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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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NASA NTRS2011

ATHLETE: A Cargo-Handling Vehicle for Solar System Exploration

As part of the NASA Exploration Technology Development Program, the Jet Propulsion Laboratory is developing a vehicle called ATHLETE: the All-Terrain Hex-Limbed Extra-Terrestrial Explorer. Each vehicle is based on six wheels at the ends of six multi-degree-of-freedom limbs. Because each limb has enough degrees of freedom for use as a general-purpose leg, the wheels can be locked and used as feet to walk out of excessively soft or other extreme terrain. Since the vehicle has this alternative mode of traversing through or at least out of extreme terrain, the wheels and wheel actuators can be sized for nominal terrain. There are substantial mass savings in the wheel and wheel actuators associated with designing for nominal instead of extreme terrain. These mass savings are comparable-to or larger-than the extra mass associated with the articulated limbs. As a result, the entire mobility system, including wheels and limbs, can be about 25% lighter than a conventional mobility chassis. A side benefit of this approach is that each limb has sufficient degrees-of-freedom to use as a general-purpose manipulator (hence the name "limb" instead of "leg"). Our prototype ATHLETE vehicles have quick-disconnect tool adapters on the limbs that allow tools to be drawn out of a "tool belt" and maneuvered by the limb. A power-take-off from the wheel actuates the tools, so that they can take advantage of the 1+ horsepower motor in each wheel to enable drilling, gripping or other power-tool functions. Architectural studies have indicated that one useful role for ATHLETE in planetary (moon or Mars) exploration is to "walk" cargo off the payload deck of a lander and transport it across the surface. Recent architectural approaches are focused on the concept that the lander descent stage will use liquid hydrogen as a propellant. This is the highest performance chemical fuel, but it requires very large tanks. A natural geometry for the lander is to have a single throttleable rocket engine on the centerline at the bottom, and to have the propellant tanks arranged as compactly as possible around and above that engine, with nearly-straight structural load paths that carry the heavy LO2 tanks as well as the ascent stage or cargo on a top deck. (The requirement for exactly one descent engine stems from the need to avoid symmetry planes in the exhaust plume that can entrain surface particles and loft them up into the system at hypervelocity.) This geometry is especially attractive since abort considerations drive the ascent stage to have as much open space around it as possible, in case the ascent stage needs to fire away from an out-of-control descent stage. These considerations lead to a configuration where the cargo deck of the lander is relatively high off the ground (over 6 meters in current concepts, using a 10-meter diameter launch shroud). These considerations have led some observers to presume that there is a "lander offloading problem". ATHLETE has been demonstrated as a solution to this problem, walking cargo off the high deck. This paper describes the applicability of the ATHLETE concept to exploration of the moon, Mars and even to Near- Earth Objects. Recent field test results for long-range traverse are described, along with plans for testing in the simulated microgravity environment of a NEO.

Space Robotics↗
DOE OSTI2023

Phase-Field Modeling of Materials Interfaces and Nanostructures

Nanostructured materials offer unique properties for a wide range of energy applications. Among various known processing methods, liquid metal dealloying (LMD)—the selective dissolution of a base alloy element into a metallic melt—has emerged as a powerful technique to produce a new class of nano-/meso-scale open porous and bicontinuous composite structures with ultra-high interfacial area. LMD has recently been complemented by the advent of vapor phase dealloying (VPD), a novel technique that exploits the selective evaporation of one element from a parent alloy containing elements with very different vapor pressures, thereby enabling to fabricate open nanoporous structures of various elements from less-noble metals to inorganic elements regardless of their chemical activity without requiring high LMD temperatures and chemical etching. Together LMD and VPD have greatly expanded the scope of dealloying techniques, limited by traditional electrochemical means to noble metals, and boosted the design of new functional and structural materials that combine a wide variety of elements. Topologically-connected open porous structures with ultra-high surface area allow mass transport within the structure while preserving structural integrity, enabling them to serve as catalysts, fuel cells, supercapacitors, or high-capacity battery materials. Bicontinuous composite structures in turn can display high strength and high ductility or superior radiation-damage resistance due to the ultra-high interface area between interpenetrating solid phases. This research program makes use of state-of-the-art computational methods to understand at a basic level the self-organizing dealloying process with main focus on dealloying kinetics and interfacial pattern formation at the dealloying front controlling initial structure size, topology, and phase compositions. Phase-field simulation studies of LMD focus on solid solutions, line compounds, and intermetallic systems that can form ternary composites by nucleation and growth of a new phase. Studies of VPD employ phase-field modeling and a hybrid method combining a kinetic Monte Carlo (KMC) model of evaporation and surface diffusion with molecular dynamics for vapor-phase transport inside nanopores. Simulations explore mechanisms of interface- and diffusion-controlled dealloying kinetics, both observed in VPD but not fundamentally understood. In addition, our newly developed multi-physics phase-field approach of large-volume-change phase transformations is being used to model novel 3D anode geometries based on dealloyed nanoporous structures including novel sandwiched graphene/Si/silica for highrate Li ion battery. Those studies are aimed at elucidating geometric design principles that improve mechanical stability. We expect this research to enhance the capability to tailor nano-/mesoscale structures for a wide range of energy-related materials applications and to yield further advances in computational methodologies that benefit a broad materials research community.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Deep Eutectic Solvents: A Review of Fundamentals and Applications

