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DOE OSTI2022

Experimental Investigation of a Phase Change Material Charged Finned-Tube Heat Exchanger

Understanding different thermal performance aspects of phase change material heat exchangers (PCM-HX) is critical for designing future energy-efficient thermal energy storage systems. This paper presents an experimental performance analysis of a vertically oriented annular finned-tube PCM-HX in a cylindrical container tested under six different melting and solidification test conditions, varied by heat transfer fluid’s (HTF) inlet temperatures and flow directions. The PCM-HX structure with 20 evenly spaced fins was 3D printed in aluminum, and the PCM-HX container was 285 mm in height. The PCM-HX average porosity was 89.7%, where the PCM mass was 246.4 g. Water served as the HTF, and a PCM with a nominal phase change temperature of 35 °C was selected. Instead of opaque conventional insulation sheets, a combination of air-and-argon-filled see-through insulation cylinders was assembled with the PCM-HX to visualize the phase-change phenomena, while minimizing the uncertainties due to heat loss. In total, there were 78 T-type thermocouples installed in the test section which allows a more precise assessment of thermal mass and heat loss, which are often neglected in similar studies found in the literature. We validated the reliability of the test facility as the repeated test results had negligible deviations under the same test conditions. The energy balances between the estimated theoretical and experimentally calculated PCM storage, considering heat loss and thermal mass, were within ±9% deviation for all test conditions. From the experimental investigations, we made several following observations. It was found that the melting pattern of the finned-tube PCM-HX with small gaps between the container wall and the fins was largely affected by the HTF flow directions, unlike the typical straight annular tube PCM-HX. For effective charging and discharging processes, a combination of upward melting and downward solidification is recommended to shorten the test duration. However, an upward solidification should be considered to minimize the cavity formation between the fins caused by the PCM volume contraction during the solidification process.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Space Policy Directive-1 has led to NASA partnerships with commercial entities on procurement which includes the development of the Human Landing System (HLS) [1]. With the goal of delivering human crew to the lunar surface by 2024, system uncertainties become an important obstacle to the maturation of multiple new, driving technologies and mission concepts of the HLS program. As unmitigated uncertainties have previously led to failed development programs, these risks and their impacts must be understood and handled to ensure program success [2]. Sources of uncertainty include novel engine designs and configurations, increased reliance on cryogenic fluid management(CFM), and refueling technologies—which propagate as high-level performance metrics such as overall propellant mass and engine performance. Also, the occurrence of operational uncertainties—e.g. launch conditions or need to abort during the mission—can cause cascading effects on the rest of the mission that are difficult to definitively quantify, and are outside the scope of control. These concrete examples and other occurrences can be categorized as either epistemic or aleatory uncertainties.Epistemic uncertainty arises due to a lack of knowledge and can be alleviated with design and program maturation. Aleatory uncertainty is due to the inherent randomness of the system and cannot be directly reduced, unlike epistemic uncertainty. Robust design and probabilistic methods can compensate for aleatory effects. A taxonomy of uncertainty is referred to for this work [3]. In this paper, a probabilistic methodology to handle uncertainties has been demonstrated on a three-element HLS concept [1, 4], which allows tracking of current best estimates of the concept and assessment of concept design robustness against uncertainties. A sample case has been completed for this abstract, and an expansion on the methodology will be included in the final paper. This methodology has two key parts: first, the creation of a dynamic architecture model of a three-element HLS concept; and second, its use with surrogate modeling and range estimating techniques to capture and propagate uncertainties. This abstract will cover the basics of the approach used, and further details and justifications will be in the final paper.The mission profile associated with this three-element concept (Fig 1) was modeled as a set of mission events that facilitated mass changes, idles, or spacecraft maneuvers. The mission profile scope starts with each element’s NRHO orbit insertion and aggregation and ends at post-sortie rendezvous with Orion. More detail on the mission profile will be in the final paper. The DYnamic Rocket EQuation Tool (DYREQT), a space systems synthesis and sizing framework used by NASA, was used as the physics framework to model the HLS architecture for applying the probabilistic methodology [5, 6]. Specifically, a