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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,207 records · Page 67

A manipulator arm for zero-g simulations

A 12-ft counterbalanced Slave Manipulator Arm (SMA) was designed and fabricated to be used for resolving the questions of operational applications, capabilities, and limitations for such remote manned systems as the Payload Deployment and Retrieval Mechanism (PDRM) for the shuttle, the Free-Flying Teleoperator System, the Advanced Space Tug, and Planetary Rovers. As a developmental tool for the shuttle manipulator system (or PDRM), the SMA represents an approximate one-quarter scale working model for simulating and demonstrating payload handling, docking assistance, and satellite servicing. For the Free-Flying Teleoperator System and the Advanced Tug, the SMA provides a near full-scale developmental tool for satellite servicing, docking, and deployment/retrieval procedures, techniques, and support equipment requirements. For the Planetary Rovers, it provides an oversize developmental tool for sample handling and soil mechanics investigations. The design of the SMA was based on concepts developed for a 40-ft NASA technology arm to be used for zero-g shuttle manipulator simulations.

Brodie, S. B.↗

Nickel cadmium battery performance simulation - A means toward optimum design in satellite applications

It is noted that electrochemically based cell models can advance state-of-the-art battery prediction by allowing variations in the parameters that constitute wear-out and predict end-of-life performance. This modeling method is used as the foundation for the simulation of Ni-Cd battery performance. This simulation tool consists of a comprehensive computer model to be developed which would predict the voltage behavior of a battery under mission conditions.

Clark, K.↗

Dissertation Proposal: Innovations in Pulsed Power and Plasma Science Theory Simulation and Experiment

Pulsed power and plasma physics are topics of great study at both Sandia National Laboratories (SNL or Sandia) and the University of New Mexico (UNM). The goal of this research is to further knowledge and understanding of these fields using the resources of both SNL and UNM in three ways. The first way is through the comprehension, application, and testing of theory. Reading and analytically deriving theoretical solutions of problems both real-world and simplified will allow for a fresh perspective and the furthering of the theory. One such theory is Ottinger's generalized theory for voltage measurement in magnetically insulated transmission lines (MITLs). By working through the math, a deeper understanding of the theory is gained from which one may add more physically accurate and/or more detailed physics into the theory. Additionally, understanding the theory lays a good foundation from which one can analyze, test, and compare results to the theory in the following two ways that will advance the fields of pulsed power and plasma physics. The second way is through the modeling and simulation of real-world and simplified problems that utilize and test the afore mentioned theories. Theory can be applied to a simulation domain by using the unstructured time-domain electromagnetic (UTDEM) codes EMPHASIS and EMPIRE as well as the physical modeling software CUBIT, all of which were developed at SNL. Problems such as the modeling and design of the extended MITL on HERMES III, the understanding of space-charge-limited emission from vacuum cathodes, and the interaction between a relativistic electron beam and an ideal gas can all be modeled, simulated, and analyzed with this set of codes. Here the advantage is three-fold. Firstly, theory that describes our understanding of these problems can be put to the test and advanced through iterative simulation and analysis. Secondly, the understanding of these problems will have a positive impact on national security through the advancement of the technological capability of the United States of America. Thirdly, and not unrelated to the prior advantage, is the validation and verification of EMPIRE and EMPHASIS. This segues into the third way, which is through experiment and the comparison of experiment to simulated and theoretical results. Performing experimental comparisons completes the scientific method and grounds all of the work in reality. Being able to physically test theory and simulation is necessary for any real conclusions to be drawn. Another advantage for carrying out experimental work is to advance the physical testing capabilities of SNL. Several systems will be developed and tested through the course of this work that positively impact technological advancement of Sandia National Labs. Lastly, all of the above work will converge to yield a well-rounded perspective that ties the three categories of research together.

