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At least 811 records · Page 45

0.7–2.5 μ m Spectra of Hilda Asteroids

The Hilda asteroids are primitive bodies in resonance with Jupiter whose origin and physical properties are not well understood. Current models posit that these asteroids formed in the outer solar system and were scattered along with the Jupiter Trojans into their present-day positions during a chaotic episode of dynamical restructuring. In order to explore the surface composition of these enigmatic objects in comparison with an analogous study of Trojans, we present new near-infrared spectra (0.7–2.5 μ m) of 25 Hilda asteroids. No discernible absorption features are apparent in the data. Synthesizing the bimodalities in optical color and infrared reflectivity reported in previous studies, we classify 26 of the 28 Hildas in our spectral sample into the so-called less-red and red sub-populations and find that the two sub-populations have distinct average spectral shapes. Combining our results with visible spectra, we find that Trojans and Hildas possess similar overall spectral shapes, suggesting that the two minor body populations share a common progenitor population. A more detailed examination reveals that while the red Trojans and Hildas have nearly identical spectra, less-red Hildas are systematically bluer in the visible and redder in the near-infrared than less-red Trojans, indicating a putative broad, shallow absorption feature between 0.5 and 1.0 μ m. We argue that the less-red and red objects found in both Hildas and Trojans represent two distinct surface chemistries and attribute the small discrepancy between less-red Hildas and Trojans to the difference in surface temperatures between the two regions.

79 ASTRONOMY AND ASTROPHYSICS↗

Mobility Energy Productivity Evaluation of Prediction-Based Vehicle Powertrain Control Combined with Optimal Traffic Management

Transportation vehicle and network system efficiency can be defined in two ways: 1) reduction of travel times across all the vehicles in the system, and 2) reduction in total energy consumed by all the vehicles in the system. The mechanisms to realize these efficiencies are treated as independent (i.e., vehicle and network domains) and, when combined, they have not been adequately studied to date. This research aims to integrate previously developed and published research on Predictive Optimal Energy Management Strategies (POEMS) and Intelligent Traffic Systems (ITS), to address the need for quantifying improvement in system efficiency resulting from simultaneous vehicle and network optimization. POEMS and ITS are partially independent methods which do not require each other to function but whose individual effectiveness may be affected by the presence of the other. In order to evaluate the system level efficiency improvements, the Mobility Energy Productivity (MEP) metric is used. MEP specifically measures the connectedness of a system while accounting for time and energy externalities of modes that provide mobility in a given location. A SUMO model is developed to reflect real traffic patterns in Fort Collins, Colorado and data is collected by a probe SUMO vehicle which is validated against data collected on a real vehicle driving the same routes through the city. Individual vehicle and system level efficiencies are calculated using SUMO outputs for scenarios which integrate POEMS and ITS independently as well as jointly. Results from application of POEMS and ITS show improvement in energy consumption and travel times respectively when compared to the respective baseline scenarios. Our conclusion is that there are promising synergistic benefits to travel time and energy efficiency when POEMS and ITS are combined.

ADVANCED PROPULSION SYSTEMS↗

Oregon Offshore Wind Site Feasibility and Cost Study

The focus of this presentation is to: Reflect current floating wind technology trends and industry market data in cost models; Provide cost analysis in support of Oregon state energy planners considering floating offshore wind's potential contribution to future state energy supplies.

17 WIND ENERGY↗

Antiviral Strategies Against SARS-CoV-2: A Systems Biology Approach

The unprecedented scientific achievements in combating the COVID-19 pandemic reflect a global response informed by unprecedented access to data. We now have the ability to rapidly generate a diversity of information on an emerging pathogen and, by using high-performance computing and a systems biology approach, we can mine this wealth of information to understand the complexities of viral pathogenesis and contagion like never before. These efforts will aid in the development of vaccines, antiviral medications, and inform policymakers and clinicians. Here we detail computational protocols developed as SARS-CoV-2 began to spread across the globe. They include pathogen detection, comparative structural proteomics, evolutionary adaptation analysis via network and artificial intelligence methodologies, and multiomic integration. These protocols constitute a core framework on which to build a systems-level infrastructure that can be quickly brought to bear on future pathogens before they evolve into pandemic proportions.

