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DOE OSTI2018

Cooling rate dependence of structural order in Ni 62 Nb 38 metallic glass

In this article, molecular dynamics (MD) simulations are performed to study the structure of Ni 62 Nb 38 bulk metallic glass at the atomistic level. Structural analysis based on the cluster alignment method is carried out and a new Ni-centered distorted-icosahedra (DISICO) motif is excavated. We show that the short-range order and medium-range order in the glass are enhanced with lower cooling rate. Almost 50% of the clusters around the Ni atoms in the well-annealed Ni 62 Nb 38 glass sample from our MD simulations can be classified as DISICO. It is revealed that the structural distortion with respect to the perfect icosahedra is driven by chemical ordering in the distorted region of the DISICO motif. The relationship between the structure, energy, and dynamics in this glass-forming alloy during the cooling and annealing processes is also established.

36 MATERIALS SCIENCE↗
DOE OSTI2015

STAR FORMATION ACROSS THE W3 COMPLEX

We present a multi-wavelength analysis of the history of star formation in the W3 complex. Using deep, near-infrared ground-based images combined with images obtained with Spitzer and Chandra observatories, we identified and classified young embedded sources. We identified the principal clusters in the complex and determined their structure and extension. We constructed extinction-limited samples for five principal clusters and constructed K-band luminosity functions that we compare with those of artificial clusters with varying ages. This analysis provided mean ages and possible age spreads for the clusters. We found that IC 1795, the centermost cluster of the complex, still hosts a large fraction of young sources with circumstellar disks. This indicates that star formation was active in IC 1795 as recently as 2 Myr ago, simultaneous to the star-forming activity in the flanking embedded clusters, W3-Main and W3(OH). A comparison with carbon monoxide emission maps indicates strong velocity gradients in the gas clumps hosting W3-Main and W3(OH) and shows small receding clumps of gas at IC 1795, suggestive of rapid gas removal (faster than the T Tauri timescale) in the cluster-forming regions. We discuss one possible scenario for the progression of cluster formation in the W3 complex. We propose that early processes of gas collapse in the main structure of the complex could have defined the progression of cluster formation across the complex with relatively small age differences from one group to another. However, triggering effects could act as catalysts for enhanced efficiency of formation at a local level, in agreement with previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

CLASH: NEW MULTIPLE IMAGES CONSTRAINING THE INNER MASS PROFILE OF MACS J1206.2-0847

We present a strong-lensing analysis of the galaxy cluster MACS J1206.2-0847 (z = 0.44) using UV, Optical, and IR, HST/ACS/WFC3 data taken as part of the CLASH multi-cycle treasury program, with VLT/VIMOS spectroscopy for some of the multiply lensed arcs. The CLASH observations, combined with our mass model, allow us to identify 47 new multiply lensed images of 12 distant sources. These images, along with the previously known arc, span the redshift range 1 {approx}< z {approx}< 5.5, and thus enable us to derive a detailed mass distribution and to accurately constrain, for the first time, the inner mass profile of this cluster. We find an inner profile slope of dlog {Sigma}/dlog {theta} {approx_equal} -0.55 {+-} 0.1 (in the range [1'', 53''], or 5 kpc {approx}< r {approx}< 300 kpc), as commonly found for relaxed and well-concentrated clusters. Using the many systems uncovered here we derive credible critical curves and Einstein radii for different source redshifts. For a source at z{sub s} {approx_equal} 2.5, the critical curve encloses a large area with an effective Einstein radius of {theta}{sub E} = 28'' {+-} 3'', and a projected mass of (1.34 {+-} 0.15) Multiplication-Sign 10{sup 14} M{sub Sun }. From the current understanding of structure formation in concordance cosmology, these values are relatively high for clusters at z {approx} 0.5, so that detailed studies of the inner mass distribution of clusters such as MACS J1206.2-0847 can provide stringent tests of the {Lambda}CDM paradigm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