42 ENGINEERING↗

Particle kinetic simulation of high altitude hypervelocity flight

Rarefied flows about hypersonic vehicles entering the upper atmosphere or through nozzles expanding into a near vacuum may only be simulated accurately with a direct simulation Monte Carlo (DSMC) method. Under this grant, researchers enhanced the models employed in the DSMC method and performed simulations in support of existing NASA projects or missions. DSMC models were developed and validated for simulating rotational, vibrational, and chemical relaxation in high-temperature flows, including effects of quantized anharmonic oscillators and temperature-dependent relaxation rates. State-of-the-art advancements were made in simulating coupled vibration-dissociation recombination for post-shock flows. Models were also developed to compute vehicle surface temperatures directly in the code rather than requiring isothermal estimates. These codes were instrumental in simulating aerobraking of NASA's Magellan spacecraft during orbital maneuvers to assess heat transfer and aerodynamic properties of the delicate satellite. NASA also depended upon simulations of entry of the Galileo probe into the atmosphere of Jupiter to provide drag and flow field information essential for accurate interpretation of an onboard experiment. Finally, the codes have been used extensively to simulate expanding nozzle flows in low-power thrusters in support of propulsion activities at NASA-Lewis. Detailed comparisons between continuum calculations and DSMC results helped to quantify the limitations of continuum CFD codes in rarefied applications.

Boyd, Iain↗

Influence of NOx Chemistry on the Prediction of Natural Gas End-Gas Autoignition

Research on the influence of NOx (NO/NO2) chemistry on HC oxidation has shown that NOx plays an important role in the promotion/inhibition of HC autoignition [1-6]. Current data for n-heptane, iso-octane, ethanol, and toluene [3, 4] have shown that NO chemistry inhibits autoignition at low temperatures and concentrations. However, at medium and high temperatures and low concentrations, autoignition is promoted, decreasing the Negative Temperature Coefficient (NTC) effect. This autoignition promotion, however, becomes weaker as NO concentrations are increased. Additionally, fundamental kinetics studies have suggested that NOx chemistry also promotes the autoignition of smaller HC, such as CH4 [7-10], C2H6 [11-14], and C3H8 [15]. Additionally to the chemical kinetics studies, a growing body of evidence supports the importance of NOx chemistry on SI engine simulations [16, 17]. Foong et al. [18] suggested that the addition of NO in their models significantly improved the agreement between simulations and experiments where the onset of knock was advanced due to the presence of NO, and Morganti et al. [19] showed that NO addition in the residual-gas was necessary for their models to obtain good agreement with experimental data. Lastly, Mohr et al. [20, 21] investigated the effect of Natural Gas (NG) reactivity and EGR substitution rate and composition on homogeneous ignition delay, flame speeds, and EGAI for stoichiometric NG/oxidizer/EGR blends. They observed that the addition of EGR composed of only inert species (CO2 and Ar) suppressed homogeneous autoignition in all NG fuels tested under all conditions. However, for all NG fuels tested, increasing EGR rates with reactive species (Ar, CO2, CO, and NO) promoted homogeneous autoignition under all conditions, thus reproducing the same trends for various NG fuel compositions that were observed in other studies and fuels. For this reason, a study is being conducted to analyze the effects of NOx chemistry on the prediction of NG/air/EGR homogeneous autoignition. This study has been divided into two tasks. First, the addition of NOx chemistry to the ARIES82 mechanism [20] is being validated using homogeneous ignition delay data collected by Mohr [20, 21]. Second, once the new modified mechanism with NOx reactions has been validated, it will be employed on engine multi-dimensional modeling presented in [22, 23] to analyze the influence of NOx chemistry on NG EGAI. Results thus far have shown that homogeneous ignition delay calculations are sensitive to NOx chemistry, where the modified mechanisms captured well all trends and closely matched the homogeneous ignition delays observed by Mohr et al. Also, the results in this work suggest that NOx chemistry is necessary to correctly capture the trends in NG homogeneous autoignition when EGR with reactive species is used since the opposite behavior is observed when only inert species are considered for the EGR composition.