Teixeira Prates, Erica↗

Empirical Relations between Size Parameters of Ice Hydrometeor Populations and Radar Reflectivity

Empirical power-law relations between the equivalent radar reflectivity factor Z e and the slope parameter of the gamma function Λ (i.e., Λ = cZ $^{d}_{e}$ used to describe ice hydrometeor size distributions) are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size, which is an important geophysical parameter describing the entire distribution. Two datasets from two-dimensional microphysical probes, collected during aircraft flights in subtropical and midlatitude regions, were used to obtain Λ by fitting measured size distributions. Reflectivity for different radar frequencies was calculated from microphysical probe data by using nonspherical-particle models. The derived relations have exponent d values that are approximately from -0.35 to -0.40, and the prefactors c are approximately between 30 and 55 (Λ: cm -1 ; Z e : mm 6 m -3 ). There is a tendency for d and c to decrease when radar frequency increases from K u band (~14 GHz) to W band (~94 GHz). Correlation coefficients between Z e and Λ can be very high (~0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC are due to a relatively high correlation between these two microphysical parameters. Finally, expected uncertainties in estimating Λ from reflectivity could be as high as a factor of 2, although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates.

54 ENVIRONMENTAL SCIENCES↗

Ka-Band ARM Zenith Radar Corrections (KAZRCOR, KAZRCFRCOR) Value-Added Products

The KAZRCOR Value -added Product (VAP) performs several corrections to the ingested KAZR moments and also creates a significant detection mask for each radar mode. The VAP computes gaseous attenuation as a function of time and radial distance from the radar antenna, based on ambient meteorological observations, and corrects observed reflectivities for that effect. KAZRCOR also dealiases mean Doppler velocities to correct velocities whose magnitudes exceed the radar’s Nyquist velocity. Input KAZR data fields are passed through into the KAZRCOR output files, in their native time and range coordinates. Complementary corrected reflectivity and velocity fields are provided, along with a mask of significant detections and a number of data quality flags. This report covers the KAZRCOR VAP as applied to the original KAZR radars and the upgraded KAZR2 radars. Currently there are two separate code bases for the different radar versions, but once KAZR and KAZR2 data formats are harmonized, only a single code base will be required.

54 ENVIRONMENTAL SCIENCES↗

Dynamical System Scaling of a Thermocline Thermal Storage System in the Thermal Energy Distribution System (TEDS) Facility

The purpose of this study was to develop a process to convert input signals from one facility into another by reflecting geometric and environmental settings. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility in development that aims to emulate the daily interactions among power production industry systems and be capable of receiving real-time data from those systems as inputs. To convert signals and ensure that the temporal sequences and magnitudes reflect the laboratory settings, the ability to scale and project data is essential. To demonstrate this ability, Dynamical System Scaling (a methodology that enables systems to scale and project or extrapolate datasets to desired environments while conserving the observed transient behavior based on first principles) was applied to DETAIL’s thermocline thermal storage system in the Thermal Energy Distribution System. The thermocline system was successfully scaled and a test case was conducted to generate a doubly accelerated energy charge and discharge in reference to past experimental data from the facility. The accelerated data were determined as able to conserve the amount of energy stored and the associated test boundary conditions were charge line maximum temperature, charge line velocity, and thermocline maximum temperature at 354 °C, 0.458 m/s, and 418 °C, respectively. The research results represented a case that required signals to be accelerated without altering the stored energy.

Yoshiura, Ramon (ORCID:0000000319781313)↗

NuSTAR J033202-2746.8: Direct constraints on the Compton reflection in a heavily obscured quasar at z ≈ 2

We report Nuclear Spectroscopic Telescope Array (NuSTAR) observations of NuSTAR J033202-2746.8, a heavily obscured, radio-loud quasar detected in the Extended Chandra Deep Field-South, the deepest layer of the NuSTAR extragalactic survey (∼400 ks, at its deepest). NuSTAR J033202-2746.8 is reliably detected by NuSTAR only at E > 8 keV and has a very flat spectral slope in the NuSTAR energy band (Γ=0.55{sub −0.64}{sup +0.62}; 3-30 keV). Combining the NuSTAR data with extremely deep observations by Chandra and XMM-Newton (4 Ms and 3 Ms, respectively), we constrain the broad-band X-ray spectrum of NuSTAR J033202-2746.8, indicating that this source is a heavily obscured quasar (N{sub H}=5.6{sub −0.8}{sup +0.9}×10{sup 23} cm{sup –2}) with luminosity L {sub 10-40} {sub keV} ≈ 6.4 × 10{sup 44} erg s{sup –1}. Although existing optical and near-infrared (near-IR) data, as well as follow-up spectroscopy with the Keck and VLT telescopes, failed to provide a secure redshift identification for NuSTAR J033202-2746.8, we reliably constrain the redshift z = 2.00 ± 0.04 from the X-ray spectral features (primarily from the iron K edge). The NuSTAR spectrum shows a significant reflection component (R=0.55{sub −0.37}{sup +0.44}), which was not constrained by previous analyses of Chandra and XMM-Newton data alone. The measured reflection fraction is higher than the R ∼ 0 typically observed in bright radio-loud quasars such as NuSTAR J033202-2746.8, which has L {sub 1.4} {sub GHz} ≈ 10{sup 27} W Hz{sup –1}. Constraining the spectral shape of active galactic nuclei (AGNs), including bright quasars, is very important for understanding the AGN population, and can have a strong impact on the modeling of the X-ray background. Our results show the importance of NuSTAR in investigating the broad-band spectral properties of quasars out to high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

