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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Measurement of Shear Strain in Impact Ice Using a Modified Lap Joint Test and Digital Image Correlation

The results of ice adhesion testing efforts are typically quantified using the maximum shear stress sustained at the interface before the ice detaches from the underlying substrate. While this singular value can be useful for understanding the role icing wind tunnel conditions and substrate surface properties have on the strength of the ice-substrate interface, it does not capture the mechanical behavior of the ice during an experiment. To better understand the deformation of the ice sample and ice-substrate interface during testing, digital image correlation was applied to the lap-joint shear test methodology utilized at NASA Glenn Research Center. Preparation of the sample surface for digital image correlation, initial parsing of the correlation data, and the time synchronization of data from multiple sources are discussed. Using the directional components of deformation measured via digital image correlation, a novel approach to calculating the interfacial shear strain is presented. Results from analyzing several impact ice samples consistently reveals a non-linear response in the ice during mechanical loading which occurs prior to sample delamination, a behavior not observable in the force and displacement data gathered from the testing apparatus. Both the full and small angle forms of the engineering shear strain are evaluated, with the full shear strain form providing considerably lower noise levels. The transition of sample response from near the interface to the bulk behavior of the ice under shear loading is discussed with results from several samples being presented.

: Ice Adhesion, Digital Image Correlation, Experim↗
DOE OSTI2022

Ice-shelf ocean boundary layer dynamics from large-eddy simulations

Abstract. Small-scale turbulent flow below ice shelves is regionally isolated and difficult to measure and simulate. Yet these small-scale processes, which regulate heat and salt transfer between the ocean and ice shelves, can affect sea-level rise by altering the ability of Antarctic ice shelves to “buttress” ice flux to the ocean. In this study, we improve our understanding of turbulence below ice shelves by means of large-eddy simulations at sub-meter resolution, capturing boundary layer mixing at scales intermediate between laboratory experiments or direct numerical simulations and regional or global ocean circulation models. Our simulations feature the development of an ice-shelf ocean boundary layer through dynamic ice melting in a regime with low thermal driving, low ice-shelf basal slope, and strong shear driven by the geostrophic flow. We present a preliminary assessment of existing ice-shelf basal melt parameterizations adopted in single component or coupled ice-sheet and ocean models on the basis of a small parameter study. While the parameterized linear relationship between ice-shelf melt rate and far-field ocean temperature appears to be robust, we point out a little-considered relationship between ice-shelf basal slope and melting worthy of further study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

In situ embedment of type K sheathed thermocouples with directed energy deposition

Advanced nuclear reactor systems require new technologies for heat transfer and system monitoring. Additive manufacturing (AM) offers the design flexibility to allow in-situ sensor embedment through smart manufacturing for real-time monitoring, and performance of these systems. Here, this study focuses on experiments investigating the feasibility of in-situ sensor embedment using directed energy deposition (DED). Type K thermocouples are embedded into 316L stainless steel (SS) samples using two different configurations (e.g., exposed and embedded tips) and two designs (e.g., flush to substrate) within an AM base. Embedded sensor samples are analyzed via in-situ measurements and high-temperature performance validation tests at 350ºC and 900ºC. Temperature performance results at both temperature tests show good agreement with manufacturer specifications proving that these sensors could still capture accurate temperature readings after in-situ embedment during DED processing. An additional optimization experiment was conducted on the exposed tip configuration using a surrogate thermocouple to improve tolerances and the embedment process. Results improved tolerances, lower porosity, smaller gaps between the sensor and base, and better junction contact for the sensor. Although further optimization of this embedment strategy is necessary to improve the structural stability and tolerances within the component, this research strategy provides a proof-of-feasibility for DED embedment with commercial sheathed thermocouples. This research provides early impact on embedment of sensor for multiple materials and complex geometric components..