03 NATURAL GAS↗

Ideal conductor/dielectric model (ICDM): A generalized technique to correct for finite-size effects in molecular simulations of hindered ion transport

Molecular simulations serve as indispensable tools for investigating the kinetics and elucidating the mechanism of hindered ion transport across nanoporous membranes. In particular, recent advancements in advanced sampling techniques have made it possible to access translocation timescales spanning several orders of magnitude. In our prior study [Shoemaker et al., J. Chem. Theory Comput. 18, 7142 (2022)], we identified significant finite size artifacts in simulations of pressure-driven hindered ion transport through nanoporous graphitic membranes. We introduced the ideal conductor model, which effectively corrects for such artifacts by assuming the feed to be an ideal conductor. In the present work, we introduce the ideal conductor dielectric model (Icdm), a generalization of our earlier model, which accounts for the dielectric properties of both the membrane and the filtrate. Using the Icdm model substantially enhances the agreement among corrected free energy profiles obtained from systems of varying sizes, with notable improvements observed in regions proximate to the pore exit. Moreover, the model has the capability to consider secondary ion passage events, including the transport of a co-ion subsequent to the traversal of a counter-ion, a feature that is absent in our original model. We also investigate the sensitivity of the new model to various implementation details. The Icdm model offers a universally applicable framework for addressing finite size artifacts in molecular simulations of ion transport. It stands as a significant advancement in our quest to use molecular simulations to comprehensively understand and manipulate ion transport processes through nanoporous membranes.

Chemistry↗

Comparisons of Nodal diffusion and whole-core transport methods for multiple cycles of a small Light water reacto

As part of a cooperative research and development agreement between the US department of Energy's Oak Ridge National Laboratory and Holtec International subsidiary SMR LLC, core simulator models of the SMR-160, a light water-cooled and -moderated, natural circulation, small modular reactor, were developed and compared. The model results indicate pin-by-pin power histories, critical boron concentration, and other key performance indicators useful for developing multi-cycle core loading patterns. One model uses industry standard nodal methods with a simple thermal-hydraulics solution, and the other uses an advanced deterministic neutronics solver with a coupled subchannel calculation. The goals of the comparison are to provide the reactor designer with a detailed and coupled core physics reference solution, inform the reactor designer of nodal model best practices based on the code-to-code comparison, and set up a workflow for performing subsequent detailed core simulator calculations. The results of this work will be used in the development of coupled neutronic, thermal hydraulic, and fuel performance models for advanced analysis of the SMR-160. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

MCNPX Cosmic Ray Shielding Calculations with the NORMAN Phantom Model

The United States is planning manned lunar and interplanetary missions in the coming years. Shielding from cosmic rays is a critical aspect of manned spaceflight. These ventures will present exposure issues involving the interplanetary Galactic Cosmic Ray (GCR) environment. GCRs are comprised primarily of protons (approx.84.5%) and alpha-particles (approx.14.7%), while the remainder is comprised of massive, highly energetic nuclei. The National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has commissioned a joint study with Los Alamos National Laboratory (LANL) to investigate the interaction of the GCR environment with humans using high-fidelity, state-of-the-art computer simulations. The simulations involve shielding and dose calculations in order to assess radiation effects in various organs. The simulations are being conducted using high-resolution voxel-phantom models and the MCNPX[1] Monte Carlo radiation-transport code. Recent advances in MCNPX physics packages now enable simulated transport over 2200 types of ions of widely varying energies in large, intricate geometries. We report here initial results obtained using a GCR spectrum and a NORMAN[3] phantom.

James, Michael R.↗

Simulating High Energy Dynamic Impact of IM7/PEKK Continuous Fiber Laminated Thermoplastic Composite using Open Hole Coupon Experiments

The use of advanced thermoplastic composites (TPC) for structural applications in the aerospace and automotive industries has grown increasingly popular due to their high performance, high manufactured part output, and sustainability. Enhancing verification simulations of the progressive failure in TPCs at the coupon scale is needed to better validate advanced composite material models at larger length scales, such as element level panels. MAT_213, a tabulated composite material model, has been applied to simulate high velocity dynamic impact (HEDI) and is integrated in the LS-DYNA explicit finite element (FE) software. Previous efforts using MAT_213 have calibrated HEDI simulated failures with experimental data. Traditionally simulations have relied on a structured mesh to represent quasi-isotropic panels. For this study, a continuous fiber unidirectional tape, IM7/PEKK, was analyzed through a series of verification studies of notched laminate coupons, then validation analyses of quasi-isotropic panels under HEDI were compared with experimental data. Experiments using unidirectional TPC were performed to obtain tabulated stress vs strain curves using Digital Image Correlation (DIC) for input into MAT_213. Next, notched coupon experiments were used as an intermediate step to calibrate the damage and failure behavior in MAT_213. Lastly, investigations into differences between HEDI simulations using a fiber aligned mesh were compared with experimental failure patterns and damage sizes. The use of experimentally generated material behavior along with selective mesh layout improved HEDI predictions with minimal material parameter calibration.