3D Seismic Experimentation and Advanced Processing/Inversion Development for Investigations of the Shallow Subsurface

The work plan for this project was to develop and apply advanced seismic reflection and wide-angle processing and inversion techniques to high resolution seismic data for the shallow subsurface to seismically characterize the shallow subsurface at hazardous waste sites as an aid to containment and cleanup activities. We proposed to continue work on seismic data that we had already acquired under a previous DoE grant, as well as to acquire additional new datasets for analysis. The project successfully developed and/or implemented the use of 3D reflection seismology algorithms, waveform tomography and finite-frequency tomography using compressional and shear waves for high resolution characterization of the shallow subsurface at two waste sites. These two sites have markedly different near-surface structures, groundwater flow patterns, and hazardous waste problems. This is documented in the list of refereed documents, conference proceedings, and Rice graduate theses, listed below.

54 ENVIRONMENTAL SCIENCES↗

Nevada Great Basin Play Fairway Analysis - Steptoe Valley

All datasets and products specific to the Steptoe Valley model area. Includes a packed ArcMap project (.mpk), individually zipped shapefiles, and a file geodatabase for the northern Steptoe Valley area; a GeoSoft Oasis montaj project containing GM-SYS 2D gravity profiles along the trace of our seismic reflection lines; a 3D model in EarthVision; spreadsheet of links to published maps; and spreadsheets of well data.

15 GEOTHERMAL ENERGY↗

Critical and subcritical mass computations for {sup 247}Cm - 14378

Experimental nuclear criticality data are unavailable for many special actinides so subcritical limits are established using computations and conservative practices. Computations are done using codes in the SCALE6.1 system and the MCNP6, version 1.0, Monte Carlo code with cross sections based on Evaluated Nuclear Data File (ENDF) B-VI, B-VII.0, and B-VII.1 data. Both SCALE multigroup and MCNP continuous energy cross sections are used to estimate critical masses of unreflected, stainless steel reflected, and water reflected spherical {sup 247}Cm metal/water systems. For well moderated systems the critical masses derived using ENDF/B-VII data are about half those previously reported. The difference appears to be caused by changes in the ENDF/B-VII fission cross sections and an overall increase in the value of ν-bar. Subcritical mass limits are derived based on the critical mass estimates. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Robust error calibration for serial crystallography

Serial crystallography is an important technique with unique abilities to resolve enzymatic transition states, minimize radiation damage to sensitive metalloenzymes and perform de novo structure determination from micrometre-sized crystals. This technique requires the merging of data from thousands of crystals, making manual identification of errant crystals unfeasible. cctbx.xfel.merge uses filtering to remove problematic data. However, this process is imperfect, and data reduction must be robust to outliers. We add robustness to cctbx.xfel.merge at the step of uncertainty determination for reflection intensities. This step is a critical point for robustness because it is the first step where the data sets are considered as a whole, as opposed to individual lattices. Robustness is conferred by reformulating the error-calibration procedure to have fewer and less stringent statistical assumptions and incorporating the ability to down-weight low-quality lattices. We then apply this method to five macromolecular XFEL data sets and observe the improvements to each. The appropriateness of the intensity uncertainties is demonstrated through internal consistency. This is performed through theoretical CC 1/2 and I /σ relationships and by weighted second moments, which use Wilson's prior to connect intensity uncertainties with their expected distribution. This work presents new mathematical tools to analyze intensity statistics and demonstrates their effectiveness through the often underappreciated process of uncertainty analysis.

Mittan-Moreau, David W.↗

Development of a Life Cycle Inventory of Water Consumption Associated with the Production of Transportation Fuels

The production of all forms of energy consumes water. To meet increased energy demands, it is essential to quantify the amount of water consumed in the production of different forms of energy. By analyzing the water consumed in different technologies, it is possible to identify areas for improvement in water conservation and reduce water stress in energy-producing regions. The transportation sector is a major consumer of energy in the United States. Because of the relationships between water and energy, the sustainability of transportation is tied to management of water resources. Assessment of water consumption throughout the life cycle of a fuel is necessary to understand its water resource implications. To perform a comparative life cycle assessment of transportation fuels, it is necessary first to develop an inventory of the water consumed in each process in each production supply chain. The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model is an analytical tool that can used to estimate the full life-cycle environmental impacts of various transportation fuel pathways from wells to wheels. GREET is currently being expanded to include water consumption as a sustainability metric. The purpose of this report was to document data sources and methodologies to estimate water consumption factors (WCF) for the various transportation fuel pathways in GREET. WCFs reflect the quantity of freshwater directly consumed per unit production for various production processes in GREET. These factors do not include consumption of precipitation or low-quality water (e.g., seawater) and reflect only water that is consumed (i.e., not returned to the source from which it was withdrawn). The data in the report can be combined with GREET to compare the life cycle water consumption for different transportation fuels.

