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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Millimeter-wave imaging diagnostics systems on the EAST tokamak (invited)

Millimeter-wave imaging diagnostics, with large poloidal span and wide radial range, have been developed on the EAST tokamak for visualization of 2D electron temperature and density fluctuations. A 384 channel (24 poloidal × 16 radial) Electron Cyclotron Emission Imaging (ECEI) system in F-band (90-140 GHz) was installed on the EAST tokamak in 2012 to provide 2D electron temperature fluctuation images with high spatial and temporal resolution. A co-located Microwave Imaging Reflectometry (MIR) will be installed for imaging of density fluctuations by December 2016. This “4th generation” MIR system has eight independent frequency illumination beams in W-band (75-110 GHz) driven by fast tuning synthesizers and active multipliers. Both of these advanced millimeter-wave imaging diagnostic systems have applied the latest techniques. A novel design philosophy “general optics structure” has been employed for the design of the ECEI and MIR receiver optics with large aperture. The extended radial and poloidal coverage of ECEI on EAST is made possible by innovations in the design of front-end optics. The front-end optical structures of the two imaging diagnostics, ECEI and MIR, have been integrated into a compact system, including the ECEI receiver and MIR transmitter and receiver. Two imaging systems share the same mid-plane port for simultaneous, co-located 2D fluctuation measurements of electron density and temperature. An intelligent remote-control is utilized in the MIR electronics systems to maintain focusing at the desired radial region even with density variations by remotely tuning the probe frequencies in about 200 μs. A similar intelligent technique has also been applied on the ECEI IF system, with remote configuration of the attenuations for each channel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Measuring the soot onset temperature in high-pressure n-dodecane spray pyrolysis

In this paper, soot formation in pyrolyzing sprays of n-dodecane is visualized and quantified in a high-pressure, high-temperature, constant-volume spray chamber at 38 bar, 76 bar, and 114 bar. Sprays of n-dodecane are injected at 500 bar from a single-hole, 186-µm orifice diameter fuel injector. We quantify the temporal evolution of the soot optical thickness and the total soot mass formed in the pyrolyzing sprays using a high-speed extinction imaging diagnostic. The vessel ambient temperature and pressure are varied independently to identify the soot onset temperature for n-dodecane pyrolysis. Linear extrapolation of the maximum soot formation rates as a function of ambient temperature reveals a soot onset temperature near 1450 K. Finally, the onset temperature determined here for n-dodecane is within 50 K of those previously measured along the centerline of atmospheric pressure coflow diffusion flames for smaller alkane fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Elevation distributed micro-climatology data in a coastal glaciated watershed

Air temperature, ground temperature and relative humidity data were collected in a longitudinal transect of the Nooksack watershed at varying elevations from 500 to 1800 m above sea level. Data were collected by anchoring sensors from trees above winter snow levels and shaded from direct solar radiation. Paired sensors were also buried 3 cm under ground near each air temperature sensor to determine snow absence or presence. Select sites included relative humidity sensors to indicate whether precipitation was occurring. Data were collected every 3-4 h from December 2015 to Sept 2018 (with ongoing collection). Code for analysis of daily mean, minimum, maximum, and temperature change with elevation (lapse rates) are available on Github (https://doi.org/10.5281/zenodo.3239539). The sensor download and intermediate data products are available on HydroShare at (http://www.hydroshare.org/resource/222e832d3df24dea9bae9bbeb6f4219d) with publicly accessible visualization available from the Nooksack Observatory at data.cuahsi.org. Hydrologic models are generally structured with a single annual average lapse rate parameter which assumes a linear temperature gradient with elevation. The daily data (2016-2018) is used as part of ongoing studies on the non-linear dynamics and temporal variability of temperature with elevation to improve assessments of watershed function and salmon habitat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Visualizing spatiotemporal pulse propagation: first-order spatiotemporal couplings in laser pulses

Even though a general theory of first-order spatiotemporal couplings exists in the literature, it is often difficult to visualize how these distortions affect laser pulses. In particular, it is difficult to show the spatiotemporal phase of pulses in a meaningful way. We propose a general solution to plotting the electric fields of pulses in three-dimensional space that intuitively shows the effects of spatiotemporal phases. The temporal phase information is color-coded using spectrograms and color response functions, and the beam is propagated to show the spatial phase evolution. In using this plotting technique, we generate two- and three-dimensional images and movies that show the effects of spatiotemporal couplings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗
DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

MO-FG-202-08: Real-Time Monte Carlo-Based Treatment Dose Reconstruction and Monitoring for Radiotherapy