Deep eutectic solvents (DESs) are an emerging class of mixtures characterized by significant depressions in melting points compared to those of the neat constituent components. These green materials are promising for applications as inexpensive ’designer’ solvents exhibiting a host of tunable physicochemical properties. Here, a detailed review of the current literature reveals the lack of predictive understanding of the microscopic mechanisms that govern the structure-property relationships in this class of solvents. Complex hydrogen bonding behavior is postulated as the root cause of their melt-ing point depressions and physicochemical properties; to understand these hydrogen bonded networks, it is imperative to study these systems as dynamic entities using both simulations and experiments. This review emphasizes recent research efforts in order to elucidate the next steps needed to develop a fundamental framework for understanding DESs. It covers recent developments in DES research, frames outstanding scientific questions, and identifies gainful research thrusts that would advance the field towards predictive models and fundamental understanding of these solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Ab Initio Molecular Dynamics. 1. Theory, Algorithm, and Performance

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions (MLWFs)) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems of interest at the hybrid DFT level. We focus our theoretical discussion on the integration of this approach into the framework of Car–Parrinello AIMD, and highlight the central role played by the MLWF-product potential (i.e., the solution of Poisson’s equation for each corresponding MLWF-product density) in the evaluation of the EXX energy and wave function forces. We then provide a comprehensive description of the exx algorithm implemented in the open-source Quantum ESPRESSO program, which employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize the high-performance computing (HPC) resources available on current- and next-generation supercomputer architectures. Furthermore, this is followed by a critical assessment of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach when AIMD simulations of liquid water are performed in the canonical (NVT) ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT-based AIMD simulations of condensed-phase systems containing 500–1000 atoms (e.g., (H₂O)₂₅₆) with a wall time cost that is comparable to that of semilocal DFT. In doing so, exx takes us one step closer to routinely performing AIMD simulations of complex and large-scale condensed-phase systems for sufficiently long time scales at the hybrid DFT level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Guo, T. H.↗
DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗
DOE OSTI2018

Mechanistic View of hnRNPA2 Low-Complexity Domain Structure, Interactions, and Phase Separation Altered by Mutation and Arginine Methylation

hnRNPA2, a component of RNA-processing membraneless organelles, forms inclusions when mutatedin a syndrome characterized by the degeneration of neurons (bearing features of amyotrophic lateral sclerosis [ALS] and frontotemporal dementia), muscle,and bone. In this work we provide a unified structural view of hnRNPA2 self-assembly, aggregation, and interaction and the distinct effects of small chemical changes—disease mutations and arginine methylation—on these assemblies. The hnRNPA2 low-complexity (LC) domain is compact and intrinsically disordered as a monomer, retaining predominant disorder in a liquid-liquid phase-separated form. Disease mutations D290V and P298L induce aggregation by enhancing and extending, respectively, the aggregation-prone region. Co-aggregating in disease inclusions, hnRNPA2 LC directly interacts with and induces phase separation of TDP-43. Conversely, arginine methylation reduces hnRNPA2 phase separation, disrupting arginine-mediated contacts. These results highlight the mechanistic role of specific LC domain interactions and modifications conserved across many hnRNP family members but altered by aggregation-causing pathological mutations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

