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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 757 records · Page 42

Predicting Catalyst Surface Stability Under Reaction Conditions Using Deep Reinforcement Learning and Machine Learning Potentials

Catalysts are critical for most large-scale energy intensive chemical transformation processes, such as energy storage, liquid fuel production, and the formation of chemical building blocks. The catalyst composition, structure, and morphology impact the performance under reaction conditions and influences properties like activity and selectivity. Many industrial catalysts offer imperfect activity/selectivity, or contain expensive metals. Further, catalysts can deactivate over time as the morphology changes or harsh reactive environments alter the surface structure. Methods to automatically model and predict the kinetics of how catalyst surfaces will restructure would enable engineers to design around these challenges, improve performance, increase longevity. This project investigated a specific type of machine learning model, deep reinforcement learning, machine learning models to act as surrogates for the physical system, and compared the results of these approaches with a specialized high-throughput experimental synthesis and measurement platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

Hong Kong is an impact crater: Proof from the geomorphological and geological evidence

Hong Kong is a city in southern China. The urban districts of Hong Kong, Kowloon, and Victoria Harbour are situated within Hong Kong. Hong Kong is surrounded by mountains with a diameter of 11 km. Three million people live inside the basin. The round structure of the mountains in Hong Kong has been describd as a granite dome that is deeply eroded (batholith). The circularity of the mountains, the existence of a central hill, the inner slope of the mountains being greater than the outer slope, the presence of deep layer rock inside the basin, and the depth-to-diameter ratio were studied. All this evidence shows that the Hong Kong structure satisfies the geomorphological requirement of an impact crater. Some shock metamorphic phenomena of the rocks in Hong Kong such as planar features, microspherilitic silica glass (lechaterlierite), fused margins of rock fragments, concussion fractures, impact glass in which some schlierens are consistent with pyroxene spiculites, etc., were first discovered in Oct. 1990. In Hong Kong Island, an impact melt sheet was observed from the Victoria Peak to the southern shore. Quenching fractures of quartz in Kowloon fine-grained granite was also discovered. In our work, the K-Ar age (83.34 + 1.26 m.y.) of the impact melt rock, which is younger in comparison to the K-Ar age (117 m.y.) in Hong Kong and Kowloon granite, was measured, and the phenomena indicate that after the granite body formed, there was another geologic event. Maybe it is the Hong Kong cratering event.

Chan, Chu-Lok↗

Deploying Adversarial Attacks in Super-Resolution Models

Reliable super-resolution methods are crucial for applications like remote sensing, grid resilience and disaster impact analysis, and standoff biometrics. These methods infuse additional high-frequency information into reconstructions, allowing for better contextualization and image intelligence. However, super-resolution models can also introduce hallucinations or other unseen vulnerabilities that could be exploited by an adversary. This is further compounded by the prominence of deep learning in these models, as models are often blindly applied on out-of-distribution images. In this work, we implement adversarial attacks in common open-source super-resolution models and examine their impact on reconstructions and downstream classification tasks. We find that an adversarially trained super-resolution model can produce high-quality reconstructions that degrade downstream classifications. Moreover, these attacks do not require access to low-resolution imagery or class labels at inference time. These results demonstrate the vulnerability of super-resolution methods to malicious actors and motivates the development of a detector for super-resolution adversarial attacks. Further exploration of adversarial attacks in this domain is required to ensure trustworthiness and robustness of super-resolution models for national security applications.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Variable X-Ray Absorption in the Mini-BAL QSO PG 1126-041

