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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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TEAMER – Harvesting Subsea Water Motion to Provide Clean Electrical Power (Abstract)
Power generation from vortex induced vibration (VIV) is an emerging field with new technologies that are just beginning to be field tested. In this TEAMER project, WITT Energy will be field testing the power production of its pendulum system in two different configurations to evaluate its performance. The amount of power produced by a VIV instrument depend on the frequency at which it vibrates. The vibrational frequency is controlled by the device shape and its interaction with the flow velocity. Computer models are used to predict vibration frequencies as a function of flow velocity but they may be inaccurate due to complicated bathymetry and bottom roughness that is not captures by the models. This project will test the WITT VIV device in the Sequim Bay channel over a range of tidal velocities. Two tests will be completed with different pipe lengths that are expected to vary the vibrational frequency and therefore the power produced. PNNL will use an acoustic doppler current profiler (ADCP) to monitor the flow conditions during the tests. These tests will help WITT Energy evaluate how closely field operations follow computer model predictions and how best to configure their device for electricity production.
Infrared Measurements of Forward Heat Conduction during Simulated Microgravity Flame Spread in the Narrow Channel Apparatus
An infrared (IR) camera provides a way of examining temperature trends associated with simulated microgravity flame spread in the Narrow Channel Apparatus (NCA). The IR camera measures the surface temperature of solid poly methyl methacrylate (PMMA) fuel. These tests examine the forward conduction of heat ahead of the flame front in the non-thermally thin fuel.The NCA is a combustion wind tunnel that simulates a microgravity flame spread environment by employing a narrow gap between the fuel and ceiling of the device, limiting the effects of buoyancy. Test conditions of a 5 mm gap, mean opposed flow velocity of 15 cm/s, and fuel thickness of 3 mm are used.PMMA is selected as the fuel due to repeatability of test results, ease of computational modeling, and known combustion mechanics. Using specific lens and bandpass filter combinations the PMMA can be imaged as effectively opaque. The spectral emissivity for PMMA was calculated and incorporated into the calibration of the camera.Surface temperatures from the IR camera are compared to results from thermocouples embedded in the surface of the fuel. The IR camera results show that nontrivial forward conduction occurs during tests, and therefore must be included in computational models of the process.
Analytical study of laser-supported combustion waves in hydrogen
Laser supported combustion (LSC) waves are an important ingredient in the fluid mechanics of CW laser propulsion using a hydrogen propellant and 10.6 micron lasers. Therefore, a computer model has been constructed to solve the one-dimensional energy equation with constant pressure and area. Physical processes considered include convection, conduction, absorption of laser energy, radiation energy loss, and accurate properties of equilibrium hydrogen. Calculations for 1, 3, 10 and 30 atm were made for intensities of 10 to the 4th to 10 to the 6th W/sq cm, which gave temperature profiles, wave speed, etc. To pursue the propulsion application, a second computer model was developed to describe the acceleration of the gas emerging from the LSC wave into a variable-pressure, converging streamtube, still including all the above-mentioned physical processes. The results show very high temperatures in LSC waves which absorb all the laser energy, and high radiative losses.
Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries
LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.
TRACE Code Validation of BWR SVEA Fuel Assembly Spray Cooling
Emergency spray cooling injection is a safety feature implemented in many boiling water reactor designs to reflood a reactor during an accident. Significant experimental work has qualified the efficacy of spray cooling, and ongoing computational modeling efforts strive to more accurately portray the phenomena involved. This work examines the physical phenomena pertaining to emergency spray cooling injection over SVEA-type fuel assemblies. BWR emergency core cooling system (ECCS) designs commonly incorporate a Low-Pressure Core Spray (LPCS) system that introduces coolant through spray nozzles directed to the top of the core, and are located in the upper plenum region. This design is effective for LOCA response, particularly during the initial refill and reflood stages of accident response where the goal is limiting the peak cladding temperature rise in the core. The U.S. NRC thermal-hydraulics code TRACE version 5.0 Patch 4 has been chosen to simulate the separate-effect tests performed by ASEA-ATOM. The computational model was evaluated by performing forward uncertainty quantification using Dakota as the analysis tool and code driver on 31 identified parameters from the input model and TRACE physical constitutive models. This paper discusses the sensitivity of the investigated parameters with respect to spray cooling simulation. (authors)
Computational and empirical studies predict Mycobacterium tuberculosis -specific T cells as a biomarker for infection outcome
Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis . We identified T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb -specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.