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Scalar Breit interaction for molecular calculations

Variational treatment of the Dirac–Coulomb–Gaunt or Dirac–Coulomb–Breit two-electron interaction at the Dirac–Hartree–Fock level is the starting point of high-accuracy four-component calculations of atomic and molecular systems. In this work, we introduce, for the first time, the scalar Hamiltonians derived from the Dirac–Coulomb–Gaunt and Dirac–Coulomb–Breit operators based on spin separation in the Pauli quaternion basis. While the widely used spin-free Dirac–Coulomb Hamiltonian includes only the direct Coulomb and exchange terms that resemble nonrelativistic two-electron interactions, the scalar Gaunt operator adds a scalar spin–spin term. The spin separation of the gauge operator gives rise to an additional scalar orbit-orbit interaction in the scalar Breit Hamiltonian. Benchmark calculations of Au n (n = 2–8) show that the scalar Dirac–Coulomb–Breit Hamiltonian can capture 99.99% of the total energy with only 10% of the computational cost when real-valued arithmetic is used, compared to the full Dirac–Coulomb–Breit Hamiltonian. In conclusion, the scalar relativistic formulation developed in this work lays the theoretical foundation for the development of high-accuracy, low-cost correlated variational relativistic many-body theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Additive Manufacturing for Propulsion Systems

Additive Manufacturing (AM) has become a prominent technology of interest for manufacturing propulsion components and gaining attention across the aerospace industry. AM is maturing at a rapid pace and providing new design opportunities, novel materials, new industries and supply chains resulting in programmatic and technical performance improvements. The successful use of AM requires a methodical and intentional approach to understanding the concept to utilization lifecycle for AM. This course will provide an overview of the various steps in AM process trades, design, build process, post-processing, certification and infusion of AM. This will provide various lessons learned and experiences that were captured in a recent AIAA textbook titled "Metal Additive Manufacturing for Propulsion Applications" by the session chairs and industry colleagues. This course will include specific liquid rocket engine component examples and that went through the AM lifecycle including hot-fire testing.

Additive Manufacturing↗
NASA NTRS1985

Low-speed experimental study of the vortex flow effects of a fighter forebody having unconventional cross-section

A low speed wind tunnel investigation is conducted for the vortex flow characteristics of a tailless fighter configuration that features full length, fuselage-blended forebody strakes. Static pressure distributions were obtained on the forebody upper surface, and six-component forces and moments were measured on the complete, 60-deg cropped delta wing-fuselage-centerline vertical fin model at angles of attack and sideslip respectively reaching 50 deg and + or - 20 deg. The surface pressure data reveal that development of concentrated vortices from the sharp edged forebody strakes occurred at moderate and high angles of attack. The blended forebody was effective in capturing the windward vortical flow up to high incidence and sideslip angles. The direct suction effect of the windward vortex on the forebody sidewall was the primary contributor to static directional stability at high angles of attack. These improvements are potentially offset, however, by reduced or unstable roll and yaw damping.

Erickson, G. E.↗
DOE OSTI2025

Improved damage tolerance of SiC-based nuclear fuel cladding with novel multi-layered SiC coating design at 1200 °C

Continuous SiC fibre reinforced SiC matrix composites (SiC f -SiC m ) with monolithic SiC outer coatings are considered as a damage-tolerant cladding design for loss of coolant accident (LOCA) conditions in light water reactors. However, monolithic SiC coatings are brittle and prone to catastrophic failure. In this study, a SiC f -SiC m cladding with a novel multi-layer SiC outer coating (11 sub-layers, ∼260 µm in total thickness) was investigated under C-ring compression at room temperature and 1200 °C in argon environment. Real-time synchrotron X-ray computed tomography (XCT) was employed to capture crack initiation and propagation processes. Compared to conventional monolithic SiC outer coatings, the multi-layer coating structure facilitated crack deflection and bifurcation enhancing its damage tolerance at both temperatures. Despite pre-existing surface cracks, claddings exhibited stable mechanical-performance at both temperatures. These initial cracks did not critically affect the failure processes as they were not aligned with the maximum stress direction. Furthermore, the microstructure, distribution of residual stresses, and local properties of individual components in the material were thoroughly characterized, and compared with open literature on conventional claddings with monolithic outer coatings. These results provide new insights into the failure mechanisms of multi-layer SiC coatings and offer guidance for the future design of accident-tolerant nuclear fuel claddings.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Seasonal and Long‐Term Groundwater Unloading in the Central Valley Modifies Crustal Stress

