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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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Data Architecture and Analytics Requirements for Artificial Intelligence and Machine Learning Applications to Achieve Condition-Based Maintenance

This report identified some of the important requirements that needs to be taken into consideration as part of the data evolution for the CBM application of a CWS in a NPP. In the data evolution process, the information is converted into insight leading into actions using advancements in AI/ML technologies. A notion of RESET AI: design, development, deployment, and operation principals are introduced to lifecycle of AI technologies. Towards the end of the report, we discussed how this CBM can be realized in a SDE. As path forward, this report lays the foundation for developing a more detailed industry guidance supporting data evolution for other plant applications like operations and plant support. These would be developed as part of ongoing research in the fiscal year 2023.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Insights Into Seismicity Associated With Flexibly Operating Enhanced Geothermal System From Real‐Time Distributed Acoustic Sensing

Enhanced Geothermal Systems (EGS) have the capacity to broaden the accessible resource pool for geothermal power generation. Traditionally viewed as a “baseload” resource, their flexible operation might also enable dispatchable load‐following generation and long‐term energy storage, aligning them with the evolving landscape of decarbonized electricity systems. However, increasing permeability and extracting energy during EGS operations can induce microseismic events; for many prior EGS efforts, some associated seismicity has been observed. While energetically beneficial, the flexibility of EGS operations prompts our inquiry into whether new types of operations will yield previously unseen seismicity patterns. We demonstrate the use of distributed acoustic sensing (DAS) with real‐time edge computing to monitor seismicity during a pilot test of a cyclically operated EGS facility at the Blue Mountain geothermal field. Our focus lies in uncovering seismicity insights from the real‐time microseismic catalog, particularly during load‐following dispatchability tests simulating flexible EGS operation. Here, we find that variations in pore pressure consistently correlate with seismicity, and that controlling pressure cycles during flexible operations appears to constrain microseismic activity during subsequent cycles. The spatio‐temporal evolution of microseismic clouds recorded during cyclic injection cycles fits diffusive models over our available observation period. Additionally, seismicity elevation lags behind pore pressure increases, likely due to pressure diffusion to the fracture system boundary. Through real‐time monitoring, we offer novel insights into seismicity associated with flexibly operating EGS. Our findings suggest that leveraging DAS and edge computing can inform EGS operations and help mitigate induced seismicity.

Chamarczuk, Michal [Rice Univ., Houston, TX (Unite↗

Null states and time evolution in a toy model of black hole dynamics

Abstract Spacetime wormholes can provide non-perturbative contributions to the gravitational path integral that make the actual number of statese S in a gravitational system much smaller than the number of states$$ {e}^{S_{\textrm{p}}} $$ e S p predicted by perturbative semiclassical effective field theory. The effects on the physics of the system are naturally profound in contexts in which the perturbative description actively involvesN=O(e S ) of the possible$$ {e}^{S_{\textrm{p}}} $$ e S p perturbative states; e.g., in late stages of black hole evaporation. Such contexts are typically associated with the existence of non-trivial quantum extremal surfaces. However, by forcing a simple topological gravity model to evolve in time, we find that such effects can also have large impact forN≪e S (in which case no quantum extremal surfaces can arise). In particular, even for smallN, the insertion of generic operators into the path integral can cause the non-perturbative time evolution to differ dramatically from perturbative expectations. On the other hand, this discrepancy is small for the special case where the inserted operators are non-trivial only in a subspace of dimensionD≪e S . We thus study this latter case in detail. We also discuss potential implications for more realistic gravitational systems.

Physics↗

Overview of Model-Based Systems Engineering Efforts to Evolve the Airspace Research Roadmap

NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution requires a plan to effectively organize, integrate, and communicate NASA’s research and development. The planning tool, called the UAM airspace research roadmap, or just roadmap, is key to the execution of NASA’s UAM airspace research over the next ten years. Implemented through Model-Based Systems Engineering (MBSE) methodology, the roadmap will help to prioritize and coordinate research efforts, and to integrate results that build towards NASA’s research goals of evolving UAM airspace for integration of UAM operations into the National Airspace System (NAS). This paper presents an overview of on-going MBSE efforts to meet these overarching goals. Note: Included mp4 video of presentation included in record, runtime 9 mins 57 secs.

Model-Based Systems Engineering↗

Overview of Model-Based Systems Engineering Efforts to Evolve the Airspace Research Roadmap

NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution requires a plan to effectively organize, integrate, and communicate NASA’s research and development. The planning tool, called the UAM airspace research roadmap, or just roadmap, is key to the execution of NASA’s UAM airspace research over the next ten years. Implemented through Model-Based Systems Engineering (MBSE) methodology, the roadmap will help to prioritize and coordinate research efforts, and to integrate results that build towards NASA’s research goals of evolving UAM airspace for integration of UAM operations into the National Airspace System (NAS). This paper presents an overview of on-going MBSE efforts to meet these overarching goals.