parametric representation of the lander, ascent, and transfer elements and the mission profile of each element was established, with vehicle and mission parameters available as inputs to allow for a dynamic model. Each vehicle stage was modeled with high-level performance metrics, using Isp and propellant mass fraction (PMF) to remain parametric. For the probabilistic analysis, uncertainties of interest within the HLS concept were enumerated and represented as parameters within the DYREQT model as inputs for vehicle stages or mission profile events. These parameters were frozen at their nominal values for the purposes of baselining architecture performance and sizing the vehicle appropriately based on reference documentation [1]. Range estimating—a probabilistic method that combines Monte Carlo sampling, focus on critical parameters, and heuristics to assess risk and opportunities—is traditionally used with Mass Equipment Lists (MELs), but has been adapted with operational parameters as well as vehicle parameters in theDYREQT model to capture mission uncertainty alongside vehicle uncertainty [7, 3]. This method was selected due to its application and insight on a system from a bottom-up perspective, independence from historical rules of thumb, and ability to generate sensitivities based on design decisions and uncertainties. As a sample case for the abstract, the boiloff rates of the vehicle elements and the loiter times during the mission (simulating launch time variations and changing window of opportunities) were used with range estimating to provide preliminary results. To perform the range estimation portion of this methodology (depicted in Fig. 3, further details in final paper), the DYREQT model was sampled using a Design of Experiments (DoE) to efficiently explore the architecture design space with respect to the sample set of uncertainty parameters; 5,000 cases via Latin Hypercube Sampling were computed on the DYREQT architecture model. Then, the results were used to create surrogate models, multivariate regressions that can visualize hypercube trends in the design space, of the architecture with respect to the uncertainty parameters. Range estimating was applied to the surrogates instead of the actual models, which saves computational expense due to the bulk of cases needed for the Monte Carlo simulation as part of range estimating. Uncertainty parameters were sampled independently from triangular distributions using the DoE ranges as ‘min’ and ‘max’, and the nominal value as ‘most likely’. Based engineering intuition, some uncertainty parameters are correlated—e.g. if the main propellant has a high boil-off rate, the oxidizer should follow suit as both are related to CFM technology.While a Monte Carlo simulation samples all inputs as independent, the results would show model correlations; thus, it is efficient to sample the inputs as correlated. Using a correlation matrix constructed for the uncertainty parameters, previously independent samples were transformed to perform a Correlated Monte Carlo. A table for the DoE ranges and probability distribution parameters is shown in Table 1, and more details on Correlated Monte Carlo Simulations will be discussed in the final paper. The model’s resulting DoE showed that multivariate polynomial equations fit via least squares method captured its behavior accurately for the sample case. For the Correlated Monte Carlo Simulation, a positive correlation between fuel and oxidizer boiloff rates was used as a demonstration. 10,000 cases were computed with the surrogates and the launched masses for each vehicle element was collated. The results can be displayed in a probability density function (PDF), showing the impact of the uncertainty parameters chosen. Integrating the PDFs will yield a cumulative distribution function (CDF) that shows the cumulative probability of a given value on the x-axis. For the sample case, the elements’ launch mass margin was calculated and represented in as CDFs, as a demonstrated representation of figures of merit for the HLS concept. For the lander and ascent elements, the NRHO mass insertion limit is 16t; the transfer element has a limit of 30t [1]. It can be seen with Figure 2 that this probabilistic methodology can provide insight into mass margin with respect to the uncertainties being modeled. Currently, the results show that the lander (descent) vehicle element has the most restrictive design space; it is the only element to show a 10% probability of negative margin. Further analysis on the Monte Carlo results will show sensitivities for driving constraints and parameters for architecture feasibility, which can lead to establishing potential mission rules.The combination of range estimating with a parametric architecture model for HLS demonstrated the capability of this probabilistic methodology in a sample case. As the HLS development progresses, this methodology has the potential for keeping current best estimates of architecture performance for awarded concepts due to the flexibility in DYREQT’s modeling framework and its parametric nature. Concept maturation and increased epistemic knowledge can be injected into the model probabilistic modeling, and thus continue to track probability of mission success.