Abstract Changes in terrestrial water content cause elastic deformation of the Earth's crust. This deformation is thought to play a role in modulating crustal stress and seismicity in regions where large water storage fluctuations occur. Groundwater is an important component of total water storage change in California, helping to drive annual water storage fluctuations and loss during periods of drought. Here we use direct estimates of groundwater volume loss during the 2007–2010 drought in California's Central Valley obtained from high resolution Interferometric Synthetic Aperture Radar‐based vertical land motion data to investigate the effect of groundwater volume change on the evolution of the stress field. We show that GPS‐derived elastic load models may not capture the contribution of groundwater to terrestrial water loading, resulting in an underestimation of nontectonic crustal stress change. We find that groundwater unloading during the drought causes Coulomb stress change of up to 5.5 kPa and seasonal fluctuations of up to 2.6 kPa at seismogenic depth. We find that faults near the Valley show the largest stress change and the San Andreas fault experiences only ~40 Pa of Coulomb stress change over the course of a year from groundwater storage change. Annual Coulomb stress change peaks dominantly in the fall, when the groundwater level is low; however, some faults experience peak stress in the spring when groundwater levels are higher. Additionally, we find that periods of increased stress correlate with higher than average seismic moment release but are not correlated with an increase in the number of earthquakes. This indicates groundwater loading likely contributes to nontectonic loading of faults, especially near the Valley edge, but is not a dominant factor in modulation of seismicity in California because the amplitude of stress change declines rapidly with distance from the Valley. By carefully quantifying and spatially locating groundwater fluctuations, we will improve our understanding of what drives nontectonic stress and forces that modulate seismicity in California.

58 GEOSCIENCES↗
DOE OSTI2022

Automatic Generation of Event Trees and Fault Trees: A Model-Based Approach

In the past few decades, the increasing complexity of modern engineering systems has been driven by the integration of a large number of components whose operations may involve many disciplines (e.g., thermal hydraulics, plant operations, cybersecurity). Most computational tools used by industry and regulators for system safety and reliability assessments are still based on the traditional fault tree (FT) and event tree (ET) approach, which may not be able to capture complex interactions among system constituents. The use of simulation tools has widely increased in the past few decades to improve the fidelity of the reliability and safety analyses. However, the direct use of simulation tools as part of dynamic probabilistic risk assessment (DPRA) methods is not getting traction since (1) modeling the whole system under consideration with DPRA methods may be computationally expensive and unnecessary, and (2) the manual integration of DPRA models into existing state-of-practice probabilistic risk assessment models (i.e., based on FTs and ETs) can be time consuming and prone to errors. Here, in this paper we propose a procedure to overcome this limitation by presenting several algorithms designed to automatically construct subsystem ETs and FTs from DPRA methods for integration into an existing ET/FT system model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Multi-modal Approach to Understanding Degradation of Organic Photovoltaic Materials