Context. X-ray studies of AGN with powerful nuclear winds are important to constrain the physics of the inner accretion/ejection flow around SMBH, and to understand the impact of such winds on the AGN environment. Aims. Our main scientific goal is to constrain the properties of a variable outflowing absorber that is thought to be launched near the SMBH of the mini-BAL QSO PG 1126-041 using a multi-epoch observational campaign performed with XMM-Newton. Methods. We performed temporally resolved X-ray spectroscopy and simultaneous UV and X-ray photometry on the most complete set of observations and on the deepest X-ray exposure of a mini-BAL QSO to date. Results. We found complex X-ray spectral variability on time scales of both months and hours, best reproduced by means of variable massive ionized absorbers along the line of sight. As a consequence, the observed optical-to-X-ray spectral index is found to be variable with time. In the highest signal-to-noise observation we detected highly ionized X-ray absorbing material outflowing much faster (u(sub X) approx. 16 500 km/s) than the UV absorbing one (u(sub uv) approx. 5,000 km/s). This highly ionized absorber is found to be variable on very short (a few kiloseconds) time scales. Conclusions. Our findings are qualitatively consistent with line driven accretion disk winds scenarios. Our observations have opened the time-resolved X-ray spectral analysis field for mini-BAL QSOs; only with future deep studies will we be able to map the dynamics of the inner flow and understand the physics of AGN winds and their impact on the environment.

Giustini, M.↗

The Role of Surface Oxygen Vacancies in BiVO 4

Bismuth vanadate (BiVO 4 ) is a widely studied oxide in solar water splitting, known for its ease of synthesis, high charge extraction yields, and advantageous band alignment with water. We present a combined first-principles and experimental study of the electronic structure of the (010) surface of BiVO 4 aimed at disentangling the impact of the surface and bulk oxygen vacancies on the electronic structure and transport properties. We found that oxygen vacancies are deep donors at the surface as they are in the bulk; our calculations on defect and polaron formation energies suggest that, while polarons formed from oxygen vacancies in the bulk can contribute to conductivity, those at the surface likely do not. Our results also show that out-of-plane structural relaxations at the surface contribute to the relatively immobile nature of electron polarons derived from surface oxygen vacancies. The structural model derived from first-principles calculation was validated by comparing computed results with experimental measurements of single-crystal and epitaxially grown single-crystalline BiVO 4 samples. Finally, we also found a reasonably good agreement between our calculated and measured work functions for BiVO 4 samples with and without oxygen vacancies.

36 MATERIALS SCIENCE↗

Identification of mobile genetic elements with geNomad

Identifying and characterizing mobile genetic elements in sequencing data is essential for understanding their diversity, ecology, biotechnological applications and impact on public health. Here we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a dataset of more than 200,000 marker protein profiles to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks, geNomad achieved high classification performance for diverse plasmids and viruses (Matthews correlation coefficient of 77.8% and 95.3%, respectively), substantially outperforming other tools. Leveraging geNomad’s speed and scalability, we processed over 2.7 trillion base pairs of sequencing data, leading to the discovery of millions of viruses and plasmids that are available through the IMG/VR and IMG/PR databases. geNomad is available at https://portal.nersc.gov/genomad.

59 BASIC BIOLOGICAL SCIENCES↗

Detection of the significant impact of source clustering on higher order statistics with DES Year 3 weak gravitational lensing data

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10 −3 (2.6σ) using third-order map moments and p = 3 × 10 −11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order N-point functions, wavelet-moment observables, and deep learning or field-level summary statistics of weak lensing maps.

79 ASTRONOMY AND ASTROPHYSICS↗

Paradigm lost: Venus crater depths and the role of gravity in crater modification

Previous to Magellan, a convincing case had been assembled that predicted that complex impact craters on Venus were considerably shallower than their counterparts on Mars, Mercury, the Moon, and perhaps even Earth. This was fueled primarily by the morphometric observation that, for a given diameter (D), crater depth (d) seems to scale inversely with surface gravity for the other planets in the inner solar system. The unpredicted depth of fresh impact craters on Venus argues against a simple inverse relationship between surface gravity and crater depth. Factors that could contribute to deep craters on Venus include (1) more efficient excavation on Venus, possibly reflecting rheological effects of the hot venusian environment; (2) more melting and efficient removal of melt from the crater cavity; and (3) enhanced ejection of material out of the crater, possibly as a result of entrainment in an atmosphere set in motion by the passage of the projectile. The broader issue raised by the venusian crater depths is whether surface gravity is the predominant influence on crater depths on any planet. While inverse gravity scaling of crater depths has been a useful paradigm in planetary cratering, the venusian data do not support this model and the terrestrial data are equivocal at best. The hypothesis that planetary gravity is the primary influence over crater depths and the paradigm that terrestrial craters are shallow should be reevaluated.

