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DOE OSTI2018

Bison Fuel Performance Modeling on RIA in a PWR

This report is prepared to fulfill a Level 2 milestone for CASL on “deliver and document RIA fuel performance modeling using Bison fuel performance code.” The work performed is focused on modeling the full length commercial fuel rod response under a design basis Reactivity Initiated Accident (RIA), in particular, a hypothetical Control Rod Ejection Accident (CREA) in a Pressurized Water Reactor (PWR). Fuel rods with different burnups, 0 (fresh fuel), 20, 40, and 60 GWd/tU have been modeled with a reactivity worth insertion of $1.24 at Hot Zero Power (HZP) condition. Bison failure modeling method, and a brief summary of validations on selected RIA cases from CABRI and NSRR testing facilities are also described. The work performed has demonstrated the successful application of Bison code in the modeling of thermal and mechanical responses in RIAs for PWRs. In particular, Bison code has a more mature capability in the modeling of the frictional contact between pellet and cladding of the high burnup fuels, which is critical for modeling the Pellet Clad Mechanical Interaction (PCMI). The modeling of RIA using Bison code shows fuels in PWR environment could have different responses than in the simulated RIA tests, and results indicate that a transition from PCMI to Departure from Nucleate Boiling (DNB) could happen at relatively lower enthalpies: a better heat transfer from the fuel to coolant could increase cladding temperature and ductility, but at the same time also reduces the margin to DNB, which could cause high temperature oxidation and ballooning type of failures. The precise determination of the transition into DNB may rely on a more accurate input of the power histories in the simulated RIAs from VERA, the core simulator of CASL. The limiting conditions in PWRs could be quite different than those tests with non-typical testing conditions, and the improvement of the modeling of thermal responses, such as, clad coolant heat transfer, gap heat transfer, clad thermal inertia, and radial power profiles could be important considerations of the RIAs. In modeling the fuel responses in a fast transient, a number of variables could affect the initial burnup states, and some material models, e.g., fuel mechanical models, fission gas release, and corrosion models, and parameters can affect modeling results as well. Those uncertainties and advanced modeling capabilities need to be investigated in the future study of RIAs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.

58 GEOSCIENCES↗

DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Image transformers for classifying acute lymphoblastic leukemia

Cancer is the leading cause of death by disease in American children. Each year, nearly 16,000 children in the United States and over 300,000 children globally are diagnosed with cancer. Leukemia is a form of blood cancer that originates in the bone marrow and accounts for one-third of pediatric cancers. This disease occurs when the bone marrow contains 20% or more immature white blood cell blasts. Acute lymphoblastic leukemia is the most prevalent leukemia type found in children, with half of all annual cases in the U.S. diagnosed for subjects under 20 years of age. To diagnose acute lymphoblastic leukemia, pathologists often conduct a morphological bone marrow assessment. This assessment determines whether the immature white blood cell blasts in bone marrow display the correct morphological characteristics, such as size and appearance of nuclei. Pathologists also use immunophenotyping via multi-channel flow cytometry to test whether certain antigens are present on the surface of blast cells; the antigens are used to identify the cell lineage of acute lymphoblastic leukemia. These manual processes require well-trained personnel and medical professionals, thus being costly in time and expenses. Computerized decision support via machine learning can accelerate the diagnosis process and reduce the cost. Training a reliable classification model to distinguish between mature and immature white blood cells is essential to the decision support system. Here, we adopted the Vision Transformer model to classify white blood cells. The Vision Transformer achieved superb classification performance compared to state-of-the-art convolutional neural networks while requiring less computational resources for training. Additionally, the latent self-attention architecture provided attention maps for a given image, providing clues as to which portion(s) of the image were significant in decision-making. We applied the Vision Transformer model and a convolutional neural network model to an acute lymphoblastic leukemia classification dataset of 12,528 samples and achieved accuracies of 88.4% and 86.2%.