LoCuSS: A DYNAMICAL ANALYSIS OF X-RAY ACTIVE GALACTIC NUCLEI IN LOCAL CLUSTERS

We present a study of the distribution of X-ray active galactic nuclei (AGNs) in a representative sample of 26 massive clusters at 0.15 < z < 0.30, combining Chandra observations sensitive to X-ray point sources of luminosity L{sub X} {approx} 10{sup 42} erg s{sup -1} at the cluster redshift with extensive and highly complete spectroscopy of cluster members down to {approx}M*{sub K} + 2. In total we identify 48 X-ray AGNs among the cluster members, with luminosities 2 Multiplication-Sign 10{sup 41}-1 Multiplication-Sign 10{sup 44} erg s{sup -1}. Based on these identifications, we estimate that 0.73% {+-} 0.14% of cluster galaxies brighter than M{sub K} = -23.1 (M*{sub K} + 1.5) host an X-ray AGN with L{sub X} > 10{sup 42} erg s{sup -1}. In the stacked caustic diagram that shows (v{sub los} - (v))/{sigma}{sub v} versus r{sub proj}/r{sub 500}, the X-ray AGN appear to preferentially lie along the caustics, suggestive of an infalling population. They also appear to avoid the region with lowest cluster-centric radii and relative velocities (r{sub proj} < 0.4r{sub 500}; |v - (v)|/{sigma}{sub v} < 0.8), which is dominated by the virialized population of galaxies accreted earliest into the clusters. The line-of-sight velocity histogram of the X-ray AGN shows a relatively flat distribution, and is inconsistent with the Gaussian distribution expected for a virialized population at 98.9% confidence. Moreover, the velocity dispersion of the 48 X-ray AGNs is 1.51 times that of the overall cluster population, which is consistent with the {radical}2 ratio expected by simple energetic arguments when comparing infalling versus virialized populations. This kinematic segregation is significant at the 4.66{sigma} level. When splitting the X-ray AGN sample into two according to X-ray or infrared (IR) luminosity, both X-ray bright (L{sub X} > 10{sup 42}) and IR-bright (L{sub TIR} > 2 Multiplication-Sign 10{sup 10} L{sub Sun }) subsamples show higher velocity dispersions than their X-ray dim and IR-dim counterparts at >2{sigma} significance. This is consistent with the nuclear activity responsible for the X-ray and IR emission being slowly shut down as the host galaxies are accreted into the cluster. Overall, our results provide the strongest observational evidence to date that X-ray AGNs found in massive clusters are an infalling population, and that the cluster environment very effectively suppresses radiatively efficient nuclear activity in its member galaxies. These results are consistent with the view that for galaxies to host an X-ray AGN they should be the central galaxy within their dark matter halo and have a ready supply of cold gas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Bias due to neutrinos must not uncorrect'd go

It is a well known fact that galaxies are biased tracers of the distribution of matter in the Universe. The galaxy bias is usually factored as a function of redshift and scale, and approximated as being scale-independent on large, linear scales. In cosmologies with massive neutrinos, the galaxy bias defined with respect to the total matter field (cold dark matter, baryons, and non-relativistic neutrinos) also depends on the sum of the neutrino masses M ν , and becomes scale-dependent even on large scales. This effect has been usually neglected given the sensitivity of current surveys. Yet, it becomes a severe systematic for future surveys aiming to provide the first detection of non-zero M ν . The effect can be corrected for by defining the bias with respect to the density field of cold dark matter and baryons, rather than the total matter field. In this work, we provide a simple prescription for correctly mitigating the neutrino-induced scale-dependent bias effect in a practical way. We clarify a number of subtleties regarding how to properly implement this correction in the presence of redshift-space distortions and non-linear evolution of perturbations. We perform a Markov Chain Monte Carlo analysis on simulated galaxy clustering data that match the expected sensitivity of the Euclid survey. We reveal that the neutrino-induced scale-dependent bias can lead to important shifts in both the inferred mean value of M ν , as well as its uncertainty, and provide an analytical explanation for the magnitude of the shifts. We show how these shifts propagate to the inferred values of other cosmological parameters correlated with M ν , such as the cold dark matter physical density Ω cdm h 2 and the scalar spectral index n s . In the end, we find that correctly accounting for the neutrino-induced scale-dependent bias will be of crucial importance for future galaxy clustering analyses. We encourage the cosmology community to correctly account for this effect using the simple prescription we present in our work. The tools necessary to easily correct for the neutrino-induced scale-dependent bias will be made publicly available in an upcoming release of the Boltzmann solver CLASS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. Here, the explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973) tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