Purpose: This proof-of-concept study is to develop a real-time Monte Carlo (MC) based treatment-dose reconstruction and monitoring system for radiotherapy, especially for the treatments with complicated delivery, to catch treatment delivery errors at the earliest possible opportunity and interrupt the treatment only when an unacceptable dosimetric deviation from our expectation occurs. Methods: First an offline scheme is launched to pre-calculate the expected dose from the treatment plan, used as ground truth for real-time monitoring later. Then an online scheme with three concurrent threads is launched while treatment delivering, to reconstruct and monitor the patient dose in a temporally resolved fashion in real-time. Thread T1 acquires machine status every 20 ms to calculate and accumulate fluence map (FM). Once our accumulation threshold is reached, T1 transfers the FM to T2 for dose reconstruction ad starts to accumulate a new FM. A GPU-based MC dose calculation is performed on T2 when MC dose engine is ready and a new FM is available. The reconstructed instantaneous dose is directed to T3 for dose accumulation and real-time visualization. Multiple dose metrics (e.g. maximum and mean dose for targets and organs) are calculated from the current accumulated dose and compared with the pre-calculated expected values. Once the discrepancies go beyond our tolerance, an error message will be send to interrupt the treatment delivery. Results: A VMAT Head-and-neck patient case was used to test the performance of our system. Real-time machine status acquisition was simulated here. The differences between the actual dose metrics and the expected ones were 0.06%–0.36%, indicating an accurate delivery. ∼10Hz frequency of dose reconstruction and monitoring was achieved, with 287.94s online computation time compared to 287.84s treatment delivery time. Conclusion: Our study has demonstrated the feasibility of computing a dose distribution in a temporally resolved fashion in real-time and quantitatively and dosimetrically monitoring the treatment delivery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A high quantum yield molecule-protein complex fluorophore for near-infrared II imaging

Fluorescence imaging in the second near-infrared window (NIR-II) allows visualization of deep anatomical features with an unprecedented degree of clarity. NIR-II fluorophores draw from a broad spectrum of materials spanning semiconducting nanomaterials to organic molecular dyes, yet unfortunately all water-soluble organic molecules with 41,000 nm emission suffer from low quantum yields that have limited temporal resolution and penetration depth. We report tailoring the supramolecular assemblies of protein complexes with a sulfonated NIR-II organic dye (CH-4T) to produce a brilliant 110-fold increase in fluorescence, resulting in the highest quantum yield molecular fluorophore thus far. The bright molecular complex allowed for the fastest video-rate imaging in the second NIR window with B50-fold reduced exposure times at a fast 50 frames-per-second (FPS) capable of resolving mouse cardiac cycles. Additionally, we demonstrate that the NIR-II molecular complexes are superior to clinically approved ICG for lymph node imaging deep within the mouse body.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A detailed study of the barium central star of the planetary nebula Abell 70

ABSTRACT We present a detailed study of the barium star at the heart of the planetary nebula Abell 70. Time-series photometry obtained over a period of more than 10 yr demonstrates that the barium-contaminated companion is a rapid rotator with temporal variability due to spots. The amplitude and phasing of the photometric variability change abruptly; however, there is no evidence for a change in the rotation period (P = 2.06 d) over the course of the observations. The co-addition of 17 high-resolution spectra obtained with Ultraviolet and Visual Échelle Spectrograph mounted on the Very Large Telescope allows us to measure the physical and chemical properties of the companion, confirming it to be a chromospherically active, late G-type sub-giant with more than +1 dex of barium enhancement. We find no evidence of radial velocity variability in the spectra, obtained over the course of approximately 130 d with a single additional point some 8 yr later, with the radial velocities of all epochs approximately −10 km s −1 from the previously measured systemic velocity of the nebula. This is perhaps indicative that the binary has a relatively long period (P ≳ 2 yr) and high eccentricity (e ≳ 0.3), and that all the observations were taken around radial velocity minimum. However, unless the binary orbital plane is not aligned with the waist of the nebula or the systemic velocity of the binary is not equal to the literature value for the nebula, this would imply an unfeasibly large mass for the nebular progenitor.

Jones, David (ORCID:0000000339475946)↗
DOE OSTI2023

Interpretation of Fracture Initiation Points by In-Well Low-Frequency Distributed Acoustic Sensing in Horizontal Wells

