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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 109 records · Page 6

Validation of NSFsim as a Grad-Shafranov equilibrium solver at DIII-D

Plasma shape is a significant factor that must be considered for any Fusion Pilot Plant (FPP) as it has significant consequences for plasma stability and core confinement. A new simulator, NSFsim, has been developed based on a historically successful code, DINA [1], offering tools to simulate both transport and plasma shape. Specifically, NSFsim is a free boundary equilibrium and transport solver and has been configured to match the properties of the DIII-D tokamak. This paper is focused on validating the Grad-Shafranov (GS) solver of NSFsim by analyzing its ability to recreate the plasma shape, the poloidal flux distribution, and the measurements of the simulated diagnostic signals originating from flux loops and magnetic probes in DIII-D. Five different plasma shapes are simulated to show the robustness of NSFsim to different plasma conditions; these shapes are Lower Single Null (LSN), Upper Single Null (USN), Double Null (DN), Inner Wall Limited (IWL), and Negative Triangularity (NT). The NSFsim results are compared against real measured signals, magnetic profile fits from EFIT [2], and another plasma equilibrium simulator, GSevolve [3]. EFIT reconstructions of shots are readily available at DIII-D, but GSevolve was manually ran by us to provide simulation data to compare against.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An E and B gyrokinetic simulation model for kinetic Alfvén waves in tokamak plasmas

The gyrokinetic particle simulation is a powerful tool for studies of transport, nonlinear phenomenon, and energetic particle physics in tokamak plasmas. While most gyrokinetic simulations make use of the scalar and vector potentials, a new model (GK-E&B) has been developed by using the E and B field in a general form and has been implemented in simulating kinetic Alfvén waves in uniform plasma. In our work, the Chen et al. GK-E&B model has been expressed, in general, tokamak geometry using the local orthogonal coordinates and general tokamak coordinates. Its reduction for uniform plasma is verified, and the numerical results show good agreement with the original work. The theoretical dispersion relation and numerical results in the local model in screw pinch geometry are also in excellent agreement. Numerical results show excellent performance in a realistic parameter regime of burning plasmas with high values of β/(M e k$^{2}_{⊥}$ρ$^{2}_{i}$), which is a challenge for traditional methods due to the “cancellation” problem. As one application, the GK-E&B model is implemented with kinetic electrons in the local single flux surface limit. With the matched International Tokamak Physics Activity-Toroidicity-induced Alfvén Eigenmodes parameters adopted, numerical results show the capability of the GK-E&B in treating the parallel electron Landau damping for realistic tokamak plasma parameters. As another application, the global GK-E&B model has been implemented with the dominant electron contribution in the cold electron limit. Its capability in simulating the finite E || due to the finite electron mass is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle Sensitivity Analysis

We propose to develop a computational sensitivity analysis capability for Monte Carlo sampling-based particle simulation relevant to Aleph, Cheetah-MC, Empire, Emphasis, ITS, SPARTA, and LAMMPS codes. These software tools model plasmas, radiation transport, low-density fluids, and molecular motion. Our report demonstrates how adjoint optimization methods can be combined with Monte Carlo sampling-based adjoint particle simulation. Our goal is to develop a sensitivity analysis to drive robust design-based optimization for Monte Carlo sampling-based particle simulation - a currently unavailable capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental Steps toward a Density Law for Chlorine-Crediting Criticality Models of Aqueous Plutonium solutions