State-of-the-art organic photovoltaic (OPV) materials are composed of complex, chemically diverse polymeric and molecular structures that form highly intricate solid-state interactions, collectively yielding exceptional tunability in performance and aesthetics. These properties are especially attractive for semitransparent power-generating windows or shades in living environments, greenhouses, or other architectural integrations. However, before such a future is realized, a broader and deeper understanding of property stability must be acquired. Stability during operating and environmental conditions is critical, namely, material color steadfastness, optoelectronic performance retention, morphological rigidity, and chemical robustness. To date, no single investigation encompasses all four distinct, yet interconnected, metrics. Here, we present a multimodal strategy that captures a dynamic and interconnected evolution of each property during the course of an accelerated photobleaching experiment. We demonstrate this approach across relevant length scales (from molecular to visual macroscale) using X-ray photoelectron spectroscopy, grazing-incidence X-ray scattering, microwave conductivity, and time-dependent photobleaching spectroscopies for two high-performance semitransparent OPV blends—PDPP4T:PC 60 BM and PDPP4T:IEICO-4F, with comparisons to the stabilities of the individual components. We present direct evidence that specific molecular acceptor (fullerene vs nonfullerene) designs and the resulting donor–acceptor interactions lead to distinctly different mechanistic routes that ultimately arrive at what is termed “OPV degradation.” We directly observe a chemical oxidation of the cyano endcaps of the IEICO-4F that coincides with a morphological change and large loss in photoconductivity while the fullerene acceptor-containing blend demonstrates a significantly greater fraction of oxygen uptake but retains 55% of the photoconductivity. Finally, this experimental roadmap provides meaningful guidance for future high-throughput, multimodal studies, benchmarking the sensitivity of the different analytical techniques for assessing stability in printable active layers, independent of complete device architectures.

14 SOLAR ENERGY↗
NASA NTRS2003

Concentration and Velocity Gradients in Fluidized Beds

In this work we focus on the height dependence of particle concentration, average velocity components, fluctuations in these velocities and, with the flow turned off, the sedimentation velocity. The latter quantities are measured using Particle Imaging Velocimetry (PIV). The PIV technique uses a 1-megapixel camera to capture two time-displaced images of particles in the bed. The depth of field of the imaging system is approximately 0.5 cm. The camera images a region with characteristic length of 2.6 cm for the small particles and 4.7 cm. for the large particles. The local direction of particle flow is determined by calculating the correlation function for sub-regions of 32 x 32 pixels. The velocity vector map is created from this correlation function using the time between images (we use 15 to 30 ms). The software is sensitive variations of 1/64th of a pixel. We produce velocity maps at various heights, each consisting of 3844 velocities. We break this map into three vertical zones for increased height information. The concentration profile is measured using an expanded (1 cm diameter) linearly polarized HeNe Laser incident on the fluidized bed. A COHU camera (gamma=1, AGC off) with a lens and a polarizer images the transmitted linearly polarized light to minimize the effects of multiply scattered light. The intensity profile (640 X 480 pixels) is well described by a Gaussian fit and the height of the Gaussian is used to characterize the concentration. This value is compared to the heights found for known concentrations. The sedimentation velocity is estimated using by imaging a region near the bottom of the bed and using PIV to measure the velocity as a function of time. With a nearly uniform concentration profile, the time can be converted to height information. The stable fluidized beds are made from large pseudo-monodisperse particles (silica spheres with radii (250-300) microns and (425-500) microns) dispersed in a glycerin/water mix. The Peclet number is sufficiently large that Brownian motion of the particles can be ignored and the Reynolds number sufficiently small that particle inertia is negligible. A packed particle bed is used to randomize and disperse the flowing fluid introduced by a peristaltic pump. The bed itself is a rectangular glass cell 8 cm wide (x), 0.8 cm deep and a height of 30.5 cm (z). The depth of field of the camera is approximately 0.5 cm so depth information is averaged. Over flow fluid is returned to the reservoir making a closed loop system. In these experiments the particles form a sediment approximately 5.7 cm high with the pump off and expand to 22 cm with the pump on. For the smaller particles the pump velocity is .5 millimeters per second and 1.1 millimeters per second for the large particles. At this concentration the bed has a very well defined top where particle concentration rapidly drops to zero.