A HIGHLY ELONGATED PROMINENT LENS AT z = 0.87: FIRST STRONG-LENSING ANALYSIS OF EL GORDO

We present the first strong-lensing (SL) analysis of the galaxy cluster ACT-CL J0102-4915 (El Gordo), in recent HST/ACS images, revealing a prominent strong lens at a redshift of z = 0.87. This finding adds to the already-established unique properties of El Gordo: it is the most massive, hot, X-ray luminous, and bright Sunyaev-Zeldovich effect cluster at z {approx}> 0.6, and the only {sup b}ullet{sup -}like merging cluster known at these redshifts. The lens consists of two merging massive clumps, where, for a source redshift of z{sub s} {approx} 2, each clump exhibits only a small, separate critical area, with a total area of 0.69 {+-} 0.11{open_square}' over the two clumps. For a higher source redshift, z{sub s} {approx} 4, the critical curves of the two clumps merge together into one bigger and very elongated lens (axis ratio {approx_equal} 5.5), enclosing an effective area of 1.44 {+-} 0.22{open_square}'. The critical curves continue expanding with increasing redshift so that for high-redshift sources (z{sub s} {approx}> 9) they enclose an area of {approx}1.91 {+-} 0.30{open_square}' (effective {theta}{sub e} {approx_equal} 46.''8 {+-} 3.''7) and a mass of 6.09 {+-} 1.04 Multiplication-Sign 10{sup 14} M{sub Sun }. According to our model, the area of high magnification ({mu} > 10) for such high-redshift sources is {approx_equal}1.2{open_square}', and the area with {mu} > 5 is {approx_equal}2.3{open_square}', making El Gordo a compelling target for studying the high-redshift universe. We obtain a strong lower limit on the total mass of El Gordo, {approx}> 1.7 Multiplication-Sign 10{sup 15} M{sub Sun} from the SL regime alone, suggesting a total mass of roughly M{sub 200} {approx} 2.3 Multiplication-Sign 10{sup 15} M{sub Sun }. Our results should be revisited when additional spectroscopic and HST imaging data are available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

HH 1158: THE LOWEST LUMINOSITY EXTERNALLY IRRADIATED HERBIG–HARO JET

We have identified a new externally irradiated Herbig–Haro (HH) jet, HH 1158, within ∼2 pc of the massive OB type stars in the σ Orionis cluster. At an L{sub bol} ∼ 0.1 L{sub ⊙}, HH 1158 is the lowest luminosity irradiated HH jet identified to date in any cluster. Results from the analysis of high-resolution optical spectra indicate asymmetries in the brightness, morphology, electron density, velocity, and the mass outflow rates for the blue and redshifted lobes. We constrain the position angle of the HH 1158 jet at 102° ± 5°. The mass outflow rate and the mean accretion rate for HH 1158 using multiple diagnostics are estimated to be (5.2 ± 2.6) × 10{sup −10} M{sub ⊙} yr{sup −1} and (3.0 ± 1.0) × 10{sup −10} M{sub ⊙} yr{sup −1}, respectively. The properties for HH 1158 are notably similar to the externally irradiated HH 444–HH 447 jets previously identified in σ Orionis. In particular, the morphology is such that the weaker jet beam is tilted toward the massive stars, indicating a higher extent of photo-evaporation. The high value for the Hα/[S ii] ratio is also consistent with the ratios measured in other irradiated jets, including HH 444–HH 447. The presence of an extended collimated jet that is bipolar and the evidence of shocked emission knots make HH 1158 the first unique case of irradiated HH jets at the very low-luminosity end, and provides an opportunity to learn the physical properties of very faint HH jet sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Microbial and viral-like rhodopsins present in coastal marine sediments from four polar and subpolar regions

Rhodopsins are broadly distributed. In this work, we analyzed 23 metagenomes corresponding to marine sediment samples from four regions that share cold climate conditions (Norway; Sweden; Argentina and Antarctica). In order to investigate the genes evolution of viral rhodopsins, an initial set of 6224 bacterial rhodopsin sequences according to COG5524 were retrieved from the 23 metagenomes. After selection by the presence of transmembrane domains and alignment, 123 viral (51) and non-viral (72) sequences (>50 amino acids) were finally included in further analysis. Viral rhodopsin genes were homologs of Phaeocystis globosa virus and Organic lake Phycodnavirus. Non-viral microbial rhodopsin genes were ascribed to Bacteroidetes, Planctomycetes, Firmicutes, Actinobacteria, Cyanobacteria, Proteobacteria, Deinococcus-Thermus and Cryptophyta and Fungi. A rescreening using Blastp, using as queries the viral sequences previously described, retrieved 30 sequences (>100 amino acids). Phylogeographic analysis revealed a geographical clustering of the sequences affiliated to the viral group. This clustering was not observed for the microbial non-viral sequences. The phylogenetic reconstruction allowed us to propose the existence of a putative ancestor of viral rhodopsin genes related to Actinobacteria and Chloroflexi. This is the first report about the existence of a phylogeographic association of the viral rhodopsin sequences from marine sediments.