Criticality accident prevention is an essential safety consideration for all operations involving fissionable and fissile materials. Predictive criticality calculations using advanced neutron transport codes, such as Monte Carlo N-Particle Transport (MCNP), are invaluable tools for designing and implementing operational limits. While indispensable, these tools are limited by the quality and accuracy of the inputs that the user provides to define the modeled system. Parameters such as atomic composition, shape, and material density must be accurately defined to obtain a meaningful result. In the case of material property details for a plutonium model, accurate material characterization data is sometimes sparse. Thus limitations in calculation accuracy can be reduced by improving our knowledge of material properties in the targeted fissile systems. One of the biggest remaining challenges to accurately defining fissile systems is the description of aqueous fissile solutions. Even simple properties, such as density, are not well-known for fissile solutions relevant to nuclear energy and security. Described here are initial efforts undertaken to improve criticality calculation inputs for fissile plutonium chloride solutions in water. This effort is focused on experimentally determining accurate solution characteristics for ternary plutonium chloride/hydrochloric acid/water systems, by measurement of water activity and solution density. The effect of inputting experimental densities for these solutions into MCNP criticality calculations is compared to the traditional approach of modeling an idealized (and fictitious) plutonium-water mixture. Expansion of these efforts to a working density law for aqueous plutonium chloride solutions is also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Marine Alternative Fuel Pricing, Supply, and Demand

The International Maritime Organization low sulfur fuel rules and greenhouse gas-reduction strategy may create a significant perturbation to global refinery operations, impacting volumes and prices of marine fuel globally and within the United States and incentivizing the transition to alternative fuel use. The goals of this project are to (1) enhance understanding of how very low-sulfur fuel-primarily fuel oil and diesel-and low carbon fuel requirements and promising biofuel processes will affect the marine fuel supply chain; and (2) explore how these perturbations interact with and impact indicators such as pricing, number of trips, and demand behavior, along with the potential to meet low sulfur and carbon fuel demand with biofuel supply chains, (3) merge innovative thinking in the area of marine fuels within research centers of DOE (NREL) and the U.S. Department of Transportation (Volpe). These goals will be accomplished through the combination of detailed refinery, marine fuel burn, system dynamics, and geospatially explicit linear programming models.

biofuel↗

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO 2 v7.3

We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO 2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO 2 transport processes within the MPAS-CO 2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO 2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO 2 observations to surface CO 2 fluxes and the initial atmospheric CO 2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO 2 observations, namely the tower-based in situ CO 2 mixing ratio and satellite-derived column-averaged CO 2 mixing ratio (X CO 2 ). A comparison between the sensitivity to surface flux calculated by the MPAS-CO 2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for X CO 2 , might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO 2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO 2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO 2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO 2 TL and adjoint models, and their integration into the MPAS-CO 2 system, establish the possibility of using MPAS's unique features in atmospheric CO 2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

54 ENVIRONMENTAL SCIENCES↗

Developing capacitated p-median location-allocation model in the spopt library to allow UCL student teacher placements using public transport

Location-allocation is a key tool within the GIS and network analysis toolbox. In this paper we discuss the real world application of a location-allocation case study (approx 800 students, 500 schools) from UCL using public transport. The use of public transportation is key for this case study, as many location-allocation approaches only make use of drive-time or walking-time distances, but the location of UCL in Greater London, UK makes the inclusion of public transport vital for this case study. The location-allocation is implemented as a capacitated p-median location-allocation model, using the spopt library, part of the Python Spatial Analysis Library (PySAL). The capacitated variation of the p-median location-allocation problem is a new addition to the spopt library, which this work will present. The results from the initial version of the capacitated p-median location-allocation problem has shown a marked improvement on public transport travel time, with public transport travel time reduced by 891 minutes overall for an initial sample of 93 students (9.58 minutes per student). Results will be presented below and plans for further improvement shared.

Bearman, Nick↗

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction

Here, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements. Toward emerging applications of digital twins in aviation, the proposed approach allows for constructing a realtime predictive tool for wake-vortex transport and decay systems. We build on the fact that in realistic application, there are uncertainties in initial and boundary conditions, model parameters, as well as measurements. Moreover, conventional nonlinear ROMs based on Galerkin projection (GROMs) suffer from imperfection and solution instabilities, especially for advection-dominated flows with slow decay in the Kolmogorov n-width. In the presented LSTM nudging (LSTM-N) approach, we fuse forecasts from a combination of imperfect GROM and uncertain state estimates, with sparse Eulerian sensor measurements to provide more reliable predictions in a dynamical data assimilation framework. We illustrate our concept by solving the two-dimensional vorticity transport equation. We investigate the effects of measurements noise and state estimate uncertainty on the performance of the LSTM-N behavior. We also demonstrate that it can sufficiently handle different levels of temporal and spatial measurement sparsity, and offer a huge potential in developing next-generation digital twin technologies for aerospace applications.