Stephanie Y Zhu↗

DOE OSTI2021

Structure Perception in 3D Point Clouds

Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗

DOE OSTI2021

Structure Perception in 3D Point Clouds: Preprint

Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗

DOE OSTI2016

SCALE Code System

The SCALE Code System is a widely-used modeling and simulation suite for nuclear safety analysis and design that is developed, maintained, tested, and managed by the Reactor and Nuclear Systems Division (RNSD) of Oak Ridge National Laboratory (ORNL). SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor and lattice physics, radiation shielding, spent fuel and radioactive source term characterization, and sensitivity and uncertainty analysis. Since 1980, regulators, licensees, and research institutions around the world have used SCALE for safety analysis and design. SCALE provides an integrated framework with dozens of computational modules including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution strategy. SCALE includes current nuclear data libraries and problem-dependent processing tools for continuous-energy (CE) and multigroup (MG) neutronics and coupled neutron-gamma calculations, as well as activation, depletion, and decay calculations. SCALE includes unique capabilities for automated variance reduction for shielding calculations, as well as sensitivity and uncertainty analysis. SCALE’s graphical user interfaces assist with accurate system modeling, visualization of nuclear data, and convenient access to desired results.SCALE 6.2 provides many new capabilities and significant improvements of existing features.New capabilities include:• ENDF/B-VII.1 nuclear data libraries CE and MG with enhanced group structures,• Neutron covariance data based on ENDF/B-VII.1 and supplemented with ORNL data,• Covariance data for fission product yields and decay constants,• Stochastic uncertainty and correlation quantification for any SCALE sequence with Sampler,• Parallel calculations with KENO,• Problem-dependent temperature corrections for CE calculations,• CE shielding and criticality accident alarm system analysis with MAVRIC,• CE depletion with TRITON (T5-DEPL/T6-DEPL),• CE sensitivity/uncertainty analysis with TSUNAMI-3D,• Simplified and efficient LWR lattice physics with Polaris,• Large scale detailed spent fuel characterization with ORIGAMI and ORIGAMI Automator,• Advanced fission source convergence acceleration capabilities with Sourcerer,• Nuclear data library generation with AMPX, and• Integrated user interface with Fulcrum.Enhanced capabilities include:• Accurate and efficient CE Monte Carlo methods for eigenvalue and fixed source calculations,• Improved MG resonance self-shielding methodologies and data,• Resonance self-shielding with modernized and efficient XSProc integrated into most sequences,• Accelerated calculations with TRITON/NEWT (generally 4x faster than SCALE 6.1),• Spent fuel characterization with 1470 new reactor-specific libraries for ORIGEN,• Modernization of ORIGEN (Chebyshev Rational Approximation Method [CRAM] solver, API for high-performance depletion, new keyword input format)• Extension of the maximum mixture number to values well beyond the previous limit of 2147 to ~2 billion,• Nuclear data formats enabling the use of more than 999 energy groups,• Updated standard composition library to provide more accurate use of natural abundances, andvi• Numerous other enhancements for improved usability and stability.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2023

Driving mode analysis—How uncertain functional inputs propagate to an output

Abstract Driving mode analysis elucidates how correlated features of uncertain functional inputs jointly propagate to produce uncertainty in the output of a computation. Uncertain input functions are decomposed into three terms: the mean functions, a zero‐mean driving mode, and zero‐mean residual. The random driving mode varies along a single direction, having fixed functional shape and random scale. It is uncorrelated with the residual, and under linear error propagation, it produces an output variance equal to that of the full input uncertainty. Finally, the driving mode best represents how input uncertainties propagate to the output because it minimizes expected squared Mahalanobis distance amongst competitors. These characteristics recommend interpretation of the driving mode as the single‐degree‐of‐freedom component of input uncertainty that drives output uncertainty. We derive the functional driving mode, show its superiority to other seemingly sensible definitions, and demonstrate the utility of driving mode analysis in an application. The application is the simulation of neutron transport in criticality experiments. The uncertain input functions are nuclear data that describe how Pu reacts to bombardment by neutrons. Visualization of the driving mode helps scientists understand what aspects of correlated functional uncertainty have effects that either reinforce or cancel one another in propagating to the output of the simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Partnership for Edge Physics Simulation (EPSI)