Pattern recognition is the identification of structures and regularities in data. In high energy physics, it is a vital stage in the reconstruction of events recorded by fine-granularity detectors. The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. Whereas the human brain excels at identifying features in the recorded events, it is a significant challenge to develop an automated solution. The Pandora Software Development Kit (SDK) provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. In particular, it promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each aim to address a specific task in a particular topology; a series of many tens of algorithms then carefully build-up a picture of the event and, together, provide a robust automated pattern recognition solution. Building on successful use of the Pandora SDK for pattern recognition at collider experiments, a sophisticated chain of algorithms has been created to perform pattern recognition for neutrino experiments utilising LAr TPCs like MicroBooNE. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction. In this document, we present details of the Pandora pattern recognition algorithms used to reconstruct cosmic-ray and neutrino events in LAr TPCs. We also present metrics that assess the current reconstruction performance using simulated data from MicroBooNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Assessment of MOOSE-Based Tools for Calculating Radial Core Expansion

Radial core expansion in liquid-metal cooled fast reactor systems is a well-known phenomenon that produces strong reactivity feedback effects. An inherently safe reactor design takes advantage of negative reactivity feedback in accident scenarios by utilizing a core restraint system which produces a bowed shape that allows for radial expansion of the fuel regions. Detailed modeling and simulation of core radial expansion itself as well as subsequent reactivity feedback is a challenging task involving contact of many fuel assembly elements and physics feedback from neutronics, thermal hydraulics, and thermal mechanical response. A variety of physics codes have been developed to model aspects of radial core expansion but in general invoke geometrical or physics approximations. No code system currently exists which tightly and robustly couples these physics with enough detail to fully resolve the complex core radial expansion reactivity feedback effects. The future availability of such a code system is of vital importance to fully understanding the reactivity feedback effects that occur due to radial expansion, and consequently to optimizing the design of the core restraint system. A high-fidelity code will also be used to benchmark existing lower fidelity, faster running models to understand their benefits, limitations, and range of applications. A code development path using MOOSE-based tools is proposed in order to leverage the detailed geometry capabilities and natural tight coupling and robustness of MOOSE-based applications for modeling this complex phenomena. While simulation of the full phenomenon involves several physics, an assessment has been initiated on the capabilities and readiness of the currently available Tensor Mechanics module within MOOSE for calculation of the structural mechanical responses which occur within the reactor core. This report focuses on modeling the force-deformation response which mimics the physics of a duct contact deformation, as well as differential thermal expansion which produces a thermal bowed shaped for the fuel assemblies in a core. Simple examples were initially performed such as simple supported beam bending under load. The complexity of examples was progressively increased to better mimic the duct behavior by including a differential thermal example and inclusion of hexagonal cross-sections in the geometry. Further assessment of the structural mechanical response simulation capability is still required for modeling duct contact interactions and irradiation creep and swelling. Companion thermal hydraulic and neutronics assessments will also be required; these activities are planned for future years. Finally, integration of the multiple physics components through MOOSE is required to predict the core radial expansion and subsequent feedback effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Theory of the spatial transfer of interface-nucleated changes of dynamical constraints and its consequences in glass-forming films

We formulate a new theory for how caging constraints in glass-forming liquids at a surface or interface are modified and then spatially transferred, in a layer-by-layer bootstrapped manner, into the film interior in the context of the dynamic free energy concept of the Nonlinear Langevin Equation (NLE) theory approach. The dynamic free energy at any mean location (cage center) involves contributions from two adjacent layers where confining forces are not the same. At the most fundamental level of the theory, the caging component of the dynamic free energy varies essentially exponentially with distance from the interface, saturating deep enough into the film with a correlation length of modest size and weak sensitivity to the thermodynamic state. This imparts a roughly exponential spatial variation of all the key features of the dynamic free energy required to compute gradients of dynamical quantities including the localization length, jump distance, cage barrier, collective elastic barrier, and alpha relaxation time. The spatial gradients are entirely of dynamical, not structural or thermodynamic, origin. The theory is implemented for the hard sphere fluid and diverse interfaces which can be a vapor, a rough pinned particle solid, a vibrating (softened) pinned particle solid, or a smooth hard wall. Their basic description at the level of the spatially heterogeneous dynamic free energy is identical, with the crucial difference arising from the first layer where dynamical constraints can be weakened, softened, or hardly changed depending on the specific interface. Numerical calculations establish the spatial dependence and fluid volume fraction sensitivity of the key dynamical property gradients for five different model interfaces. A comparison of the theoretical predictions for the dynamic localization length and glassy modulus with simulations and experiments for systems with a vapor interface reveals good agreement. Finally, the present advance sets the stage for using the Elastically Collective NLE theory to make quantitative predictions for the alpha relaxation time gradient, decoupling phenomena, T g gradient, and many film-averaged properties of both model and experimental (colloids, molecules, and polymers) systems with diverse interfaces and chemical makeup.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Progress in Spacecraft Environment Interactions: International Space Station (ISS) Development and Operations