42 ENGINEERING↗

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools Case Studies of Benchmarks and Applications

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Oregon Rivers Characterization Tool

DHS’s Regional Resiliency Assessment Program (RRAP) undertook the Oregon State Transportation Systems RRAP project between 2018-2021 to assess the seismic vulnerabilities of the state’s transportation system to a Cascadia Subduction Zone (CSZ) earthquake (CISA 2021). The project primarily focused on the effects of a CSZ earthquake on the mobility of emergency response efforts into the region. In the event that bridges located at crucial river crossings fail during a CSZ earthquake, rivers will become natural barriers affecting the ability to support response and recovery efforts. The characteristics of rivers (e.g., width, depth, and flow) are critical data to inform planning for the recovery of transportation systems across river barriers and determine reopening times following a CSZ earthquake. As part of the transportation system assessment, an Argonne National Laboratory (Argonne) project team developed a River Characterization Tool (RCT) to quantify the physical characteristics of the river system in Oregon, which can be used to inform a system-level analysis of transportation recovery and reopening times. This report mainly discusses approaches, methods, development, and applications of the RCT. The use of the river data generated from this tool for a system-level analysis of transportation recovery is discussed in the Oregon Transportation Systems RRAP Resiliency Assessment report (CISA 2021). The primary goal of the RCT is to generate statewide dataset of widths, depths, and flows for all rivers across Oregon to assess the effects of river barriers on emergency response and recovery efforts following a CSZ earthquake. The RCT leverages remote sensing data that multispectral sensors collect from satellites, employs a deep learning model to characterize river predictions, and computes river channel geometric dimensions with hydraulic relationships and river predictions. The entire process of river characterization is automated and implemented through the RCT.

58 GEOSCIENCES↗

Numerical modeling of ion transport and adsorption in porous media: A pore-scale study for capacitive deionization desalination

In this report a pore-scale model is presented to simulate the dynamic ion transport and adsorption processes in porous electrodes used for capacitive deionization (CDI). The Stokes equation governing water flow is solved using the lattice Boltzmann method and Nernst-Planck equation describing ion transport is solved using the finite volume method. The ion adsorption process is considered at the surface of carbon electrodes. After validation against analytical solutions and published results, the model is used to study the coupled water flow, ion transport and adsorption in both two-dimensional and three-dimensional porous CDI electrodes at the pore scale. The effect of electrode microstructure, electrical potential and flow velocity on the adsorption processes is quantitatively investigated, and the relative importance of various parameters is determined. The presented model can be a powerful numerical tool to quantitatively analyze ion transport and adsorption in porous electrodes, and may provide useful information for the design and optimization of CDI electrodes and operating conditions for desired desalination efficiency, water throughput and cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal CO2 Transport and Storage Cost Screening: Application Example

Poster on “Optimal CO2 Transport and Storage Cost Screening: Application Example” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. A major challenge to commercial scale CCS deployment from the perspective of coal and natural gas-fired power plants is understanding cost-optimal CO2 transport and viable geologic storage options. This study demonstrates unique workflows, using NETL-developed, publicly-available models and tools, to efficiently estimate optimal CO2 transport and storage (T&S) costs for each of the CO2 sources in NETL’s Carbon Capture Retrofit Databases (CCRD) for Electricity Generating Units. The results demonstrate the impact of cost-drivers on optimal T&S, and trends in optimal T&S data, based on real point sources that could be retrofitted with CO2 source technologies.