marine sediment↗
DOE OSTI2022

AutoEnRichness: A hybrid empirical and analytical approach for estimating the richness of galaxy clusters

ABSTRACT We introduce AutoEnRichness, a hybrid approach that combines empirical and analytical strategies to determine the richness of galaxy clusters (in the redshift range of 0.1 ≤ z ≤ 0.35) using photometry data from the Sloan Digital Sky Survey Data Release 16, where cluster richness can be used as a proxy for cluster mass. In order to reliably estimate cluster richness, it is vital that the background subtraction is as accurate as possible when distinguishing cluster and field galaxies to mitigate severe contamination. AutoEnRichness is comprised of a multistage machine learning algorithm that performs background subtraction of interloping field galaxies along the cluster line of sight and a conventional luminosity distribution fitting approach that estimates cluster richness based only on the number of galaxies within a magnitude range and search area. In this proof-of-concept study, we obtain a balanced accuracy of 83.20 per cent when distinguishing between cluster and field galaxies as well as a median absolute percentage error of 33.50 per cent between our estimated cluster richnesses and known cluster richnesses within r200. In the future, we aim for AutoEnRichness to be applied on upcoming large-scale optical surveys, such as the Legacy Survey of Space and Time and Euclid, to estimate the richness of a large sample of galaxy groups and clusters from across the halo mass function. This would advance our overall understanding of galaxy evolution within overdense environments as well as enable cosmological parameters to be further constrained.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Estimating cluster masses from SDSS multiband images with transfer learning

ABSTRACT The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass scales. We present a transfer-learning approach to estimate cluster masses using the ugriz-band images in the SDSS Data Release 12. The target masses are derived from X-ray or SZ measurements that are only available for a small subset of the clusters. We designed a semisupervised deep learning model consisting of two convolutional neural networks. In the first network, a feature extractor is trained to classify the SDSS photometric bands. The second network takes the previously trained features as inputs to estimate their total masses. The training and testing processes in this work depend purely on real observational data. Our algorithm reaches a mean absolute error (MAE) of 0.232 dex on average and 0.214 dex for the best fold. The performance is comparable to that given by redMaPPer, 0.192 dex. We have further applied a joint integrated gradient and class activation mapping method to interpret such a two-step neural network. The performance of our algorithm is likely to improve as the size of training data set increases. This proof-of-concept experiment demonstrates the potential of deep learning in maximizing the scientific return of the current and future large cluster surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Cosmology with the Roman Space Telescope – Synergies with CMB lensing

ABSTRACT We explore synergies between the Nancy Grace Roman Space Telescope and CMB lensing data to constrain dark energy and modified gravity scenarios. A simulated likelihood analysis of the galaxy clustering and weak lensing data from the Roman Space Telescope High Latitude Survey combined with CMB lensing data from the Simons Observatory is undertaken, marginalizing over important astrophysical effects and calibration uncertainties. Included in the modelling are the effects of baryons on small-scale clustering, scale-dependent growth suppression by neutrinos, as well as uncertainties in the galaxy clustering biases, in the intrinsic alignment contributions to the lensing signal, in the redshift distributions, and in the galaxy shape calibration. The addition of CMB lensing roughly doubles the dark energy figure-of-merit from Roman photometric survey data alone, varying from a factor of 1.7 to 2.4 improvement depending on the particular Roman survey configuration. Alternatively, the inclusion of CMB lensing information can compensate for uncertainties in the Roman galaxy shape calibration if it falls below the design goals. Furthermore, we report the first forecast of Roman constraints on a model-independent structure growth, parametrized by σ8(z), and on the Hu-Sawicki f(R) gravity as well as an improved forecast of the phenomenological (Σ0, μ0) model. We find that CMB lensing plays a crucial role in constraining σ8(z) at z > 2, with percent-level constraints forecasted out to z = 4. CMB lensing information does not improve constraints on the f(R) model substantially. It does, however, increase the (Σ0, μ0) figure-of-merit by a factor of about 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A measurement of CMB cluster lensing with SPT and DES year 1 data