Polymer matrix composites↗

Observing and modeling the effects of production infrastructure in electromagnetic surveys

Electromagnetic (EM) methods are among the original techniques for subsurface characterization in exploration geophysics because of their particular sensitivity to the earth electrical conductivity, a physical property of rocks distinct yet complementary to density, magnetization, and strength. However, this unique ability also makes them sensitive to metallic artifacts — infrastructure such as pipes, cables, and other forms of cultural clutter — the EM footprint of which often far exceeds their diminutive stature when compared to that of bulk rock itself. In the hunt for buried treasure or unexploded ordnance, this is an advantage; in the long-term monitoring of mature oil fields after decades of production, it is quite troublesome indeed. In this study we consider the latter through the lens of an evolving energy industry landscape in which the traditional methods of EM characterization for the exploration geophysicist are applied toward emergent problems in well-casing integrity, carbon capture and storage, and overall situational awareness in the oil field. We introduce case studies from these exemplars, showing how signals from metallic artifacts can dominate those from the target itself and impose significant burdens on the requisite simulation complexity. Furthermore, we show how recent advances in numerical methods mitigate the computational explosivity of infrastructure modeling, providing feasible and real-time analysis tools for the desktop geophysicist. Lastly, we demonstrate through comparison of field data and simulation results that incorporation of infrastructure into the analysis of such geophysical data is, in a growing number of cases, a requisite but now manageable step.

58 GEOSCIENCES↗

Large Eddy Simulations and Turbulence Modeling for Film Cooling

The objective of the research is to perform Direct Numerical Simulations (DNS) and Large Eddy Simulations (LES) for film cooling process, and to evaluate and improve advanced forms of the two equation turbulence models for turbine blade surface flow analysis. The DNS/LES were used to resolve the large eddies within the flow field near the coolant jet location. The work involved code development and applications of the codes developed to the film cooling problems. Five different codes were developed and utilized to perform this research. This report presented a summary of the development of the codes and their applications to analyze the turbulence properties at locations near coolant injection holes.

Acharya, Sumanta↗

The Fission Accelerated Steady State Test (FAST) -- A Revised Capsule Design for the Accelerated Testing of Advanced Reactor Fuels

In an effort to improve the development and testing of novel nuclear fuels, a detailed evaluation on reducing the size of fuel specimens for irradiation has been performed. Theoretically speaking, reducing the fuels diameter and incorporating an inner capsule while maintaining the original outside diameter of the experiment significantly reduces the experiment’s sensitivity to fabrication tolerances and drastically reduces the time necessary to reach a desired fuel burnup; both of which improve the cost and schedule associated with the fuel testing. Simulations of this reduced diameter, double encapsulated concept have been performed using Abaqus, MCNP, and ORIGEN. The results of the Abaqus simulations are beyond the scope of this summary and will not be presented herein. For results of these Abaqus simulations, see Beausoleil [2]. The models were tested using various parameters and design deviations which were then compared to the original Advanced Fuels Campaign (AFC) designs. The results of these simulations confirmed that the introduction of a second capsule coupled to a reduction in the fuel pin diameter significantly reduces the experiment’s sensitivity to fabrication tolerances and reduces the time to reach a desired burnup by nearly an order of magnitude. The original AFC design requires approximately 11.7 years to reach 30 Atom % Heavy Metal (at% HM) burnup. A burnup of 30 at% HM can be reached in approximately 2.5 to 3.5 years (irradiation position dependent) with a fuel diameter ½ (~0.097 in. diameter) that of the original AFC design. An added benefit to the fuel pin diameter reduction is that more specimens can be irradiated in any given cycle. Essentially, significantly more specimens can be tested and incur more burnup over a given operating cycle relative to the AFC design. This allows the development of a large test matrix of samples with rapid throughput in ATR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Mathematical model for lift/cruise fan V/STOL aircraft simulator programming data