application example↗

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluating diffusion and the thermodynamic factor for binary ionic mixtures

Molecular dynamics (MD) simulations are a powerful tool for the calculation of transport properties in mixtures. Not only are MD simulations capable of treating multicomponent systems, they are also applicable over a wide range of temperatures and densities. In plasma physics, this is particularly important for applications such as inertial confinement fusion. While many studies have focused on the effect of plasma coupling on transport properties, here we focus on the effects of mixing. We compute the thermodynamic factor, a measure of ideal/non-ideal mixing, for three binary ionic mixtures. Here, we consider mixtures of hydrogen and carbon, hydrogen and argon, and argon and carbon, each at 500 randomly generated state points in the warm dense matter and plasma regimes. The calculated thermodynamic factors indicate different mixing behavior across phase space, which can significantly affect the corresponding mutual diffusion coefficients. As MD simulations are still computationally expensive, we apply modern data science tools to predict the thermodynamic factor over a large phase space. Further, we propose a more accurate approximation to the mutual diffusion coefficient than the commonly applied Darken relation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetic imaging of topological phases of matter (Final Report)

This project presents a detailed understanding of the local electronic transport in two different types of conductors. The experimental tools are a combination of local magnetic probes and electronic transport measurements. The first set of samples were superconducting microstructures that exhibited unusual transport behavior. Magnetic imaging revealed the presence of a strain field in the microstructures, which spatially modulated the superconducting properties. This strain field can be controlled through a variety of design parameters opening opportunities for a broad range of quantum materials including topological phases of matter. The second set of samples was fabricated from Cr-doped (Bi,Sb) 2 Te 3 heterostructures that exhibited the quantum anomalous Hall effect (QAHE). Magnetic imaging visualized the current flow in these devices, while simultaneous transport measurements verified that the devices exhibit the QAHE. Surprisingly, the current flowed in the interior of the sample even when exhibiting a high level of quantization.

36 MATERIALS SCIENCE↗

FY2019 Energy Efficient Mobility Systems Annual Progress Report

EEMS Program activities during FY 2019 focused on analytical research to understand the impacts that new mobility technologies and services will have at the vehicle, traveler, and overall transportation system-level. This research included the development of vehicle and transportation system simulation models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results for projects within four of the five EEMS activity areas: (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) High Performance Computing and Big Data Solutions for Mobility Data, (3) Advanced R&D Projects conducted by industry and academia, and (4) Core Modeling, Simulation, and Evaluation, Similarly, the remaining EEMS activity area – (5) Living Labs (managed under VTO’s Technology Integration Program). Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

In situ thermal conductivity measurement revealing kinetics of thermochemical reactions

Utilizing thermochemical reactions for thermal energy storage and solar fuel production has been an emerging research topic. Thermal transport properties of the materials are an important parameter that can determine the kinetics and efficiency of thermochemical reactions. With the increasing number of new thermochemical materials (TCMs); however, there is a lack of reliable techniques to monitor the thermal transport property of the materials and their changes as a function of reactions in real time. In this work, we report the in situ monitoring of thermochemical reactions using modulated photothermal radiometry (MPR). The thermal conductivities of two TCMs, namely, calcium hydroxide (Ca(OH) 2 ) and Ba 0.15 Sr 0.85 FeO 3–δ (BSF1585), were measured as a function of temperature and time using the MPR technique. The measured thermal conductivities were correlated to the reaction. The work has two significant contributions to the research communities. First, it provides a non-invasive diagnostic tool for monitoring the thermal transport properties of TCMs that can potentially be a high-throughput measurement technique conducive to optimizing TCMs, reactors, and related thermal systems. Second, for TCMs that show observable changes in thermal transport properties, a correlation between the measured thermal conductivity and the conversion fraction of the reaction can be established for monitoring the reaction kinetics based on thermal characterization.

14 SOLAR ENERGY↗