energy-water nexus↗

The effect of lighting environment on task performance in buildings – A review

The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ka-Band ARM Zenith Radar Corrections (KAZRCOR, KAZRCFRCOR) Value-Added Products

The Ka-Band Atmospheric Radiation Measurement (ARM) Zenith Radar Corrections (KAZRCOR) and KA-Band ARM Zenith Radar CF-Radial, Corrected (KAZRCFRCOR) value-added products (VAPs) perform several corrections to the ingested KAZR moments and also create a significant detection mask for each radar mode. The VAPs compute gaseous attenuation as a function of time and radial distance from the radar antenna, based on ambient meteorological observations, and correct observed reflectivities for that effect. Mean Doppler velocities are dealiased to correct velocities whose magnitudes exceed the radar’s Nyquist velocity. Input KAZR data fields are passed through to the KAZRCOR or KAZRCFRCOR output files, in their native time and range coordinates. Complementary corrected reflectivity and velocity fields are provided, along with a mask of significant detections and a number of data quality flags. This report covers the KAZRCOR VAP as applied to the original KAZR radars and the upgraded KAZR2 radars. Originally, prior to late 2019, there were two separate code bases for the different radar versions. Following the harmonization of KAZR and KAZR2 data formats in 2019, only a single code base is required. The new combined KAZR and KAZR2 code base is called the KAZRCFRCOR VAP. The ‘cfr portion of the VAP name refers to the Radial Climate and Forecasting data format standards that are used in these data sets. Throughout this report, references to ‘KAZRCOR’ should be taken to apply to the ‘KAZRCFRCOR’ VAP as well unless there is an explicit statement to the contrary.

54 ENVIRONMENTAL SCIENCES↗

Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Mapping canopy photosynthesis in both high spatial and temporal resolution is essential for carbon cycle monitoring in heterogeneous areas. However, well established satellites in sun-synchronous orbits such as Sentinel-2, Landsat and MODIS can only provide either high spatial or high temporal resolution but not both. Recently established CubeSat satellite constellations have created an opportunity to overcome this resolution trade-off. In particular, Planet Fusion allows full utilization of the CubeSat data resolution and coverage while maintaining high radiometric quality. In this study, we used the Planet Fusion surface reflectance product to calculate daily, 3-m resolution, gap-free maps of the near-infrared radiation reflected from vegetation (NIRvP). We then evaluated the performance of these NIRvP maps for estimating canopy photosynthesis by comparing with data from a flux tower network in Sacramento-San Joaquin Delta, California, USA. Overall, NIRvP maps captured temporal variations in canopy photosynthesis of individual sites, despite changes in water extent in the wetlands and frequent mowing in the crop fields. When combining data from all sites, however, we found that robust agreement between NIRvP maps and canopy photosynthesis could only be achieved when matching NIRvP maps to the flux tower footprints. In this case of matched footprints, NIRvP maps showed considerably better performance than in situ NIRvP in estimating canopy photosynthesis both for daily sum and data around the time of satellite overpass (R2 = 0.78 vs. 0.60, for maps vs. in situ for the satellite overpass time case). This difference in performance was mostly due to the higher degree of consistency in slopes of NIRvP-canopy photosynthesis relationships across the study sites for flux tower footprint-matched maps. Our results show the importance of matching satellite observations to the flux tower footprint and demonstrate the potential of CubeSat constellation imagery to monitor canopy photosynthesis remotely at high spatio-temporal resolution.

54 ENVIRONMENTAL SCIENCES↗

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

Studying Transient Phenomena in Thin Films with Reinforcement Learning

Neutron reflectometry has long been a powerful tool to study the interfacial properties of energy materials. Recently, time-resolved neutron reflectometry has been used to better understand transient phenomena in electrochemical systems. Those measurements often comprise a large number of reflectivity curves acquired over a narrow q range, with each individual curve having lower information content compared to a typical steady-state measurement. In this work, we present an approach that leverages existing reinforcement learning tools to model time-resolved data to extract the time evolution of structure parameters. Further, by mapping the reflectivity curves taken at different times as individual states, we use the Soft Actor-Critic algorithm to optimize the time series of structure parameters that best represent the evolution of an electrochemical system. We show that this approach constitutes an elegant solution to the modeling of time-resolved neutron reflectometry data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