Model-Based Systems Engineering↗

Rescuing Legacy Seismic Data FAIR’ly

The Earth’s interconnected and dynamical systems operate on a spectrum of time scales from millions of years to fractions of a second. While the evolution of the Earth and its deep interior are beyond the time span of human observations, understanding of many natural phenomena operating on human times scales have benefited from direct scientific observation. Continuous processes and those that are repeated over time shape the environment we live in. Furthermore, as we are faced with unprecedented changes to climate, understanding the deeper patterns and trends in natural systems through time have taken on new importance (Research Data Alliance, 2019). The call to reuse data is driven not only by economics but also by the recognition of their complete uniqueness (observations of natural systems are not repeatable) and scientific value in enhancing current understandings as well as potential new discoveries especially in the era of big data. These data are part of the historical record and our scientific heritage (American Geophysical Union, 2019) not only in explicitly recording earth observations but implicitly recording, and thus providing the evidence that addresses the manner in which science was conducted.

58 GEOSCIENCES↗

Decoupling the catalytic and degradation mechanisms of cobalt active sites during acidic water oxidation

Advancement of iridium-free catalysts for the low-pH oxygen evolution reaction (OER) is required to enable multi-gigawatt-scale proton-exchange water electrolysis. Cobalt-based materials might address this requirement, but little is known about the mechanism of operation of these OER catalysts at low pH. Here we investigate the nature and evolution of the active cobalt sites along with charge- and mass-transfer processes that support their catalytic function within a cobalt–iron–lead oxide material using in situ spectroscopic, gravimetric and electrochemical techniques. We demonstrate that corrosion of the cobalt sites and their reformation through electrooxidation of dissolved Co 2+ do not affect the catalytic mechanism and are decoupled from the OER. The OER-coupled charge transfer is supported by Co (3+δ)+ -oxo-species, which are structurally different from those reported for alkaline/near-neutral conditions and are formed on a relatively slow timescale of minutes. These mechanistic insights might assist in developing genuinely practical catalysts for this vital technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree–Fock and density functional theory but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate and costly classical methods for treating electron correlation. However, here we tighten bounds showing that certain first-quantized quantum algorithms enable exact time evolution of electronic systems with exponentially less space and polynomially fewer operations in basis set size than conventional real-time time-dependent Hartree–Fock and density functional theory. Although the need to sample observables in the quantum algorithm reduces the speedup, we show that one can estimate all elements of the k-particle reduced density matrix with a number of samples scaling only polylogarithmically in basis set size. We also introduce a more efficient quantum algorithm for first-quantized mean-field state preparation that is likely cheaper than the cost of time evolution. We conclude that quantum speedup is most pronounced for finite-temperature simulations and suggest several practically important electron dynamics problems with potential quantum advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Potential space station evolution and growth modes

User requirements for the first ten years of space station operation are assessed, and space station system capabilities to meet those needs are delineated. A module length of about 11.5 m with external interconnects best meets growth needs, and a power unit which provides 42 KW is desirable. Four growth scenarios for the manned element of the space station program are studied, and typical growth configurations are described. The full dual keel configuration is attractive at this point due to its increased flexibility.

Pritchard, E. B.↗

Synergism of He-3 acquisition with lunar base evolution

It is shown how acquisition of He-3 affects Lunar Base development and operation. A four phase evolutionary Lunar Base scenario is summarized with initial equipment mass and resupply requirements. Requirements for various He-3 mining operations are shown and available by-products are identified. Impacts of mining He-3 on Lunar Base development include increases in equipment masses to be delivered to the lunar surface and a reduction of Lunar Base resupply based on availability of He-3 acquisition by-products. It is concluded that the acquisition of this valuable fusion fuel element greatly enhances the commercial potential of a Lunar Base.

Crabb, Thomas M.↗

The Flux of Impact Ejecta on the Lunar Surface from Scaling Considerations: Implications for Operational Hazards and Geomorphic Forcing