Shoemaker-Levy 9 and Plume-Forming Collisions on Earth
Computational models for the July, 1994 collision of comet Shoemaker Levy 9 with Jupiter have provided a framework for interpreting the observational data. Imaging, photometry, and spectroscopy data from ground-based, Hubble Space Telescope, and Galileo spacecraft instruments are consistent with phenomena that were dominated by the generation of incandescent fireballs that were ballistically ejected to high altitudes, where they formed plumes that subsequently collapsed over large areas of Jupiter's atmosphere. Applications of similar computational models to collisions into Earth's atmosphere show that a very similar sequence of events should take place for NEO impacts with energies as low as 3 megatons, recurring on 100 year timescales or less. This result suggests that the 1908 Tunguska event was a plume-forming atmospheric explosion, and that some of the phenomena associated with it might be related to the ejection and collapse of a high plume. Hazards associated with plume growth and collapse should be included in the evaluation of the impact threat to Earth, and opportunities should be sought for observational validation of atmospheric impact models by exploiting data already being collected from the natural flux of multikiloton to megaton sized objects that constantly enter Earth's atmosphere on annual to decadal timescales.
MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities
The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.
Fusion materials science and technology research opportunities now and during the ITER era
Several high-priority near-term potential research activities to address fusion nuclear science challenges are summarized. General recommendations include: (1) Research should be preferentially focused on the most technologically advanced options (i.e., options that have been developed at least through the singleeffects concept exploration stage, technology readiness levels >3), (2) Significant near-term progress can be achieved by modifying existing facilities and/or moderate investment in new medium-scale facilities, and (3) Computational modeling for fusion nuclear sciences is generally not yet sufficiently robust to enable truly predictive results to be obtained, but large reductions in risk, cost and schedule can be achieved by careful integration of experiment and modeling.
Solid-State Architecture Batteries for Enhanced Rechargeability and Safety (SABERS): Advanced Battery Technology for Sustainable Aviation
All-electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The primary barrier to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL vehicles are at least two times greater than those of electric ground vehicles. Furthermore, inherently non-flammable batteries are essential for safe operation of commercial electric aerovehicles. The SABERS concept proposes a battery that meets the key performance criteria through development of a solid-state architecture battery utilizing high-capacity sulfur-selenium cathode and lithium metal anode. The combination of sulfur and selenium offers a balanced energy-to-power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This hybrid cathode will be developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. A solid-state electrolyte will be used as a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. This solid-state lithium-sulfur/selenium cell will be designed into a serial stacking configuration to enable dense packaging of the battery cells. The serial stacking configuration is termed a bipolar stack, which has the advantages of reducing overall cell weight, simplifying the interfaced connections for the cell, and minimizing the cooling requirements. Lastly, optimization of battery components will occur through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a fully solid-state battery with operational temperatures up to 150 °C which provides the required energy density, discharge rates, and inherent safety to meet the strict aerospace mission performance criteria. This presentation will demonstrate a feasible path for solid-state cells that possess a specific energy of greater than 400 Wh/kg to enable electric aircraft. The presentation will also explore novel materials and computational models used to achieve all solid-state cells that operate safely at very high temperatures and specific energies. The cells can withstand damage while operating without an increase in temperature or spontaneous ignition.
Finite Element Modeling of a Cylindrical Contact Using Hertzian Assumptions
The turbine blades in the high-pressure fuel turbopump/alternate turbopump (HPFTP/AT) are subjected to hot gases rapidly flowing around them. This flow excites vibrations in the blades. Naturally, one has to worry about resonance, so a damping device was added to dissipate some energy from the system. The foundation is now laid for a very complex problem. The damper is in contact with the blade, so now there are contact stresses (both normal and tangential) to contend with. Since these stresses can be very high, it is not all that difficult to yield the material. Friction is another non-linearity and the blade is made out of a Nickel-based single-crystal superalloy that is orthotropic. A few approaches exist to solve such a problem and computer models, using contact elements, have been built with friction, plasticity, etc. These models are quite cumbersome and require many hours to solve just one load case and material orientation. A simpler approach is required. Ideally, the model should be simplified so the analysis can be conducted faster. When working with contact problems determining the contact patch and the stresses in the material are the main concerns. Closed-form solutions for non-conforming bodies, developed by Hertz, made out of isotropic materials are readily available. More involved solutions for 3-D cases using different materials are also available. The question is this: can Hertzian1 solutions be applied, or superimposed, to more complicated problems-like those involving anisotropic materials? That is the point of the investigation here. If these results agree with the more complicated computer models, then the analytical solutions can be used in lieu of the numerical solutions that take a very long time to process. As time goes on, the analytical solution will eventually have to include things like friction and plasticity. The models in this report use no contact elements and are essentially an applied load problem using Hertzian assumptions to determine the contact patch dimensions.