Sharpton, Virgil L.↗

January and July global distributions of atmospheric heating for 1986, 1987, and 1988

Three-dimensional global distributions of atmospheric heating are estimated for January and July of the 3-year period 1986-88 from the European Center for Medium Weather Forecasts (ECMWF) Tropical Ocean Global Atmosphere (TOGA) assimilated datasets. Emphasis is placed on the interseasonal and interannual variability of heating both locally and regionally. Large fluctuations in the magnitude of heating and the disposition of maxima/minima in the Tropics occur over the 3-year period. This variability, which is largely in accord with anomalous precipitation expected during the El Nino-Southern Oscillation (ENSO) cycle, appears realistic. In both January and July, interannual differences of 1.0-1.5 K/day in the vertically averaged heating occur over the tropical Pacific. These interannual regional differences are substantial in comparison with maximum monthly averaged heating rates of 2.0-2.5 K/day. In the extratropics, the most prominent interannual variability occurs along the wintertime North Atlantic cyclone track. Vertical profiles of heating from selected regions also reveal large interannual variability. Clearly evident is the modulation of the heating within tropical regions of deep moist convection associated with the evolution of the ENSO cycle. The heating integrated over continental and oceanic basins emphasizes the impact of land and ocean surfaces on atmospheric energy balance and depicts marked interseasonal and interannual large-scale variability.

Schaack, Todd K.↗

Enabling Technologies for Deep Space Motion Imagery

From the beginning of the Space Age, imagery, particularly motion imagery, has been a part of crewed and uncrewed missions. As technologies have evolved the imagery gets better, more compelling, and more useful for operations and monitoring of systems, crew, and spacecraft. Film, video and live television have engaged the public and sparked the imaginations of engineers, scientists, and artists alike. As we look forward now to crewed missions beyond low-Earth orbit, such as the Deep Space Gateway being considered as a pre-cursor to future crewed Mars missions, there are both opportunities and challenges in implementing a multi-faceted imaging system that advances mission capabilities and technology.This paper will present a vision for an imaging system that is relevant for operations of the ISS and future crewed missions in deep space, with a detailed look at some of the key innovative technologies required to enable such a system. In addition, impacts to Space Operations, video distribution to the public and to science investigators, and video system interoperability will be presented. Opportunities where standardization can enable interoperability are also identified for those imagery and communications functions planned for inclusion in the Consultative Committee for Space Data Systems (CCSDS) Blue Book.

Grubbs, Rodney↗

Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves

Ocean-driven basal melting of Antarctica’s floating ice shelves accounts for about half of their mass loss in steady state, where gains in ice-shelf mass are balanced by losses. Ice-shelf thickness changes driven by varying basal melt rates modulate mass loss from the grounded ice sheet and its contribution to sea level, and the changing meltwater fluxes influence climate processes in the Southern Ocean. Existing continent-wide melt-rate datasets have no temporal variability, introducing uncertainties in sea level and climate projections. Here, we combine surface height data from satellite radar altimeters with satellite-derived ice velocities and a new model of firn-layer evolution to generate a high-resolution map of time-averaged (2010–2018) basal melt rates and time series (1994–2018) of meltwater fluxes for most ice shelves. Total basal meltwater flux in 1994 (1,090 ± 150 Gt/yr) was similar to the steady-state value (1,100 ± 60 Gt/yr), but increased to 1,570 ± 140 Gt/yr in 2009, followed by a decline to 1,160 ± 150 Gt/yr in 2018. For the four largest ‘cold-water’ ice shelves, we partition meltwater fluxes into deep and shallow sources to reveal distinct signatures of temporal variability, providing insights into climate forcing of basal melting and the impact of this melting on the Southern Ocean.