We propose to develop advanced simulation codes, based upon an extreme parallelism, first principles kinetic approach, to address the challenges associated with the edge region of magnetically confined plasmas. This work is relevant to both existing magnetic fusion facilities and essential for next-generation burning plasma experiments, such as ITER where success is critically dependent upon H-mode operation achieving an edge pedestal of sufficient height for good core plasma performance without producing deleterious large scale edge localized instabilities. The plasma edge presents a well-known set of multi-physics, multi-scale problems involving complex 3D magnetic geometry. Perhaps the greatest computational challenge is the lack of scale separation – temporal scales for drift waves, Alfven waves, ELM dynamics for example have strong overlap. Similar overlap occurs on the spatial scales for the ion poloidal gyro-radius, drift wave and pedestal width. The traditional approach of separating fusion problems into weakly interacting spatial or temporal domains clearly breaks down in the edge. A full kinetic model (full-f model) must be solved to understand and predict the edge physics including non-equilibrium thermodynamic issues arising from the magnetic topology (the open field lines producing a spatially sensitive velocity hole), plasma wall interactions, neutral and atomic physics. The plan here is to model these phenomena within a comprehensive first principles set of equations without the need for the insurmountable multiple-codes coupling issues by building on the XGC1 code developed under the SciDAC Proto-FSP Center for Plasma Edge Simulation (CPES). This proposal includes the critical participants in the XGC1 development. We propose enhancing the capability of XGC1 by including all the important turbulence physics contained in kinetic ion and electron electromagnetic dynamics, by extending the PIC technology to incorporate several positive features found in the Eulerian grid technology, combining the coarse grained XGC0 code into it with a multiscale projective time integration technique to be developed in the project for experimental time scale simulation of the edge multi-physics, and by implementing modern computational technologies to move forward with the extreme scale heterogeneous hardware/software platform development. Ultra-fast edge localized instabilities, involving compressional Alven modes, will be studied using a proper MHD or two-fluid codes employing kinetic closure information from XGC. The proposed research integrates the most important physical processes on overlapping temporal and spatial scales, to study (i) transitions and thresholds for enhanced confinement regimes, (ii) the predictive understanding of the edge pedestal formation, structure and dynamics, (iii) the effect of the edge plasma on the core confinement, (iv) the physics of Edge Localized Modes and their suppression or mitigation via external control techniques, and (v) the heat load on the material wall. Our approach will implement physical models that are valid in their relevant collisionality regimes for current experiments and future burning plasma devices. Comparisons with experimental data will be made at multiple levels including characterization of turbulence dynamics, flux-gradient responses in the energy, particle and momentum channels, and observations of global phenomena such as L-H transitions, momentum generation, ELM dynamics, ELM-free regimes and the tokamak density limit. The proposal team has established strong connections, through joint membership, with other organizations that will be critical for success. These include FASTMath, SUPER and QUEST Institutes respectively for meshing tools and solvers; code performance tuning and uncertainty quantification as well as a proposed Data Management and Visualization Institute.. We will also be teaming with ongoing fusion SciDAC’s: CSWPI for RF-edge plasmas interactions; CEMM for the M3D MHD simulations and with PEPSC for incorporation of energetic particle physics. Finally, the team includes representatives from each of the major U.S. experimental facilities who will coordinate the validation program and the development of synthetic diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Stellar Population Properties in the Stellar Streams around SPRC047