The set of spacecraft interactions with the space flight environment that have produced the largest impacts on the design, verification, and operation of the International Space Station (ISS) Program during the May 2000 to May 2007 time frame are the focus of this paper. In-flight data, flight crew observations, and the results of ground-based test and analysis directly supporting programmatic and operational decision-making are reported as are the analysis and simulation efforts that have led to new knowledge and capabilities supporting current and future space explorations programs. The specific spacecraft-environment interactions that have had the greatest impact on ISS Program activities during the first several years of flight are: 1) spacecraft charging, 2) micrometeoroids and orbital debris effects, 3) ionizing radiation (both total dose to materials and single event effects [SEE] on avionics), 4) hypergolic rocket engine plume impingement effects, 5) venting/dumping of liquids, 6) spacecraft contamination effects, 7) neutral atmosphere and atomic oxygen effects, 8) satellite drag effects, and 9) solar ultraviolet effects. Orbital inclination (51.6deg) and altitude (nominally between 350 km and 460 km) determine the set of natural environment factors affecting the performance and reliability of materials and systems on ISS. ISS operates in the F2 region of Earth s ionosphere in well-defined fluxes of atomic oxygen, other ionospheric plasma species, solar UV, VUV, and x-ray radiation as well as galactic cosmic rays, trapped radiation, and solar cosmic rays. The micrometeoroid and orbital debris environment is an important determinant of spacecraft design and operations in any orbital inclination. The induced environment results from ISS interactions with the natural environment as well as environmental factors produced by ISS itself and visiting vehicles. Examples include ram-wake effects, hypergolic thruster plume impingement, materials out-gassing, venting and dumping of fluids, and specific photovoltaic (PV) power system interactions with the ionospheric plasma. Vehicle size (L) and velocity (v), combined with the magnitude and direction of the geomagnetic field (B) produce operationally significant magnetic induction voltages (VxB.L) in ISS conducting structure during high latitude flight (>+/- 45deg) during each orbit. In addition, ISS is a large vehicle and produces a deep wake structure from which both ionospheric plasma and neutrals species are largely excluded. ISS must fly in a very limited number of approved flight attitudes, so that exposure of a particular material or system to environmental factors depends upon: 1) location on ISS, 2) ISS flight configuration, 3) ISS flight attitude, and 4) variation of solar exposure (Beta angle), and hence thermal environment, with time. Finally, an induced ionizing radiation environment is produced by trapped radiation and solar/cosmic ray interactions with the relatively massive ISS structural shielding.

Koontz, Steve↗
NASA NTRS2002

Predictions for Radiation Shielding Materials

Radiation from galactic cosmic rays (GCR) and solar particle events (SPE) is a serious hazard to humans and electronic instruments during space travel, particularly on prolonged missions outside the Earth s magnetic fields. Galactic cosmic radiation (GCR) is composed of approx. 98% nucleons and approx. 2% electrons and positrons. Although cosmic ray heavy ions are 1-2% of the fluence, these energetic heavy nuclei (HZE) contribute 50% of the long-term dose. These unusually high specific ionizations pose a significant health hazard acting as carcinogens and also causing microelectronics damage inside spacecraft and high-flying aircraft. These HZE ions are of concern for radiation protection and radiation shielding technology, because gross rearrangements and mutations and deletions in DNA are expected. Calculations have shown that HZE particles have a strong preference for interaction with light nuclei. The best shield for this radiation would be liquid hydrogen, which is totally impractical. For this reason, hydrogen-containing polymers make the most effective practical shields. Shielding is required during missions in Earth orbit and possibly for frequent flying at high altitude because of the broad GCR spectrum and during a passage into deep space and LunarMars habitation because of the protracted exposure encountered on a long space mission. An additional hazard comes from solar particle events (SPEs) which are mostly energetic protons that can produce heavy ion secondaries as well as neutrons in materials. These events occur at unpredictable times and can deliver a potentially lethal dose within several hours to an unshielded human. Radiation protection for humans requires safety in short-term missions and maintaining career exposure limits within acceptable levels on future long-term exploration missions. The selection of shield materials can alter the protection of humans by an order of magnitude. If improperly selected, shielding materials can actually increase radiation damage due to penetration properties and nuclear fragmentation. Protecting space-borne microelectronics from single event upsets (SEUs) by transmitted radiation will benefit system reliability and system design cost by using optimal shield materials. Long-term missions on the surface of the Moon or Mars will require the construction of habitats to protect humans during their stay. One approach to the construction is to make structural materials from lunar or Martian regolith using a polymeric material as a binder. The hydrogen-containing polymers are considerably more effective for radiation protection than the regolith, but the combination minimizes the amount of polymer to be transported. We have made composites of simulated lunar regolith with two different polymers, LaRC-SI, a high-performance polyimide thermoset, and polyethylene, a thermoplastic.