Summary Low-frequency distributed acoustic sensing (LF-DAS) exploits the optical phase shift of Rayleigh backscatter in fiber-optic cables to obtain distributed measurements of changes in strain and temperature. Fiber-optic cables are often installed for multistage hydraulic fracture diagnostics in horizontal wells. LF-DAS in an untreated well provides far-field strain measurements, while offset wells are hydraulically fractured. Such a configuration is called crosswell LF-DAS sensing. Crosswell LF-DAS measurements have proved useful in diagnosing fracture hits, fracture azimuth, planarity, cluster efficiency, fracture propagation rates, and the dynamic distance to the fracture front. In contrast, in-well LF-DAS is conducted on the actively fractured well. Due to cool fracture fluid being injected at high injection rates, the strain component of the LF-DAS response is largely obscured by temperature changes. In permanent fiber-optic cable installations, distributed temperature sensing (DTS) is often conducted simultaneously with LF-DAS. An opportunity exists to decouple the temperature and strain components of LF-DAS sensors to observe strain changes on in-well LF-DAS. The LF-DAS response is modeled as linearly dependent on strain and temperature changes. Theoretical LF-DAS temperature and strain sensitivity coefficients are derived based on the changes to the index of refraction and length of the fiber. Using the DTS measurements, temperature changes are computed, smoothed, filtered, and compared to the LF-DAS response. Crossplots of the in-well LF-DAS measurements and temperature changes from DTS measurements far from the actively fractured region are used to validate the theoretical sensitivity coefficients. Uncertainty in the temperature component of the LF-DAS response is quantified. The difficulty in corresponding the different spatial and temporal resolutions of the DTS and LF-DAS measurements is overcome by comparing the responses over a moving temporal and spatial window. If the LF-DAS response at the center of the window agrees with the DTS response within uncertainty, the measurement is filtered out. After filtering, the remaining nonzero in-well LF-DAS measurements are due to changes in strain. The data are then visualized in waterfall plots. The results indicate that the theoretical and observed strain and temperature coefficients agree within 10%. After the temperature component of the in-well LF-DAS response is extracted, the remaining nonzero measurements are located primarily within the actively treated region. Locations with peaks in the strain response are interpreted to indicate fracture initiation points. These fracture initiation points are compared with in-well DTS and high-frequency DAS noise measurements across multiple stages to better understand fracture initiation along the horizontal well.

Engineering↗
DOE OSTI2020

How “hot” are hotspots: Statistically localizing the high-activity areas on soil and rhizosphere images

The topic of microbial hotspots in soil requires not only visualizing their spatial distribution and biochemical analyses, but also statistical approaches to identify these hotspots and separate them from the surrounding activities (background). We hypothesized that each hotspot type (e.g. enzyme activities in the rhizosphere, root exudation, localization of herbicide accumulation) is a result of local process driven by biotic and/or abiotic factors, and the process rates in the hotspots are much faster than those in the soil background. We further hypothesized that the background and hotspot activities in soil belong to different statistical distributions. Consequently, hotspot determination should be based on statistical separation of activities significantly higher than the background. We analyzed for the statistical distributions of grey values on three groups of published images: 1) 14 C images of carbon input by roots into the rhizosphere, 2) 14 C glyphosate accumulation in the plant, and 3) zymogram of leucine aminopeptidase activity in rooted soil. The two Gaussian distributions were fit (the first representing the background, the second the hotspots) to the distribution of grey values in the images, the parameters (means and standard deviations, SD) of the fitted distributions were calculated, and the background was removed. Thus, we identified hotspots as areas outside of the Mean+2SD image intensity (corresponding to the upper ~ 2.5% of activity, being over 97.5% of background values) and finally, visualized images of solely hotspot locations. Finally, these results were compared with previously used decisions on hotspot intensity thresholding (i.e. Top-25% and 17 standard thresholding approaches in ImageJ) and discussed the advantages of the Mean+2SD as well as Mean+3SD approaches. These advantages include: i) simple unification of the thresholding approach for several imaging methods with various principles of activity distribution, ii) identification of hotspots with various activity levels, iii) analysis of “time-specific” hotspots in temporal sequences of images. Compared with 17 standard thresholding methods, we concluded that objectively elucidating and separating the hotspots should be based on statistical distribution analysis, e.g. using the Mean+2SD or Mean+3SD approaches. Furthermore, this simple Mean+2SD approach delivered suitable results for three groups of images and so, helps to understand the processes responsible for the highest activities and elucidate hotspots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Spatial and Temporal Variations in Characteristic Ratios of Elemental Carbon to Carbon Monoxide and Nitrogen Oxides across the United States

Here, a ratio-based method is used to characterize anthropogenic elemental carbon (EC a ) using in situ measurements and emissions of carbon monoxide (CO) and nitrogen oxides (NO x ). We use long-term records of ground-based measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System and Interagency Monitoring of Protected Visual Environments to assess the patterns in anthropogenic combustion ratios (ΔEC a /ΔCO and ΔEC a /ΔNO x ) across the U.S. Petroleum Administration for Defense Districts (PADD) regions for the years 2000-2015. We investigate the change in these ratios between the periods 2000-2007 and 2008-2015. Overall, ΔEC a /ΔCO ratios increase by 0.7-82% and ΔEC a /ΔNO x by 6.8-104% across the East and West PADD regions. The urban West showed the largest increase relative to other regions. This is mainly attributed to a 13-23% increase in ΔEC a during the winter and fall seasons and significant reductions in urban ΔNO x (except in winter). We also find that emission ratios derived from the EPA's National Emission Inventory (NEI) overestimate (underestimate) the increase in the observed enhancement ratios in the East (West). Analyses of changes in NEI emissions in the West reveal (a) smaller reductions in NEI emissions for NO x from the off-road sector and (b) an increase in PM 2.5 (particulate matter 2.5 μm or less in diameter) emissions from commercial/residential combustion and smaller reductions in nonroad emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