Abstract We have investigated the properties (e.g., age, metallicity) of the stellar populations of a ringlike tidal stellar stream (or streams) around the edge-on galaxy SPRC047 (z= 0.031) using spectral energy distribution (SED) fits to integrated broadband aperture flux densities. We used visual images in six different bands and Spitzer/IRAC 3.6μm data. We have attempted to derive best-fit stellar population parameters (metallicity, age) in three noncontiguous segments of the stream. Due to the very low surface brightness of the stream, we have performed a deconvolution with a Richardson–Lucy–type algorithm of the low spatial resolution 3.6μm IRAC image, thereby reducing the effect of the point-spread function aliasedemissionfrom the bright edge-on central galaxy at the locations of our three stream segments. Our SED fits that used several different star formation (SF) history priors, from an exponentially decaying SF burst to continuous SF, indicate that the age–metallicity–dust degeneracy is not resolved, most likely because of inadequate wavelength coverage and low signal-to-noise ratios of the low surface brightness features. We also discuss how future deep visual–near-infrared observations, combined with absolute flux calibration uncertainties at or below the 1% level, complemented by equally well absolute flux-calibrated observations in ultraviolet and mid-infrared bands, would improve the accuracy of broadband SED fitting results for low surface brightness targets, such as stellar streams around nearby galaxies that are not resolved into stars.

Astronomy & Astrophysics↗

NASA NTRS2023

Information Systems Technology for NASA Earth Systems Digital Twins (ESDT)

The term “Digital Twin” was first used in 2002 for product lifecycle management. Since then, Digital Twin concepts have been proposed in various domains until very recently for Earth Science. For NASA’s Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as composed of three components: 1. A Digital Replica, i.e., an integrated picture of the past and current states of Earth systems 2. Forecasting capabilities, providing an integrated picture of how Earth systems will evolve in the future from the current state 3. Impact Assessment capabilities, providing an integrated picture of how Earth systems could evolve under different hypothetical what-if scenarios. Developing such a vision will require technologies related to: integrating continuous observations from various disparate sources; developing frameworks that builds on inter-connected models; improving the speed and accuracy of integrated prediction, analysis and visualization capabilities (e.g., by using machine learning); and utilizing causality and uncertainty quantification to improve our understanding of the evolution of Earth Science systems as a function of their interactions with other Earth and human systems. In addition, AIST is also investigating interoperability standards to federate multiple Digital Twins, as well as computational resources required by those systems.

Earth Science Remote Sensing; Information Systems↗

NASA NTRSDate not supplied

Flow Visualization of Intrusive and Non-Intrusive Configurations for Lunar- and Martian-Relevant Plume-Surface Interaction

Flow visualization of a heated, inert-gas plume impinging onto a rigid surface was performed in lunar- and Martian-relevant pressure conditions. The experimental campaign was part of a broader effort to improve predictive models and capabilities for plume-surface interactions in spacecraft landing environments relevant to the Moon and Mars. The experiments used the planar laser induced fluorescence (PLIF) technique to visualize the flow of the jet over both a full-plane configuration using a flat impingement plate and a half-plane configuration where the jet flow was bisected by a splitter edge mounted to the impingement plate. The latter configuration has been previously used to study erosion mechanisms in plume-surface interactions because the technique enables cross-sectional optical access for visualizing the plume-induced crater. However, this approach has some uncertainty regarding the influence of the splitter edge on the flow field. The present work evaluates the differences in flow structures and characteristics between the flat plate and splitter plate experimental configurations at eight unique test conditions with and without the splitter edge where the vacuum chamber pressure, nozzle mass flow rate, and height of the nozzle were varied. Several features are identified which differ between the flat plate and splitter plate comparison cases, and these are summarized in this paper. The results presented provide insights to the differences between intrusive and non-intrusive experimental configurations for plume-surface interaction studies that can be used to further validate predictive models and inform future ground and flight test results.