Kiefer, Richard L.↗
DOE OSTI2016

MELCOR/CONTAIN LMR Implementation Report - FY16 Progress.

This report describes the progress of the CONTAIN - LMR sodium physics and chemistry models to be implemented in MELCOR 2.1. In the past three years , the implementation included the addition of sodium equations of state and sodium properties from two different sources. The first source is based on the previous work done by Idaho National Laboratory by modifying MELCOR to include liquid lithium equation of state as a working fluid to model the nuclear fusion safety research. The second source uses properties generated for the SIMMER code. The implemented modeling has been tested and results are reported in this document. In addition, the CONTAIN - LMR code was derived from an early version of the CONTAIN code, and many physical models that were developed since this early version of CONTAIN are not available in this early code version. Therefore, CONTAIN 2 has been updated with the sodium models in CONTAIN - LMR as CONTAIN2 - LMR, which may be used to provide code-to-code comparison with CONTAIN - LMR and MELCOR when the sodium chemistry models from CONTAIN - LMR have been completed. Both the spray fire and pool fire chemistry routines from CONTAIN - LMR have been integrated into MELCOR 2.1, and debugging and testing are in progress. Because MELCOR only models the equation of state for liquid and gas phases of the coolant, a modeling gap still exists when dealing with experiments or accident conditions that take place when the ambient temperature is below the freezing point of sodium. An alternative method is under investigation to overcome this gap . We are no longer working on the separate branch from the main branch of MELCOR 2.1 since the major modeling of MELCOR 2.1 has been completed. At the current stage, the newly implemented sodium chemistry models will be a part of the main MELCOR release version (MELCOR 2.2). This report will discuss the accomplishments and issues relating to the implementation. Also, we will report on the planned completion of all remaining tasks in the upcoming FY2017, including the atmospheric chemistry model and sodium - concrete interaction model implementation .

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Oscillation-like diffusion of two-dimensional liquid dusty plasmas on one-dimensional periodic substrates with varied widths

The long-time diffusion of two-dimensional dusty plasmas on a one-dimensional periodic substrate with varying widths is investigated using Langevin dynamical simulations. When the substrate is narrow and the dust particles form a single row, the diffusion is the smallest in both directions. In this study, we find that as the substrate width gradually increases to twice its initial value, the long-time diffusion of the two-dimensional dusty plasmas first increases, then decreases, and finally increases again, giving an oscillation-like diffusion with varying substrate widths. When the width increases to a specific value, the dust particles within each potential well arrange themselves in a stable zigzag pattern, greatly reducing the diffusion and leading to the observed oscillation in the diffusion with the increase in the width. In addition, the long-time oscillation-like diffusion is consistent with the number of dust particles that are hopping across the potential wells of the substrate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Liquid-like dynamics in a solid-state lithium electrolyte

Superionic materials represent a regime intermediate between the crystalline and liquid states of matter. Despite the considerable interest in potential applications for solid-state batteries or thermoelectric devices, it remains unclear whether the fast ionic diffusion observed in superionic materials reflects liquid-like dynamics or whether the hops of mobile ions are inherently coupled to more conventional lattice phonons. Here we reveal a crossover from crystalline vibrations to relaxational dynamics of ionic diffusion in the superionic compound Li 6 PS 5 Cl, a candidate solid-state electrolyte. By combining inelastic and quasi-elastic neutron-scattering measurements with first-principles-based machine-learned molecular dynamics simulations, we found that the vibrational density of states in the superionic state strongly deviates from the quadratic behaviour expected from the Debye law of lattice dynamics. The superionic dynamics emerges from overdamped phonon quasiparticles to give rise to a linear density of states characteristic of instantaneous normal modes in the liquid state. Further, we showed that the coupling of lattice phonons with a dynamic breathing of the Li+ diffusion bottleneck enables an order-of-magnitude increase in diffusivity. Thus, our results shed insights into superionics for future energy storage and conversion technologies.