Cho, Priscilla↗

NASA NTRS2004

Magnetohydrodynamic Convection in the Outer Core and its Geodynamic Consequences

The Earth's fluid outer core is in vigorous convection through much of the Earth's history. In addition to generating and maintaining Earth s time-varying magnetic field (geodynamo), the core convection also generates mass redistribution in the core and a dynamical pressure field on the core-mantle boundary (CMB). All these shall result in various core-mantle interactions, and contribute to surface geodynamic observables. For example, electromagnetic core-mantle coupling arises from finite electrically conducting lower mantle; gravitational interaction occurs between the cores and the heterogeneous mantle; mechanical coupling may also occur when the CMB topography is aspherical. Besides changing the mantle rotation via the coupling torques, the mass-redistribution in the core shall produce a spatial-temporal gravity anomaly. Numerical modeling of the core dynamical processes contributes in several geophysical disciplines. It helps explain the physical causes of surface geodynamic observables via space geodetic techniques and other means, e.g. Earth's rotation variation on decadal time scales, and secular time-variable gravity. Conversely, identification of the sources of the observables can provide additional insights on the dynamics of the fluid core, leading to better constraints on the physics in the numerical modeling. In the past few years, our core dynamics modeling efforts, with respect to our MoSST model, have made significant progress in understanding individual geophysical consequences. However, integrated studies are desirable, not only because of more mature numerical core dynamics models, but also because of inter-correlation among the geophysical phenomena, e.g. mass redistribution in the outer core produces not only time-variable gravity, but also gravitational core-mantle coupling and thus the Earth's rotation variation. They are expected to further facilitate multidisciplinary studies of core dynamics and interactions of the core with other components of the Earth.

Kuang, Weijia↗

DOE OSTI2025

Including frameworks of public health ethics in computational modelling of infectious disease interventions

Decisions on public health interventions to control infectious diseases are often informed by computational models. Interpreting the predicted outcomes of a public health decision requires not only high-quality modelling but also an ethical framework for assessing the benefits and harms associated with different options. The design and specification of ethical frameworks matured independently of computational modelling, so many values recognized as important for ethical decision-making are missing from computational models. We demonstrate a proof-of-concept approach to incorporate multiple public health values into the evaluation of a simple computational model for vaccination against a pathogen such as SARS-CoV-2. By examining a bounded space of alternative prioritizations of three values relevant to public health ethics (aggregate clinical burden, equity in clinical burden, equity in adverse effects from vaccination), we identify value trade-offs, where the outcomes of optimal strategies differ depending on the ethical framework. This work demonstrates an approach to incorporating diverse values into decision criteria used to evaluate outcomes of models of infectious disease interventions.

"Mathematical Biology"↗

DOE OSTI2018

Summary and Assessment of Metal Fuel Capabilities in Bison

The work described in this report was performed under funding from the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. This report is issued in satisfaction of the level 2 milestone M2MS-18IN0201012 on Release Bison with Initial Metallic Fuel Performance Capability. Metallic fuel development began in Bison a few years after light water reactor development began (~ 2009). The initial development was funded by the Advanced Fuels Campaign. With recent interest from industry, the Nuclear Regulatory Commission, and the Versatile Test Reactor program, the Nuclear Energy Modeling Simulation Program has increased funding for metallic fuel development and validation in FY18. The material models with the most mature development are binary uranium-zirconium and ternary uranium-plutonium-zirconium alloys for fuel and HT9 for cladding. The first material models were incorporated from open literature sources, which include mechanical and thermal material properties that are functions of temperature, porosity, and zirconium concentration, swelling, fission gas release, zirconium diffusion, creep, and sodium coolant channel boundary conditions. These material models have been utilized to simulate ERB-II fuel pins and the results compared to measurements. The EBR-II experiment measurements mostly consist of cladding strain and zirconium redistribution. As such, comparisons to EBR-II measurements are currently limited to these two figures of merit. Simulations and comparisons to experiment measurements have also been done for transient testing of EBR- II fuel pins in TREAT, which included temperature measurements. Preliminary comparisons between Bison calculations and experiment measurements are favorable. These comparisons have also highlighted the importance of the fuel swelling and fission gas release models on cladding strain. Also, Bison metallic fuel simulations are currently being run in support of ATR experiments and VTR exploratory design calculations. Further development and evaluation of individual material models and fuel system models are planned for FY19.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Development of a U-19Pu-10Zr fuel performance benchmark case based on the IFR-1 experiment

Metallic nuclear fuels are subject to research and development for use in advanced reactors. Robust, accurate metallic fuel performance models are important for the design, safety analysis, and licensing of these reactors. However, metallic fuel performance models require additional development; they are not as mature as UO 2 fuel performance models. A benchmark case based on the IFR-1 experiment was developed to better gauge the accuracy of existing models, identify models for high-priority development, and potentially quantify any future improvements made by further model development.This work collected publicly available information on the IFR-1 experiment and used it to develop the benchmark case. Fuel behavior during the IFR-1 irradiation was simulated by using the fuel performance code BISON, and the predicted results were compared with postirradiation examination data from the IFR-1 experiment. Furthermore, a sensitivity study and tuning studies were performed as a preliminary investigation into the causes of inaccurate temperature and dimensional change predictions.The benchmark predicted reasonably accurate values for the burnup and fission gas release. There was error in the predicted temperatures, which could be explained by uncertainty in the input parameters and legacy temperatures. BISON over-predicted dimensional changes in the fuel and cladding. The sensitivity study showed that the dimensional changes were most sensitive to the fuel swelling anisotropy and the cladding void swelling model. Future benchmark and model development should focus on cladding swelling behaviors to improve dimensional change predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Streamlining the Coupling of BISON and Dakota Through the NEAMS Workbench