PLIF↗

NASA NTRSDate not supplied

Flow Visualization of Intrusive and Non-Intrusive Configurations for Lunar- and Martian-Relevant Plume-Surface Interaction

Flow visualization of a heated, inert-gas plume impinging onto a rigid surface was performed in lunar- and Martian-relevant pressure conditions. The experimental campaign was part of a broader effort to improve predictive models and capabilities for plume-surface interactions in spacecraft landing environments relevant to the Moon and Mars. The experiments used the planar laser-induced fluorescence (PLIF) technique to visualize the flow of the jet over both a full-space configuration using a flat impingement plate and a half-space configuration where the jet flow was bisected by a splitter edge mounted to the impingement plate. The latter configuration has been previously used to study erosion mechanisms in plume-surface interactions because the technique enables cross-sectional optical access for visualizing the plume-induced crater. However, this approach has some uncertainty regarding the influence of the splitter edge on the flow field. The present work evaluates the differences in flow structures and characteristics between the flat plate and splitter plate experimental configurations at eight unique test conditions with and without the splitter edge where the vacuum chamber pressure, nozzle mass flow rate, and height of the nozzle were varied. Several features are identified which differ between the flat plate and splitter plate comparison cases, and these are summarized in this paper. The results presented provide insights to the differences between intrusive and non-intrusive experimental configurations for plume-surface interaction studies that can be used to further validate predictive models and inform future ground and flight test results.

PLIF↗

DOE OSTI2018

A High Performance Computational Framework for Dynamic Security Assessment under Uncertainty

Dynamic security assessment (DSA) is a critical function to evaluate power grids’ capability to survive the transition caused by a set of disturbances to an acceptable steady-state condition. Its computational burden is heavy. With the challenges brought by renewable energy and new smart grid technologies, DSA under uncertainty has to be considered to study the impact of forecast errors on DSA simulation, which further increases the computational burden. To address this challenge, this paper presents a high performance computational framework to support DSA simulation user uncertainty. The computational framework aims to provide a seamless workflow that links data from high performance computing, statistical analysis, to visualization so that a problem can be easily expressed in a way compatible with different functions. It also enables software compatibility such that application development can be more efficient. Case study results of the ESCA60 system and a western U.S. size system show the advantages and efficiency of the computational framework.

dynamic security assessment, high performance comp↗

NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗

DOE OSTI2015

Advanced simulation capability for environmental management, integrated tool-sets and simulator to enhance public communication - 15186

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater Remediation, is supporting multi-laboratory development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. ASCEM facilitates transparent, efficient and integrated approaches to modeling and site characterization, and provides robust and standardized assessments of performance and risk for EM cleanup and closure activities. Site subsurface simulation modeling and performance assessments are complex and involve sensitivity evaluations and uncertainty quantification to better understand the risks at a site. The ASCEM tool-set was designed in close collaboration with the sites and other potential end-users (both the public and regulators) to allow better communication and understanding of these complex modeling efforts. ASCEM's integrated tool-sets provide a user interface and tools for managing work-flows, including conceptual model development, management of data and metadata for model input, sensitivity analysis, model calibration and uncertainty analysis, model execution on diverse computational platforms, and processing of model output, including visualization. The hierarchical and modular design of ASCEM HPC simulator Amanzi easily lends itself to translating this conceptual model of a site into a numerical model that can easily be spatially and temporally discretized to run on the HPC simulator. Together this integrated work-flow allows for a seamless and integrated analysis tracking all provenance information and modeling uncertainties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

The Molten Salt Reactor (MSR) represents a significant innovation in nuclear technology, offering several operational and safety benefits over traditional solid-fuel reactors. However, MSRs face uncertainties in waste management due to their flexible designs and variable waste compositions. To address these challenges, we propose a visualization platform that illustrates solutions and performance predictions for various waste management strategies, enhancing user experience and improving strategy and communication. Immersive visualizations are widely used in the nuclear industry for training, simulation, and safety enhancement. Our project aims to develop a visualization platform incorporating virtual reality (VR) technologies to illustrate MSR characteristics immediately following reactor shutdown. This immersive simulation will allow users to interact, explore, and understand different waste management strategies. The platform will display MSR reactor characterizations, including nuclide decay, salt solidification, and corrosion, which are crucial for assessing and selecting backend management strategies. Using the Meta Quest 3 VR headset with Unity software, our platform will provide real-scale visualizations, enabling users to experience and evaluate designs and plans as if they were physically present. This user-friendly interface will make complex data accessible and understandable for non-domain experts, aiding in decision-making for MSR waste management. Our proposed visualization workflow can be applied to other nuclear reactors, assisting in the design and planning of waste management strategies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

