisons with OA measured by aerosol mass spectrometers in and around Tokyo (at Komaba and Kisai in summer 2003 and 2004) and over the outflow region in East Asia (at Fukue and Hedo in spring 2009). The simulations with aging processes of organic vapors reasonably well reproduced mass concentrations, temporal variations, and formation efficiency of observed OA at all sites. As OA mass was severely underestimated in the simulations without the aging processes, the oxidations of organic vapors are essential for reasonable OA simulations over East Asia. By considering the aging processes, simulated OA concentrations considerably increased from 0.24 to 1.28 µg m-3 in the boundary layer over the whole of East Asia. OA formed from the interaction of anthropogenic and biogenic sources was also enhanced by the aging processes. The fraction of controllable OA was estimated to be 87 % of total OA over the whole of East Asia, showing that most of the OA in our simulations formed anthropogenically (controllable). A large portion of biogenic secondary OA (78 % of biogenic secondary OA) formed through the influence of anthropogenic sources. The high fraction of controllable OA in our simulations is likely because anthropogenic emissions are dominant over East Asia and OA formation is enhanced by anthropogenic sources and their aging processes. Both the amounts (from 0.18 to 1.12 µg m-3) and the fraction (from 75 % to 87 %) of controllable OA were increased by aging processes of organic vapors over East Asia.

Matsui, H.↗
DOE OSTI2016

Home Energy Scoring Tools (website) and Application Programming Interfaces, APIs (aka HEScore)

A web-based residential energy rating tool with APIs that runs the LBNL website: Provides customized estimates of residential energy use and energy bills based on building description information provided by the user. Energy use is estimated using engineering models developed at LBNL. Space heating and cooling use is based on the DOE-2. 1E building simulation model. Other end-users (water heating, appliances, lighting, and misc. equipment) are based on engineering models developed by LBNL.

Mills, Evan↗
DOE OSTI2022

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Modeling Interactive Effects of Manganese Bioavailability, Nitrogen Deposition, and Warming on Soil Carbon Storage

Manganese (Mn) is a redox–active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn–promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn–oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin–oxidation products as mineral–associated organic C. We also explored how Mn–driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn–dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Finally, based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.

58 GEOSCIENCES↗
DOE OSTI2015

2015 Annual Report

For more than 20 years, the Atmospheric Radiation Measurement (ARM) Climate Research Facility has blazed the trail in providing the world’s atmospheric scientists with continuous observations of cloud and aerosol properties and their impacts on Earth’s energy balance. The result is an unprecedented data set that has proved invaluable for understanding the atmosphere and improving the predictive capabilities of earth system models. Over the past year, plans have been put in place to create a powerful new capability for furthering ARM’s mission and achieving the vision outlined in the Decadal Vision, the strategy for the ARM Facility for the next 5 to 10 years. The result is a significant reconfiguration for the ARM Facility that will provide more complete data sets to support process studies and model development. The combined observational and modeling elements will enable a new level of scientific inquiry. To achieve the next-generation ARM Facility, plans underway include the following: Establishing observation “megasites” at the Southern Great Plains and North Slope of Alaska sites Enhancing ARM measurement excellence to support U.S. Department of Energy climate science research Producing routine high-resolution model simulations over domains coincident with ARM sites Developing data products and software tools that facilitate analysis and enable the evaluation of models using ARM data Strengthening interactions with the broader atmospheric science and modeling communities. Changes being implemented at the megasites will provide additional spatial sampling of atmospheric and surface information to support a new ARM capability—the routine operation of high-resolution process models at ARM sites. The result will be even more comprehensive scientific data and the processes and tools for scientists to more easily use ARM data for climate model development.

Southern Great Plains, North Slope of Alaska, larg↗
DOE OSTI2024

CaloScore v2: single-shot calorimeter shower simulation with diffusion models

Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds of function evaluations, restricting the current applicability of these models in a realistic setting. In this work, we report updates on the CaloScorearchitecture, detailing the changes in the diffusion process, which produces higher quality samples, and the use of progressive distillation, resulting in a diffusion model capable of generating new samples with a single function evaluation. Here we demonstrate these improvements using the Calorimeter Simulation Challenge 2022 dataset.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

Artificial Intelligence (cs.AI)↗
DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Modeling multidimensional and multispecies biofilms in porous media

ABSTRACT Modeling multidimensional and multispecies biofilm in porous media at the pore scale is challenging due to the need to simultaneously track the microbial community in the biofilms and the interfaces between the biofilms and the fluid. Therefore, researchers usually assume that the model has only one dimension in space or has only one microbial species. This work uses bioremediation of U(VI)‐contaminated groundwater as the context to develop a two‐dimensional and multispecies biofilm model. The model simulates the transverse mixing zone in which U(VI) is mixed with propionate, a nutrient externally supplied to stimulate the growth of microorganisms. The model considers multiple interactions among fluid flow, transport and reaction of chemical species, and growth of biofilm. The biofilm consists of two types of active biomass (syntrophs and dissimilatory metal reducing bacteria [DMBR]) and inert biomass. The two types of active biomass collaboratively remove U(VI). The model outputs biomass distribution, chemical species concentrations, and fluid flow at the pore scale to fundamentally study the multiple interactions. The model also outputs the contaminant removal rate that can be potentially used for up‐scaling studies. The simulated results are generally consistent with experimental observations from other studies in trend. The trend can be explained by the multiple interactions based on thermodynamics and microbial kinetics. Biotechnol. Bioeng. 2017;114: 1679–1687. © 2017 Wiley Periodicals, Inc.

Tang, Youneng↗