McClymer, James P.↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2023

Absolute cross section of the C 12 ( p , γ ) N 13 reaction

Solar neutrino measurements have recently reached a level of sensitivity such that CNO fluxes can now be experimentally determined. While these first measurements are still only sensitive to the higher energy neutrinos resulting from the β + decays of 15 Ο produced by the 14 Ν ⁡( p ,$\gamma$)⁢ 15 O reaction, future measurements will work towards detection of neutrinos from the β + decay of 13 N from the 12 C ⁡( p ,$\gamma$)⁢ 13 N reaction. Here, this paper reports on a recent measurement of the 12 C ⁡( p ,$\gamma$)⁢ 13 N reaction covering a broad laboratory energy range between 1.0 and 2.5 MeV. The measurement was made to better determine the overall normalization of the absolute cross section and to explore the interference effects between the two broad, overlapping resonances at proton energies of 0.460 and 1.689 MeV and the direct capture to the ground state of 13 N in the framework of a multichannel R -matrix analysis. This work takes into account previous radiative capture as well as elastic 12 C ( p , p ) 12 C scattering data, making uncertainty estimations using a Bayesian framework, to determine a reliable extrapolation of the low energy S factor towards the stellar energy range of CNO hydrogen burning. These new experimental results, and a detailed investigation of the past literature data, suggest that the resonant component of the cross section should be 30% lower than previously accepted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Front-End Engineering Design for Piperazine with the Advanced Stripper

This Department of Energy (DOE) funded project was executed with the goal of preparing a Front-End Engineering Design (FEED) for the capture and compression of 90% of the CO2 that would normally be emitted from an existing natural gas combined cycle (NGCC) plant. The FEED focused on the application of the piperazine advanced stripper (PZAS) process at Mustang Station of the Golden Spread Electric Cooperative (GSEC), which consists of two gas turbines with common heat recovery steam generator (HRSG). The University of Texas at Austin (UT) served as the prime contractor, and subcontracted AECOM Technical Services and Trimeric Corporation to support FEED development. This project team has worked together to advance PZAS for more than a decade. ExxonMobil, Chevron, and Total provided project co-funding. The objectives of this work included: 1. To advance engineering design such that a comprehensive estimate for the total installed cost of a full-scale PZAS CO2 Capture Plant with CO2 compression can be developed on an existing NGCC power plant. a. These detailed costs can also be used to qualify PZAS and other related second generation (2G) amine scrubbing processes for use on cogeneration facilities in refineries and chemical plants that use gas turbines with HRSGs to produce steam. b. These detailed costs will help qualify 2G amine scrubbing for use on NGCC power plants and establish a more accurate baseline cost to be used as a target by other capture technologies. 2. To provide cost details to be used in the economic optimization of the process features of PZAS and other 2G amine scrubbing processes. 3. To provide DOE with a more detailed understanding of carbon capture costs in a commercial application, enabling DOE to better design its R&D program to improve the economics for carbon capture. 4. To provide the host site and cost share partners with the information necessary to determine whether a commercial project to capture and use CO2 for enhanced oil recovery (EOR) or for sequestration can be justified (when accounting for the 45Q tax credit). A key component of the FEED is the estimated total installed cost, which provides a basis for the likely capital investment necessary to implement the PZAS carbon capture process at this location and scale. In combination with the included economic analysis, which accounts for potential revenue from the produced CO2, potential avenues to profitability are explored. The major findings of the FEED are as follows: The Mustang Station PZAS CO2 Capture Plant estimated total project cost of $698 MM of which $384 MM was direct costs. The annual operating costs were $32.6 MM. The total investment for a PZAS facility at Mustang Station is $725 MM. This estimate includes owner’s cost of $25 million and a contingency of $110 MM. • The study estimated the CO2 capture plant at Mustang Station would generate CO2 at $110/tonne for EOR, assuming a 12% IRR (internal rate of return) and an 85% capacity factor. For CO2 storage, the same case would achieve a 12% IRR at about $114/tonne. At a capacity factor of 52%, the storage and EOR cases would break even when carbon is priced ~$150/tonne. The economic analysis determined that the capacity factor and utility pricing, among other variable factors, had a significant effect on the economics and will need additional studied. • The energy penalty of the PZAS plant would be about 46 MW in connected power and 35 MW in operating load. The natural gas requirement (for the Gas Boiler package) would be about 354 MMBTU/hr. • The FEED revealed no major risks in process maturity. However, some areas were outlined for further engineering during detailed design, which included the Gas Boiler system, general arrangement and site layout, air coolers, schedule development, and optimization of the process for higher CO2 removal. • If PZAS were to be implemented at another host site, additional opportunities for cost reduction for would include cost reduction through use of cooling water and steam extraction.