Metallic nuclear fuels for use in advanced reactors are an active area of research and development. Robust, accurate metallic fuel performance models are necessary for the design, analysis, and licensing of such reactors. However, metallic fuel performance models require additional development; they are not as mature as uranium dioxide fuel performance models. To support further metallic fuel development, Oak Ridge National Laboratory and the University of Florida have streamlined the coupling of the BISON fuel performance code with Design Analysis Kit for Optimization and Terascale Applications (Dakota) statistical analysis tool through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench. This work included performing three different sensitivity analyses on metallic nuclear fuel models in BISON. The analyses examined were a general model of the IFR-1 experiment, the X430 experiment T654 pin, and the X430 experiment T651 pin. The results suggest that BISON and Dakota can be integrated through NEAMS Workbench to perform sensitivity and uncertainty analyses and visualize the results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1974

A general model for the textural evolution of lunar soil

The investigation reported is concerned with the qualitative expansion of an earlier model developed by Lindsay (1971, 1972, 1973). Questions regarding the maturity of lunar soils are examined. A multivariate model related to textural maturity is considered, taking into account mean and standard deviations, the asymmetry of the grain size curve, the kurtosis anomaly, and pyroclastic materials. It is concluded that the mean grain size and the standard deviation of the lunar soil can be used as general indicators of the textural maturity of the soil anywhere on the lunar surface.

Lindsay, J. F.↗

NASA NTRS2010

Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations.

Li, Xiaowen↗

NASA NTRS2019

A NASA Supply Chain Beyond Low Earth Orbit: Explore Moon to Mars

Presentation will highlight the Space Shuttle Program Lessons Learned with a simulation of the complexity, volatility and multi-functional relationships of the supplier base followed by a review of a key element in the NASA KSC Supply Chain/Logistics Strategic Roadmap to include supply chain resiliency modeling as impacted by 3D Printing technology maturation and campaign-level network flow modeling for logistics nodal positioning of critical product needed to support space operations and In-Space Manufacturing beyond Low Earth Orbit.

Supply Chain Analytics↗

DOE OSTI2018

The dual role of cGMP in oocyte maturation of zebrafish

Highlights: • Activation of the NO/sGC/cGMP pathway could lead to oocyte maturation (OM). • Inhibition of the NO/sGC/cGMP pathway could lead to OM. • NO level increased in follicular cells but remained constant in oocytes during OM. • cGMP level increased in the follicular cells but decreased in oocytes during OM. The roles of cyclic guanosine monophosphate (cGMP) signaling in oocyte maturation attracts much attention in mammals, but its roles in fish are still largely unknown. Using zebrafish as a model, we demonstrated for the first time in fish that cGMP is involved in oocyte maturation, and its functional model in oocyte maturation is different from that of mammals. The intracellular cGMP could be regulated by nitric oxide (NO), we found that all three NO synthase enzymes and four soluble guanylyl cyclases (sGC) are expressed in the zebrafish ovary. Intriguingly, either the activation or inhibition of the NO/sGC/cGMP pathway in fully grown follicles could lead to oocyte maturation. During oocyte maturation, cGMP levels increased in the follicular cell layer but decreased in oocytes, while NO levels increased in follicular cells but remained constant in oocytes. Based on these findings in zebrafish, we propose a hypothetical model on the dual role of cGMP in oocyte maturation: in follicular cells the LH signal could increase the level of NO and cGMP which induces oocyte maturation, while in the oocyte the decreased cGMP level can also induce oocyte maturation. These findings help us to understand the molecular mechanism of fish oocyte maturation.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2023

Advanced 2030 Turboprop Aircraft Modeling for the Electrified Powertrain Flight Demonstration Program

Electrified aircraft propulsion concepts are rapidly emerging due to their huge potential in fuel saving and mitigating negative environmental impact. In order to perform a linear technology progression and fairly assess the impacts of powertrain electrification, it is important to first establish parametric state-of-the-art baseline vehicle models with advanced technologies matured by 2030. For a regional turboprop (50-passenger) size class and a thin haul (19-passenger) turboprop size class, a current state-of-the-art technology reference aircraft (TRA) is identified and modeled using a multi-disciplinary analysis and optimization environment. Viable technologies for airframe and conventional propulsion system are then identified which are expected to be available by 2030. These technologies are parametrically infused in the TRA models to create advanced technology aircraft models, which will serve as the baseline models for future studies of powertrain electrification.