Optoacoustic Microscopy for Investigation of Material Nanostructures-Embracing the Ultrasmall, Ultrafast, and the Invisible
The goal of this grant was the development of a new type of scanning acoustic microscope for nanometer resolution ultrasound imaging, based on ultrafast optoacoustics (>GHz). In the microscope, subpicosecond laser pulses was used to generate and detect very high frequency ultrasound with nanometer wavelengths. We report here on the outcome of the 3-year DOE/BES grant which involved the design, multifaceted construction, and proof-of-concept demonstration of an instrument that can be used for quantitative imaging of nanoscale material features – including features that may be buried so as to be inaccessible to conventional lightwave or electron microscopies. The research program has produced a prototype scanning optoacoustic microscope which, in combination with advanced computational modeling, is a system-level new technology (two patents issues) which offer novel means for precision metrology of material nanostructures, particularly those that are of contemporary interest to the frontline micro- and optoelectronics device industry. For accomplishing the ambitious technical goals, the research roadmap was designed and implemented in two phases. In Phase I, we constructed a “non-focusing” optoacoustic microscope instrument (“POAM”), with nanometer vertical (z-) resolution, while limited to approximately 10 micrometer scale lateral recolution. The Phase I version of the instrument which was guided by extensive acoustic and optical numerical modeling of the basic underlying acoustic and optical physics, featured nanometer scale close loop positioning between the optoacoustic transducer element and a nanostructured material sample under investigation. In phase II, we implemented and demonstrated a scanning version of the instrument (“SOAM”) where incident acoustic energy is focused, and scanned on lateral (x-y) spatial scale in the 100 nm range as per the goals of the project. In so doing we developed advanced numerical simulations to provide computational models of the focusing of multi-GHz acoustic waves to the nanometer scale and innovated a series fabrication approaches for a new type of broadband high-frequency acoustic focusing microscope objective by applying methods on nanoimprinting and focused-ion beam techniques. In the following, the Phase I and Phase II instrument development is reported as Section II. The first segment of this section describes the POAM instrument and its development, while including much of the underlying ultrafast acoustic physics which is common to all of our work for this grant. Then, the science and engineering of the SOAM instrument is described, including the methods of fabricating new types of acoustic microlenses. The results section is followed by reports on publications (Section III), Participants (Section IV), and statement of full use of the allocated grant funds (Section V).
Statistical Sampling of Tide Heights Study
The goal of the study was to determine if it was possible to reduce the cost of verifying computational models of tidal waves and currents. Statistical techniques were used to determine the least number of samples required, in a given situation, to remain statistically significant, and thereby reduce overall project costs. Commercial, academic, and Federal agencies could benefit by applying these techniques, without the need to 'touch' every item in the population. For example, the requirement of this project was to measure the heights and times of high and low tides at 8,000 locations for verification of computational models of tidal waves and currents. The application of the statistical techniques began with observations to determine the correctness of submitted measurement data, followed by some assumptions based on the observations. Among the assumptions were that the data were representative of data-collection techniques used at the measurement locations, that time measurements could be ignored (that is, height measurements alone would suffice), and that the height measurements were from a statistically normal distribution. Sample means and standard deviations were determined for all locations. Interval limits were determined for confidence levels of 95, 98, and 99 percent. It was found that the numbers of measurement locations needed to attain these confidence levels were 55, 78, and 96, respectively.
Multireference Embedding and Fragmentation Methods for Classical and Quantum Computers: From Model Systems to Realistic Applications
One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their steep scaling with system size prohibits their application to large molecules and extended materials. Quantum embedding offers a promising solution by partitioning complex systems into manageable subsystems. In this Review, we highlight recent advances in multireference density matrix embedding and localized active space self-consistent field approaches for complex molecules and extended materials. We discuss both classical implementations and the emerging potential of these methods on quantum computers. Here, by extending classical embedding concepts to the quantum landscape, these algorithms have the potential to expand the reach of multireference methods in quantum chemistry and materials.