Simulation data are reported for the purpose of programming the flight simulator for advanced aircraft for tests of the lift/cruise fan V/STOL Research Technology Aircraft. These simulation tests are to provide insight into problem areas which are encountered in operational use of the aircraft. A mathematical model is defined in sufficient detail to represent all the necessary pertinent aircraft and system characteristics. The model includes the capability to simulate two basic versions of an aircraft propulsion system: (1) the gas coupled configuration which uses insulated air ducts to transmit power between gas generators and fans in the form of high energy engine exhaust and (2) the mechanically coupled power system which uses shafts, clutches, and gearboxes for power transmittal. Both configurations are modeled such that the simulation can include vertical as well as rolling takeoff and landing, hover, powered lift flight, aerodynamic flight, and the transition between powered lift and aerodynamic flight.

Bland, M. P.↗

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

Diffusion model approach to simulating electron-proton scattering events

Generative artificial intelligence is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for simulating electron-proton collisions relevant to experiments like the Continuous Electron Beam Accelerator Facility and the future Electron-Ion Collider (EIC). These experiments play a critical role in advancing our understanding of nucleons and nuclei in terms of quark and gluon degrees of freedom. The use of generative models for simulating collider events faces several challenges such as the sparsity of the data, the presence of global or eventwide constraints, and steeply falling particle distributions. In this work, we focus on the implementation of diffusion models for the simulation of electron-proton scattering events at EIC energies. Our results demonstrate that diffusion models can reproduce relevant observables such as momentum distributions and correlations of particles, momentum sum rules, and the leading electron kinematics, all of which are of particular interest in electron-proton collisions. Although the sampling process is relatively slow compared to other machine-learning architectures, we find diffusion models can generate high-quality samples. We foresee various applications of our work including inference for nuclear structure, interpretable generative machine learning, and searches of physics beyond the Standard Model. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗

Final Report. Coupled simulations of Antarctic Ice-sheet/ocean interactions using POP and CISM

The project performed under this award, referred to from here on as CLARION (CoupLed simulations of Antarctic Ice-sheet/Ocean iNteractions), included important advances in two models of ice sheet and ocean interactions. Despite its short duration (one year), the project made significant progress on its three major foci. First, together with collaborator Daniel Martin at Lawrence Berkeley National Laboratory (LBNL), I developed the POPSICLES coupled ice sheet-ocean model to the point where it could perform a number of pan-Antarctic simulations under various forcing conditions. The results were presented at a number of major conferences and workshops worldwide, and are currently being incorporated into two manuscripts in preparation.

54 ENVIRONMENTAL SCIENCES↗

Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models

In this study, computational models have become increasingly used as part of modeling, predicting, and understanding how infectious diseases spread within large populations. These models can be broadly classified into differential equation-based models (EBM) and agent-based models (ABM). Both types of models are central in aiding public health officials design intervention strategies in case of large epidemic outbreaks. We examine these models in the context of illuminating their hidden assumptions and the impact these may have on the model outcomes. Very few ABM/EBMs are evaluated for their suitability to address a particular public health concern, and drawing relevant conclusions about their suitability requires reliable and relevant information regarding the different modeling strategies and associated assumptions. Hence, there is a need to determine how the different modeling strategies, choices of various parameters, and the resolution of information for EBMs and ABMs affect outcomes, including predictions of disease spread. In this study, we present a quantitative analysis of how the selection of model types (i.e., EBM vs. ABM), the underlying assumptions that are enforced by model types to model the disease propagation process, and the choice of time advance (continuous vs. discrete) affect the overall outcomes of modeling disease spread. Our study reveals that the magnitude and velocity of the simulated epidemic depends critically on the selection of modeling principles, various assumptions of disease process, and the choice of time advance.

60 APPLIED LIFE SCIENCES↗