03 NATURAL GAS↗
DOE OSTI2024

Two-moment Neutrino Flavor Transformation with Applications to the Fast Flavor Instability in Neutron Star Mergers

Abstract Multi-messenger astrophysics has produced a wealth of data with much more to come in the future. This enormous data set will reveal new insights into the physics of core-collapse supernovae, neutron star mergers, and many other objects where it is actually possible, if not probable, that new physics is in operation. To tease out different possibilities, we will need to analyze signals from photons, neutrinos, gravitational waves, and chemical elements. This task is made all the more difficult when it is necessary to evolve the neutrino component of the radiation field and associated quantum-mechanical property of flavor in order to model the astrophysical system of interest—a numerical challenge that has not been addressed to this day. In this work, we take a step in this direction by adopting the technique of angular-integrated moments with a truncated tower of dynamical equations and a closure, convolving the flavor-transformation with spatial transport to evolve the neutrino radiation quantum field. We show that moments capture the dynamical features of fast flavor instabilities in a variety of systems, although our technique is by no means a universal blueprint for solving fast flavor transformation. To evaluate the effectiveness of our moment results, we compare to a more precise particle-in-cell method. Based on our results, we propose areas for improvement and application to complementary techniques in the future.

Astronomy & Astrophysics↗
DOE OSTI2023

Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning

When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

Plume Collection Strategies for Icy World Sample Return

Three icy worlds in the solar system display evidence of pluming activity. Water vapor and ice particles emanate from cracks near the south pole of Saturn's moon Enceladus. The plume gas contains simple hydrocarbons that could be fragments of larger, more complex organics. More recently, observations using the Hubble and Herschel space telescopes have hinted at transient water vapor plumes at Jupiter's moon Europa and the dwarf planet Ceres. Plume materials may be ejected directly from possible sub-surface oceans, at least on Enceladus. In such oceans, liquid water, organics, and energy may co-exist, making these environments habitable. The venting of habitable ocean material into space provides a unique opportunity to capture this material during a relatively simple flyby mission and return it to Earth. Plume collection strategies should enable investigations of evidence for life in the returned samples via laboratory analyses of the structure, distribution, isotopic composition, and chirality of the chemical components (including biomolecules) of plume materials. Here, we discuss approaches for the collection of dust and volatiles during flybys through Enceladus' plume, based on Cassini results and lessons learned from the Stardust comet sample return mission. We also highlight areas where sample collector and containment technology development and testing may be needed for future plume sample return missions.

Stardust Collector↗
NASA NTRSDate not supplied

An Experimental Study on Low Pressure Frost Formation for Lunar Polar Water Capture

In-situ resource utilization (ISRU) is a vital component of NASA’s mission to the Moon and beyond, as the extraction of resources from the environment can reduce payload weight and the frequency of resupply missions. Since the discovery of water in the regolith of the permanently shadowed regions (PSR) of the Moon, its extraction and transport has become an area of increasing interest for NASA. One proposed method is heating icy regolith to free the water before de-sublimating and transporting it as ice in a tanker. However, little is known regarding the dynamics of frost growth at low pressures, and an understanding of the heat transfer process is required to properly size the heat exchanger for the tanker. To investigate this phenomenon, a cold plate was placed in a vacuum chamber with water vapor directed at its surface. The chamber pressure (300 and 500 Pa) and cold plate temperature (–18 to –5 °C) were kept below the triple point and varied throughout the experiment to examine their impact on frost layer heat transfer. As water flowed into the chamber and deposited on the cold plate surface, the heat flux and temperature were measured along with the frost layer thickness and/or mass. Density calculated at the conclusion of each test suggests the frost layer is denser than that of frost grown at atmospheric pressure. The results demonstrate unexpected density and heat transfer characteristics and require development of a new model of frost growth for lunar conditions

Lunar polar↗