Susheel Adusumilli↗

Imaging the End-to-End Dynamics of the Global Solar Wind-Magnetosphere Interaction

Much of what we know about the solar wind’s interaction with the Earth’s magnetosphere has been gained from isolated in situ measurements by single or multiple spacecraft. Based on their observations, we know that reconnection, whether on the dayside magnetopause or deep within the Earth’s magnetotail, controls the flow of solar wind energy into and through the global system. We know that nightside activity provides the energized particles that power geomagnetic storms. But by their very nature these isolated in situ measurements cannot provide an instantaneous global view of the entire system or its cross-scale dynamics. As a result, we don’t know which mode of reconnection prevails on the dayside magnetopause or within the magnetotail as a function of solar wind and geomagnetic conditions. We don’t know which mode or modes of nightside activity supply the most energized particles to the ring current. Nor do we know the dominant loss mode for ring current decay: precipitation, magnetopause outflow, or charge exchange with neutrals. Nor do we know how processes deep within the magnetosphere provide feedback to those happening in the outer magnetosphere. The answers to these questions could have an impact far beyond magnetospheric physics, since magnetic reconnection, particle acceleration, and charge-exchange are fundamental plasma processes that operate at other planets and throughout the universe. Comprehensive end-to-end global imaging of the key micro, meso-, and macro-scale plasma structures that comprise the magnetosphere will provide the answers to these questions via observations with a spatial resolution that exceeds anything possible with in situ measurements. Each proposed interaction mechanism generates a diagnostic plasma structure or boundary signature. Global, end-to-end, imaging provides the pathway to understanding the system as a whole, its constituent parts, and its cross-scale processes on a continuous basis, as needed to quantify the flow of solar wind energy through the global magnetospheric system. The significance of each mechanism is the product of its amplitude and occurrence rate. This white paper describes how a comprehensively-instrumented single spacecraft in a high-latitude circular polar orbit can provide the essential observations needed to track and quantify the flow of solar wind energy through the magnetosphere, including the solar wind plasma and magnetic field input, the magnetopause location in soft X-rays, the auroral oval in far ultraviolet, the ring current in energetic neutrals, the plasmasphere in extreme ultraviolet, the exosphere in Lyman-, the microstructure of the nightside auroral oval in ground-based all sky cameras, and the magnetic perturbations of ionospheric current patterns seen by ground-based magnetometers.

D G Sibeck↗

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗

From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption

Accurate short-term energy consumption forecasting for commercial buildings is crucial for smart grid operations. While smart meters and deep learning models enable forecasting using past data from multiple buildings, data heterogeneity from diverse buildings can reduce model performance. The impact of increasing dataset heterogeneity in time series forecasting, while keeping size and model constant, is understudied. We tackle this issue using the ComStock dataset, which provides synthetic energy consumption data for U.S. commercial buildings. Two curated subsets, identical in size and region but differing in building type diversity, are used to assess the performance of various time series forecasting models, including finetuned open-source foundation models (FMs). The results show that dataset heterogeneity and model architecture have a greater impact on post-training forecasting performance than the parameter count. Moreover, despite the higher computational cost, finetuned FMs demonstrate competitive performance compared to base models trained from scratch.

commercial buildings↗

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low clean concentration and a high dirty concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

cloud-resolving model↗

Updated QCD global analysis of single transverse-spin asymmetries: Extracting $\tilde{H}$, and the role of the Soffer bound and lattice QCD

Here, we present an update to the QCD global analysis of single transverse-spin asymmetries presented in [J. Cammarota et al. (Jefferson Lab Angular Momentum Collaboration), Phys. Rev. D 102, 054002 (2020).] (JAM3D-20). JAM3D-20 simultaneously included transverse momentum dependent and collinear twist-3 observables, both of which are sensitive to quark-gluon-quark correlations in hadrons. In this study we extract for the first time the twist-3 chiral odd fragmentation function $\tilde{H}$ by incorporating the sin φ s modulation data from semi-inclusive deep-inelastic scattering along with its contribution to the single transverse-spin asymmetry in pion production from proton-proton collisions. We also explore the impact of lattice QCD tensor charge calculations and the Soffer bound on our global analysis. We find that both constraints can be accommodated within our results, with $\tilde{H}$ playing a key role in maintaining agreement with the data from proton-proton collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