Clusters of galaxies gravitationally lens the cosmic microwave background (CMB) radiation, resulting in a distinct imprint in the CMB on arcminute scales. Measurement of this effect offers a promising way to constrain the masses of galaxy clusters, particularly those at high redshift. We use CMB maps from the South Pole Telescope Sunyaev-Zel'dovich (SZ) survey to measure the CMB lensing signal around galaxy clusters identified in optical imaging from first year observations of the Dark Energy Survey. The cluster catalog used in this analysis contains 3697 members with mean redshift of $\bar{z} = 0.45$. We detect lensing of the CMB by the galaxy clusters at $8.1\sigma$ significance. Using the measured lensing signal, we constrain the amplitude of the relation between cluster mass and optical richness to roughly $17\%$ precision, finding good agreement with recent constraints obtained with galaxy lensing. The error budget is dominated by statistical noise but includes significant contributions from systematic biases due to the thermal SZ effect and cluster miscentering.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The parallelism motifs of genomic data analysis

Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Compiler Optimization for Extreme-Scale Scripting

The data-driven task parallelism execution model can support parallel programming models that are well suited for large-scale distributed-memory parallel computing, for example, simulations and analysis pipelines running on clusters and clouds. We describe a novel compiler intermediate representation and optimizations for this execution model, including adaptions of standard techniques alongside novel techniques. These techniques are applied to Swift/T, a high-level scripting language for flexible data flow composition of functions, which may be serial or use lower-level parallel programming models such as MPI and OpenMP. This paper presents preliminary results, indicating that our compiler optimizations reduce communication overhead by 70% to 93% on distributed-memory systems.

Armstrong, Timothy G.↗
DOE OSTI2024

Ni( II )-binding affinity of Cc NikZ-II and its homologs: the role of the HH -prong and variable loop revealed by structural and mutational studies

Extracytoplasmic Ni(II)-binding proteins (NiBPs) are molecular shuttles involved in cellular nickel uptake. Here, we determined the crystal structure of apo CcNikZ-II at 2.38 Å, which revealed a Ni(II)-binding site comprised of the double His (HH-)prong (His511, His512) and a short variable (v-)loop nearby (Thr59-Thr64, TEDKYT). Mutagenesis of the site identified Glu60 and His511 as critical for high affinity Ni(II)-binding. Phylogenetic analysis showed 15 protein clusters with two groups containing the HH-prong. Metal-binding assays with 11 purified NiBPs containing this feature yielded higher Ni(II)-binding affinities. Replacement of the wild type v-loop with those from other NiBPs improved the affinity by up to an order of magnitude. This work provides molecular insights into the determinants for Ni(II) affinity and paves way for NiBP engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data Analytics Applied to Coal Fired Boilers for Detecting Leaks

Data analytics were used to detect boiler leaks from five different coal-fired boilers including both subcritical and supercritical systems. Discriminant functions were developed that detected leaks up to two weeks prior to forced plant shutdowns for repairs. The leaks were identified to occur at different sections of the boiler for each plant, including waterwalls, economizer and superheater using conventional process measurement data. Leaking conditions were detected with a high degree of confidence (&NestedLessLess; 1% misclassified observations) and were able to distinguish normal operations from those time periods with steam leaks even while operating the power plants in power cycling mode.Multivariable statistical analyses, including Principal Component (PCA), cluster, and Fischer Discriminant Analysis (FDA) were used to characterize the leak occurrence. Normal and operational states with steam leaks were provided in the original process datasets. These datasets were split into two different groups for training and validation purposes. The data were sorted chronologically, and every third observation was assigned to training the Discriminant Function Model (DFM) while the rest were reserved for validation. PCA was used to reduce dimensionality of the original datasets. Canonical and FDA analyses were used to investigate the relationship between process variables. The outcome of the analyses revealed that nearly 35,000 observations were classified correctly; less than 0.05% of total observations were misclassified to be leaking, i.e. both false positives and false negatives.

Indrawan, Natarianto↗
DOE OSTI2015

Methodology for Clustering High-Resolution Spatiotemporal Solar Resource Data

In this report, we introduce a methodology to achieve multiple levels of spatial resolution reduction of solar resource data, with minimal impact on data variability, for use in energy systems modeling. The selection of an appropriate clustering algorithm, parameter selection including cluster size, methods of temporal data segmentation, and methods of cluster evaluation are explored in the context of a repeatable process. In describing this process, we illustrate the steps in creating a reduced resolution, but still viable, dataset to support energy systems modeling, e.g. capacity expansion or production cost modeling. This process is demonstrated through the use of a solar resource dataset; however, the methods are applicable to other resource data represented through spatiotemporal grids, including wind data. In addition to energy modeling, the techniques demonstrated in this paper can be used in a novel top-down approach to assess renewable resources within many other contexts that leverage variability in resource data but require reduction in spatial resolution to accommodate modeling or computing constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