25 ENERGY STORAGE↗
DOE OSTI2016

Using ARM Measurements to Understand and Reduce the Double ITCZ Biases in the Community Atmospheric Model

1. Understanding of the observed variability of ITCZ in the equatorial eastern Pacific. The annual mean precipitation in the eastern Pacific has a maximum zonal band north of the equator in the ITCZ where the maximum SST is located. During the boreal spring (referring to February, March, and April throughout the present paper), because of the accumulated solar radiation heating and oceanic heat transport, a secondary maximum of SST exists in the southeastern equatorial Pacific. Associated with this warm SST is also a seasonal transitional maximum of precipitation in the same region in boreal spring, exhibited as a weak double ITCZ pattern in the equatorial eastern Pacific. This climatological seasonal variation, however, varies greatly from year to year: double ITCZ in the boreal spring occurs in some years but not in other years; when there a single ITCZ, it can appear either north, south or at the equator. Understanding this observed variability is critical to find the ultimate cause of the double ITCZ in climate models. Seasonal variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have found that in the region where spurious ITCZ in models occurs, there is a “seasonal cloud transition” — from stratocumulus to shallow cumulus and eventually to deep convection —in the South Equatorial Pacific (SEP) from September to April that is similar to the spatial cloud transition from the California coast to the equator. This seasonal transition is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence. This finding of seasonal cloud transition points to the same source of model errors in the ITCZ simulations as in simulation of stratocumulus-cumulus-deep convection transition. It provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double Inter-tropical Convergence Zone (ITCZ) in most models. This work is recently published in Yu et al. (2016). Interannual variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have characterized the interannual variation of boreal spring precipitation in the eastern tropical Pacific and found the cause of the observed interannual variability. We have shown that ITCZ in this region can occur as a single ITCZ along the Equator, single ITCZ north of the Equator, single ITCZ south of the Equator, and double ITCZ on both sides of the Equator. We have found that convective instability only plays a secondary role in the ITCZ interannual variability. Instead, the remote impact of the Pacific basin-wide SST on the horizontal gradient of surface pressure and wind convergence is the primary driver of this interannual variability. Results point to the need to include moisture convergence in convection schemes to improve the simulation of precipitation in the eastern tropical Pacific. This result has been recently submitted for publication (Yu and Zhang 2016). 2. Improvement of model parameterizations to reduce the double ITCZ bias We analyzed the current status of climate model performance in simulating precipitation in the equatorial Pacific. We have found that the double ITCZ bias has not been reduced in CMIP5 models relative to CMIP4 models. We have characterized the dynamic structure of the common bias by using precipitation, sea surface temperature, surface winds and sea-level. Results are published in Zhang et al. (2015): Since cumulus convection plays a significant role in the double ITCZ behavior in models, we have used measurements from ARM and other sources to carry out a systematic analysis of the roles of shallow and deep convection in the CAM. We found that in both CAM4 and CAM5, when the intensity of deep convection decreases as a result of parameterization change, the intensity of shallow convection increases, leading to very different changes in precipitation partitions but little change in the total precipitation. The different precipitation partition however can manifest themselves in other measures of model performances including temperature and humidity. This study points to the need to treat model physical parameterizations as integrated system rather than individual components. Results from this study are published in Wang and Zhang (2013). Since shallow convection interacts with the deep convection scheme and surface turbulence to trigger the double ITCZ, we studied methods to improve the shallow convection scheme in climate models. We investigated the bulk budgets of the vertical velocity and its parameterization in convective cores, convective updrafts, and clouds by using large-eddy simulation (LES) of four shallow convection cases including one from ARM. We proposed optimal forms of the Simpson and Wiggert equation to calculate the vertical velocity in bulk mass flux convection schemes for convective cores, convective updrafts, and convective clouds as parameterization schemes. The new scheme is published in Wang and Zhang (2014). By using long-term radar-based ground measurements from ARM, we derived a scale-aware inhomogeneity parameterization of cloud liquid water in climate models. We found a relationship between the inhomogeneity parameter and the model grid size as well as atmospheric stability. This relationship is implemented in the CESM to describe the subgrid-scale cloud inhomogeneity. Relative to the default CESM with the finite-volume dynamic core at 2-degree resolution, the new parameterization leads to smaller cloud inhomogeneity and larger cloud liquid-water path in high latitudes, and the opposite effect in low latitudes, with the regional impact on shortwave cloud radiation effect of up to 10 W/m 2 . This is due to both the smaller (larger) grid size in high (low) latitudes in the longitude-latitude grid setting of CESM and the more stable (unstable) atmosphere. This parameterization is expected lead to more realistic simulation of tropical precipitation in high-resolution models. Results from this study are reported in Xie and Zhang (2015).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