The impact cratering process has been critical to the evolution of the Moon’s surface over its geologic history and remains an important ongoing process today. Impact events have a major local effect, but also excavate ejecta particles that re-impact the lunar surface over a wide area. Quantifying the flux of ejecta to a given point on the Moon is the subject of this work. We also estimate how this flux is partitioned into different particle sizes and different ejecta velocities. Motivation: There are two main factors motivating this work. First, and most critically, is the assessment of the hazard posed by impact ejecta for future surface exploration (i.e., to infrastructure, spacesuits, etc.). LROC observations of new craters have led to the reemphasized need to consider this hazard. In fact, a hazard assessment of this type was made prior to Apollo, although some of the underlying assumptions of that work are now clearly obsolete (see [4]). We also now know much more about the impactor flux, scaling of impact events, and scaling of ejecta than was known in the 1960's, so revisiting this hazard assessment is appropriate.We note that also have recently revisited the earlier hazard estimates and independently revised them downward using an entirely different analytical approach. The second motivation is that several recent papers have argued that the flux of distal ejecta is the controlling factor in how fast the lunar surface evolves. For this reason, improving understanding of the ejecta mass flux and how the flux translates into geomorphic work is of interest. To be clear, it is obvious that the ejecta mass flux is much larger than the primary impactor mass flux – indeed, this is self-evident because the craters excavated by hypervelocity impacts are much larger than their impactors. On the other hand, the energy delivered by a given primary to the surface is larger than the sum of the energy delivered by all its associated ejecta, as required by conservation, aggravated by the fact that not all of an impactor’s kinetic energy is partitioned into ejecta excavation. If distal ejecta and secondaries control lunar geomorphic evolution, this suggests that re-impacting ejecta must more efficiently translate their energy into geomorphic work than primaries. It is also easy to imagine the relative efficiency of primary and secondary impacts to do geomorphic work varying with the size of the primary. Considering the details of this process is thus of significant interest for lunar geomorphology.

Fassett, C. I.↗

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Human-in-the-Loop Evaluation of Dynamic Multi-Flight Common Route Advisories

Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.

Traffic Flow Management↗

Human-in-the-Loop Evaluation of Dynamic Multi-Flight Common Route Advisories

Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.

Traffic Flow Management↗

Stochastic Averaging Principle for Spatial Birth-and-Death Evolutions in the Continuum

We study a spatial birth-and-death process on the phase space of locally finite configurations Γ{sup +}×Γ{sup −} over ℝ{sup d}. Dynamics is described by an non-equilibrium evolution of states obtained from the Fokker-Planck equation and associated with the Markov operator L{sup +}(γ{sup −})+(1/ε)L{sup −}, ε>0. Here L{sup −} describes the environment process on Γ{sup −} and L{sup +}(γ{sup −}) describes the system process on Γ{sup +}, where γ{sup −} indicates that the corresponding birth-and-death rates depend on another locally finite configuration γ{sup −}∈Γ{sup −}. We prove that, for a certain class of birth-and-death rates, the corresponding Fokker-Planck equation is well-posed, i.e. there exists a unique evolution of states μ{sub t}{sup ε} on Γ{sup +}×Γ{sup −}. Moreover, we give a sufficient condition such that the environment is ergodic with exponential rate. Let μ{sub inv} be the invariant measure for the environment process on Γ{sup −}. In the main part of this work we establish the stochastic averaging principle, i.e. we prove that the marginal of μ{sub t}{sup ε} onto Γ{sup +} converges weakly to an evolution of states on Γ{sup +} associated with the averaged Markov birth-and-death operator L̄=∫{sub Γ{sup −}}L{sup +}(γ{sup −})dμ{sub inv}(γ{sup −}).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization using Dynamic Evolutionary Systems or NODES. We apply this approach to real-time combustion engine control and develop an engine-specific hardware platform for NODES called FireBox. We demonstrate how the real-time evolution approach works in simulation and the performance of networks trained in simulation on the physical engine.

Maldonado Puente, Bryan [ORNL] (ORCID:000000033880↗

Perturbative quantum evolution of the gravitational state and dressing in general backgrounds

This paper sets up a perturbative treatment of the evolving quantum state of a gravitational system, in a Schrödinger-like picture, working about a general background. This connects gauge symmetry, the constraints, gravitational dressing, and evolution. Starting with a general time slicing, we give a simple derivation of the relation between the constraints, the Hamiltonian, and its well-known boundary term. Among different approaches to quantization with constraints, we focus on a “gauge-invariant canonical quantization,” which is developed perturbatively in the gravitational coupling. The leading-order solution of the constraints (including the Wheeler-DeWitt equation) for perturbations about the background is given in terms of an explicit construction of gravitational dressings built using certain generalized Green’s functions; different such dressings corresponding to adding propagating gravitational waves to a particular solution of the constraints. Dressed operators commute with the constraints, expressing their gauge invariance, and have an algebraic structure differing significantly from the undressed operators of the underlying field theory. These operators can act on the vacuum to create dressed states, and evolution of general such states is then generated by the boundary Hamiltonian, and alternately may be characterized using other relational observables. This provides a concrete approach to studying perturbative time evolution, including the leading gravitational backreaction, of quantum states of black holes with flat or anti–de-Sitter asymptotics, for example on horizon-crossing slices. This description of evolution in turn provides a starting point for investigating possibly important corrections to quantum evolution, that go beyond quantized general relativity. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