epfd↗

DOE OSTI2014

CHEMICAL ANALYSIS OF SIMULATED HIGH LEVEL WASTE GLASSES TO SUPPORT SULFATE SOLUBILITY MODELING

The U.S. Department of Energy (DOE), Office of Environmental Management (EM) is sponsoring an international, collaborative project to develop a fundamental model for sulfate solubility in nuclear waste glass. The solubility of sulfate has a significant impact on the achievable waste loading for nuclear waste forms both within the DOE complex and to some extent at U.K. sites. The development of enhanced borosilicate glass compositions with improved sulfate solubility will allow for higher waste loadings and accelerated cleanup missions. Much of the previous work on improving sulfate retention in waste glasses has been done on an empirical basis, making it difficult to apply the findings to future waste compositions despite the large number of glass systems studied. A more fundamental, rather than empirical, model of sulfate solubility in glass, under development at Sheffield Hallam University (SHU), could provide a solution to the issues of sulfate solubility. The model uses the normalized cation field strength index as a function of glass composition to predict sulfate capacity, and has shown early success for some glass systems. The objective of the current scope is to mature the sulfate solubility model to the point where it can be used to guide glass composition development for DOE waste vitrification efforts, allowing for enhanced waste loadings and waste throughput. A series of targeted glass compositions was selected to resolve data gaps in the current model. SHU fabricated these glasses and sent samples to the Savannah River National Laboratory (SRNL) for chemical composition analysis. SHU will use the resulting data to enhance the sulfate solubility model and resolve any deficiencies. In this report, SRNL provides chemical analyses for simulated waste glasses fabricated SHU in support of sulfate solubility model development. A review of the measured compositions revealed that there are issues with the B{sub 2}O{sub 3} and Fe{sub 2}O{sub 3} concentrations missing their targeted values by a significant amount for several of the study glasses. SHU is reviewing the fabrication of these glasses and the chemicals used in batching them to identify the source of these issues. The measured sulfate concentrations were all below their targeted values. This is expected, as the targeted concentrations likely exceeded the solubility limit for sulfate in these glass compositions. Some volatilization of sulfate may also have occurred during fabrication of the glasses. Measurements of the other oxides in the study glasses were reasonably close to their targeted values

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2003

Properties of the Hermean Regolith: New Optical Reflectance Spectra, Comparison with Lunar Anorthosites and Mineralogical Modelling - 5

We present new optical (0.4-0.65 micron) spectra of Mercury and lunar pure anorthosite locations, obtained quasi-simultaneously with the Nordic Optical Telescope (NOT) in 2002. A comparative study is performed with the model of Lucey et al. between iron-poor, mature, pure anorthosite (less than 90% plagioclase feldspar) Clementine spectra from the lunar farside and a combined 0.4-1.0 micron mercurian spectrum, obtained with the NOT, calculated for standard photometric geometry. Mercury is located at more extreme locations in the Lucey ratio-reflectance diagrams than any known lunar soil, specifically with respect to the extremely iron-poor mature anorthosites. Though quantitative prediction of FeO and TiO2 abundances cannot be made without a more generally applicable model, we find qualitatively that the abundances of both these oxides must be near zero for Mercury. We utilize the theory of Hapke, with realistic photometric parameters, to model laboratory spectra of matured mineral powders and lunar soils, and remotely sensed spectra of lunar anorthosites and Mercury. An important difference between fabricated and natural powders is the high value for the internal scattering parameter necessary to interpret the spectra for the former, and the requirement of rough and non-isotropically scattering surfaces in the modelling of the latter. The mature lunar anorthosite spectra were well modelled with binary mixtures of calcic feldspars and olivines, grain sizes of 25-30 micron and a concentration of submicroscopic metallic iron (SMFe) of 0.12-0.15% in grain coatings. The mercurian spectrum is not possible to interpret from terrestrial mineral powder spectra without introducing an average particle scattering function for the bulk soil that increases in backscattering efficiency with wavelength. The observed spectrum is somewhat better predicted with binary mixture models of feldspars and pyroxenes, that single-component regoliths consisting of either albite or diopside. Correct spectral reflectance values were predicted with a concentration of 0.1 wt% SMFe in coatings of 15-30 micron sized grains. Since reasonable cosmogonical formation scenarios for Mercury, or meteoritic infall, predict iron concentrations at least this high, we draw the conclusion that the average grain size of Mercury is about a factor of two smaller than for average returned lunar soil samples. The 0.6-2.5 micron spectrum of McCord and Clark is used to further limit the possible range of mineralogical composition of Mercury. It is found that an intimately mixed and matured 3 : 1 labradorite-to-enstatite regolith composition best matches both the optical and near-infrared spectra, yielding an abundance of approx. 1.2 wt% FeO and -approx. 0 wt% TiO2.

Warell, J.↗

NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Peter A. Liever↗