The inclusion of uncertainty in circularity transition modeling: A case study on wind turbine blade end-of-life management

The transition to a more circular economy (CE) is complex and hard to predict, including in sustainable energy technologies. Many sources of uncertainty make it challenging to model CE scenarios and their potential benefits. As an example, the high variability in costs and revenues of different recycling options makes future wind turbine blade recycling highly uncertain. To better understand this challenge, the circular economy, life cycle assessment and visualization (CELAVI) framework - a discrete event simulation and life cycle assessment framework - is modified to incorporate uncertainty analysis capabilities. Moreover, a 3-step procedure that covers different aspects of uncertainty in CE studies and includes a Monte-Carlo analysis is proposed. The procedure is tested in a case study on wind turbine blade recycling using CELAVI. Results highlight that grinding and landfilling costs are the most influential parameters for wind power circularity. The model's output coefficients of variation (when input parameter uncertainties are propagated) are between 92% and 384% depending on the indicator. The approach developed in this study may help researchers and decision-makers who study circularity prioritize their data collection effort. Finally, our method contributes to a mounting yet critical body of research: the measurement of uncertainty in circularity transitions.

17 WIND ENERGY↗

DOE OSTI2017

Mass extinction efficiency and extinction hygroscopicity of ambient PM{sub 2.5} in urban China

The ambient PM{sub 2.5} pollution problem in China has drawn substantial international attentions. The mass extinction efficiency (MEE) and hygroscopicity factor (f(RH)) of PM{sub 2.5} can be readily applied to study the impacts on atmospheric visibility and climate. The few previous investigations in China only reported results from pilot studies and are lack of spatial representativeness. In this study, hourly average ambient PM{sub 2.5} mass concentration, relative humidity, and atmospheric visibility data from China national air quality and meteorological monitoring networks were retrieved and analyzed. It includes 24 major Chinese cities from nine city-clusters with the period of October 2013 to September 2014. Annual average extinction coefficient in urban China was 759.3±258.3 Mm{sup −1}, mainly caused by dry PM{sub 2.5} (305.8.2±131.0 Mm{sup −1}) and its hygroscopicity (414.6±188.1 Mm{sup −1}). High extinction coefficient values were resulted from both high ambient PM{sub 2.5} concentration (68.5±21.7 µg/m{sup 3}) and high relative humidity (69.7±8.6%). The PM{sub 2.5} mass extinction efficiency varied from 2.87 to 6.64 m{sup 2}/g with an average of 4.40±0.84 m{sup 2}/g. The average extinction hygroscopic factor f(RH=80%) was 2.63±0.45. The levels of PM{sub 2.5} mass extinction efficiency and hygroscopic factor in China were in comparable range with those found in developed countries in spite of the significant diversities among all 24 cities. Our findings help to establish quantitative relationship between ambient extinction coefficient (visual range) and PM{sub 2.5} & relative humidity. It will reduce the uncertainty of extinction coefficient estimation of ambient PM{sub 2.5} in urban China which is essential for the research of haze pollution and climate radiative forcing. - Highlights: • Data from air quality and meteorological monitoring networks were combined. • MEE and hygroscopicity of PM{sub 2.5} in China was similar to that of developed countries. • High extinction coefficient was dominated by both high PM{sub 2.5} and relative humidity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

SCALE Code System 6.2.1

22 GENERAL STUDIES OF NUCLEAR REACTORS↗