Solar Models in Light of New High Metallicity Measurements from Solar Wind Data
We study the impact of new metallicity measurements, from solar wind data, on the solar model. The “solar modeling problem” refers to the persisting discrepancy between helioseismological observations and predictions of solar models computed implementing state-of-the-art photospheric abundances. We critically reassess the problem, in particular considering the new set of abundances of von Steiger and Zurbuchen, determined through the in situ collection of solar wind samples from polar coronal holes. This new set of abundances indicates a solar metallicity Z{sub ⊙}⩾0.0196±0.0014, significantly higher than the currently established value. The new values hint at an abundance of volatile elements (i.e., C, N, O, Ne) close to previous results of Grevesse and Sauval, whereas the abundance of refractory elements (i.e., Mg, Si, S, Fe) is considerably increased. Using the Linear Solar Model formalism, we determine the variation of helioseismological observables in response to the changes in elemental abundances, in order to explore the consistency of these new measurements with constraints from helioseismology. We find that for observables that are particularly sensitive to the abundance of volatile elements, in particular the radius of the convective zone boundary (CZB) and the sound speed around the radius of CZB, improved agreement over previous models is obtained. Conversely, the high abundance of refractories correlates with a higher core temperature, resulting in an overproduction of neutrinos and a huge increase in the surface helium abundance. We conclude that the “solar modeling problem” remains unsolved.
A Quantum Alloy: The Ligand-Protected Au{sub 25-x}Ag{sub x}(SR){sub 18} Cluster
Recent synthetic advances have produced very small (sub-2 nm), ligand-protected mixed-metal clusters. Realization of such clusters allows the investigation of fundamental questions: (1) Will heteroatoms occupy specific sites within the cluster? (2) How will the inclusion of heteroatoms affect the electronic structure and chemical properties of the cluster? (3) How will these very small mixed-metal systems differ from larger, more traditional alloy materials? In this report we provide experimental and computational characterization of the ligand-protected mixed-metal Au{sub 25–x}Ag{sub x}(SC{sub 2}H{sub 4}Ph){sub 18} cluster (abbreviated as Au{sub 25–x}Ag{sub x}, where x = 0–5 Ag atoms) compared with the unsubstituted Au{sub 25}(SC{sub 2}H{sub 4}Ph){sub 18} cluster (abbreviated as Au{sub 25}). Density functional theory analysis has predicted that Ag heteroatoms will preferentially occupy sites on the surface of the cluster core. X-ray photoelectron spectroscopy revealed Au–Ag state mixing and charge redistribution within the Au{sub 25–x}Ag{sub x} cluster. Optical spectroscopy and nonaqueous electrochemistry indicate that Ag heteroatoms increased the cluster lowest unoccupied molecular orbital (LUMO) energy, introduced new features in the Au{sub 25–x}Ag{sub x} absorbance spectrum, and rendered some optical transitions forbidden. In situ spectroelectrochemical experiments revealed charge-dependent Au{sub 25–x}Ag{sub x} optical properties and oxidative photoluminescence quenching. Finally, O{sub 2} adsorption studies have shown Au{sub 25–x}Ag{sub x} clusters can participate in photomediated charge-transfer events. These results illustrate that traditional alloy concepts like metal-centered state mixing and internal charge redistribution also occur in very small mixed-metal clusters. However, resolution of specific heteroatom locations and their impact on the cluster’s quantized electronic structure will require a combination of computational modeling, optical spectroscopy, and nonaqueous electrochemistry.
Used fuel rail shock and vibration testing options analysis
The objective of the rail shock and vibration tests is to complete the framework needed to quantify loads of fuel assembly components that are necessary to guide materials research and establish a technical basis for review organizations such as the U.S. Nuclear Regulatory Commission (NRC). A significant body of experimental and numerical modeling data exists to quantify loads and failure limits applicable to normal conditions of transport (NCT) rail transport, but the data are based on assumptions that can only be verified through experimental testing. The test options presented in this report represent possible paths for acquiring the data that are needed to confirm the assumptions of previous work, validate modeling methods that will be needed for evaluating transported fuel on a case-by-case basis, and inform material test campaigns on the anticipated range of fuel loading. The ultimate goal of this testing is to close all of the existing knowledge gaps related to the loading of used fuel under NCT conditions and inform the experiments and analysis program on specific endpoints for their research. The options include tests that would use an actual railcar, surrogate assemblies, and real or simulated rail transportation casks. The railcar carrying the cradle, cask, and surrogate fuel assembly payload would be moved in a train operating over rail track modified or selected to impart shock and vibration forces that occur during normal rail transportation. Computer modeling would be used to help design surrogates that may be needed for a rail cask, a cask’s internal basket, and a transport cradle. The objective of the design of surrogate components would be to provide a test platform that effectively simulates responses to rail shock and vibration loads that would be exhibited by state-of-the-art rail cask, basket, and/or cradle structures. The computer models would also be used to help determine the placement of instrumentation (accelerometers and strain gauges) on the surrogate fuel assemblies, cask and cradle structures, and the railcar so that forces and deflections that would result in the greatest potential for damage to high burnup and long-cooled UNF can be determined. For purposes of this report we consider testing on controlled track when we have control of the track and speed to facilitate modeling.