DeepZipper. II. Searching for Lensed Supernovae in Dark Energy Survey Data with Deep Learning

Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain 5–10 LSNe in total while next-generation experiments are expected to contain several hundred to a few thousand of these systems. We search for these systems in observed Dark Energy Survey (DES) five year SN fields—10 3 sq. deg. regions of sky imaged in the griz bands approximately every six nights over five years. To perform the search, we utilize the DeepZipper approach: a multi-branch deep learning architecture trained on image-level simulations of LSNe that simultaneously learns spatial and temporal relationships from time series of images. We find that our method obtains an LSN recall of 61.13% and a false-positive rate of 0.02% on the DES SN field data. DeepZipper selected 2245 candidates from a magnitude-limited (m i < 22.5) catalog of 3,459,186 systems. We employ human visual inspection to review systems selected by the network and find three candidate LSNe in the DES SN fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Energetic particle transport and loss induced by helically-trapped energetic-ion-driven resistive interchange modes in the Large Helical Device

Here, energetic-ion confinement and loss due to energetic-ion driven magnetohydrodynamic modes are studied using comprehensive neutron diagnostics and orbit-following numerical simulations for the Large Helical Device (LHD). The neutron flux monitor is employed in order to obtain global confinement of energetic ions and two installed vertical neutron cameras (VNCs) viewing different poloidal cross-sections are utilized in order to measure the radial profile of energetic ions. A strong helically-trapped energetic-ion-driven resistive interchange mode (EIC) excited in relatively low-density plasma terminated high-temperature state in LHD. Changes in the neutron emission profile due to the EIC excitation are clearly visualized by the VNCs. The reduction in the neutron signal for the helical ripple valley increases with EIC amplitude, which reaches approximately 50%. In addition to the EIC experiment, orbit-following simulations using the DELTA5D code with EIC fluctuations were performed to assess the energetic-ion transport and loss. Two-dimensional temporal evolution results show that the neutron emissivity at the helical ripple decreases significantly due to the EIC. The rapid reduction in neutron emissivity shows that the helically-trapped beam ions immediately escape from the plasma. The reduction in the VNC signals for the helical ripple valley and the total neutron emission rate increase with increasing EIC amplitude, as observed in the experiment. Calculated line-integrated neutron emission results show that the profile measured by VNC1 has one peak, whereas the profile measured by VNC2 has two peaks, as observed in the experiment. Although the neutron emission profile for VNC2 has a relatively wide peak compared with the experimental results, the significant decrease in neutron signal corresponding to the helical ripple valley was successfully reproduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Electronic interactions in Dirac fluids visualized by nano-terahertz spacetime interference of electron-photon quasiparticles

Ultraclean graphene at charge neutrality hosts a quantum critical Dirac fluid of interacting electrons and holes. Interactions profoundly affect the charge dynamics of graphene, which is encoded in the properties of its electron-photon collective modes: surface plasmon polaritons (SPPs). Here, we show that polaritonic interference patterns are particularly well suited to unveil the interactions in Dirac fluids by tracking polaritonic interference in time at temporal scales commensurate with the electronic scattering. Spacetime SPP interference patterns recorded in terahertz (THz) frequency range provided unobstructed readouts of the group velocity and lifetime of polariton that can be directly mapped onto the electronic spectral weight and the relaxation rate. Our data uncovered prominent departures of the electron dynamics from the predictions of the conventional Fermi-liquid theory. The deviations are particularly strong when the densities of electrons and holes are approximately equal. The proposed spacetime imaging methodology can be broadly applied to probe the electrodynamics of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗
DOE OSTI2021

Multiscale Patterning from Competing Interactions and Length Scales

We live in an era of complexity marked by impressive new tools powering the scientific method to accelerate discovery, prediction, and control of increasingly complex systems. In common with many disciplines and societal challenges and opportunities, materials and condensed matter sciences are beneficiaries. The volume and fidelity of experimental, computational, and visualization data available, and tools to rapidly interpret them, are remarkable. Conceptual frameworks, including multiscale, multiphysics modeling of this complexity, are fueled by the data and, in turn, guide directions for future experimental and computational strategies. In this spirit, we discuss the importance of competing interactions, length scales, and constraints as pervasive sources of spatio-temporal complexity. We use representative examples drawn from materials and condensed matter, including the important role of elasticity in some technologically important quantum materials.

36 MATERIALS SCIENCE↗