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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hyporheic Exchange Due to Cobbles on Sandy Beds

Hyporheic exchange induced by riverbed topography and roughness provides important ecosystem functions. We investigated how cobble clusters embedded in a finer-grained sand bed affect the near-bed channel flow and the exchange of surface and subsurface water. We tested how the spacing and embeddedness of cobbles altered hyporheic exchange through a three-dimensional fully coupled surface-subsurface model. The 3D modeling framework captured the full physics of the exchange process locating the lateral position of upwelling zones on the side of the cobble. As the cobbles protrude more into the channel, eddies appear downstream, with smaller vortices where cobbles are closer together. In our simulations, hyporheic exchange increased with the spacing and protrusion ratio. The travel time in the hyporheic zone also increased with the protrusion ratio because the hyporheic flow paths are longer when the cobble is more protruded. With different spacings at the highest protrusion ratio, the average slope of early time breakthrough curve was steeper for large spacing settings: the travel time increases as the spacing decreases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The response field and the saddle points of quantum mechanical path integrals

Highlights: • Moyal quantum mechanics and Marinov’s path integral. • Classical and semiclassical limits of Marinov’s path integral. • Oscillating functional integrals. • Instantons of the Marinov’s path integral. In quantum statistical mechanics, Moyal’s equation governs the time evolution of Wigner functions and of more general Weyl symbols that represent the density matrix of arbitrary mixed states. A formal solution to Moyal’s equation is given by Marinov’s path integral. In this paper we demonstrate that this path integral can be regarded as the natural link between several conceptual, geometric, and dynamical issues in quantum mechanics. A unifying perspective is achieved by highlighting the pivotal role which the response field, one of the integration variables in Marinov’s integral, plays for pure states even. The discussion focuses on how the integral’s semiclassical approximation relates to its strictly classical limit; unlike for Feynman type path integrals, the latter is well defined in the Marinov case. The topics covered include a random force representation of Marinov’s integral based upon the concept of “Airy averaging”, a related discussion of positivity-violating Wigner functions describing tunneling processes, and the role of the response field in maintaining quantum coherence and enabling interference phenomena. The double slit experiment for electrons and the Bohm–Aharonov effect are analyzed as illustrative examples. Furthermore, a surprising relationship between the instantons of the Marinov path integral over an analytically continued (“Wick rotated”) response field, and the complex instantons of Feynman-type integrals is found. The latter play a prominent role in recent work towards a Picard–Lefschetz theory applicable to oscillatory path integrals and the resurgence program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Experimental investigation on phase change material–based finned tube heat exchanger for thermal energy storage and building envelope thermal management

Phase change materials (PCMs) are attractive solutions for thermal energy storage (TES) applications by absorbing and releasing large amounts of latent heat during solid–liquid phase transitions. However, their relatively low thermal conductivity requires novel heat exchanger–based solutions to improve the power density and overall energy storage efficiency of the TES system. This work presents the design and experimental results of a finned tube heat exchanger to store collected natural thermal energy from a building envelope in a latent-based TES and to release it later for building heating/cooling applications. We experimentally evaluate the finned tube heat exchanger and evaluate the performance of TES in reducing building heating and cooling loads over 3–4 h of desired time of operation (e.g., peak load). The optimized design allows for maximum energy density by minimizing the heat exchanger volume, and the system is evaluated experimentally using commercially available heat exchanger materials and an organic PCM. Here, the experimental results reveal that the TES system is able to charge and discharge stored latent energy within 3–4 h, matching peak building electricity demand duration under an average fluid flow rate of 0.136 kg/s and temperature difference of 5.55 °C. Importantly, such optimized designs illuminate a path toward TES designs that are low-cost, scalable, and optimized for thermal energy and power availability under the desired time of operation.

25 ENERGY STORAGE↗
DOE OSTI2021

Dynamic time-warping correction for shifts in ultrahigh resolving power ion mobility spectrometry and structures for lossless ion manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced. Such variations are more apparent in higher Rp measurements, and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here we explore the utility of a data processing approaches employing linear alignment (LA) and nonlinear dynamic time warping (DTW) of IMS separations to correct for variations between separations, such as due to pressure fluctuations. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the LA approach effectively corrected for such variations, and significantly improvement Rp for summed separations. However, LA was much less effective for high Rp broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in IMS arrival times ions were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed DTW alignment performed similarly to LA when used over a narrow mobility range, but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 seconds were summed, and leading to a large improvement in effective Rp. We conclude that DTW is superior to LA for ultrahigh resolution broad mobility range SLIM IMS separations, correcting for ion arrival time shifts regardless of the cause. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files.

Data alignment, dynamic time warping, ion mobility↗
DOE OSTI2022

Nanostructured Composite Alloys for Extreme Environments

Accumulative Roll Bonding was used to process nanolayered Cu/Nb and Zr/Nb composites with varying individual layer thickness. Mechanical tests show remarkable strength as the average layer thickness decreases. Relatively high strength is preserved even at elevated temperatures. Despite differences in texture between rolling paths (longitudinally rolled-RL and cross rolled-CR) Cu/Nb, flow stresses between the resultant materials were similar. In addition, thermal conductivity does not change significantly as the interface density increases. The alloys show remarkable resistance to irradiation damage at very high doses due to stability of the interfaces. The results on Zr/Nb indicate that liquid phase chemistry resulting from thermal spikes play an important role and should be taken into account when designing alloys for extreme environments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Timber Harvesting Economics in Early Commercial Thinning and Group Selection Prescriptions

Forest management decisions that consider both short- and long-term objectives are becoming more challenging and costly, due to market uncertainty, labor shortages, and the evolving forest industry. Under such unpredictable circumstances, a better understanding of the production economics of various silvicultural prescriptions is crucial in implementing sound forest management activities. The objectives of this study were to: a) estimate stump to landing productivity and cost for Early Commercial Thinning (ECT) and Group Selection (GS) prescriptions; and b) compare the harvest system cost ($/PMH) using machine rate and PATH (Planning and Analysis in Timber Harvesting) methods. Detailed time-motion studies were conducted in the spruce-fir forest of Northern Maine, USA, during the summer of 2019. The results, as expected, indicated the harvesting costs were 23% higher for ECT (21.08 $/m3) compared to GS (16.32 $/m3). The average productivity of the harvester and forwarder were reduced by 15 and 37%, respectively, for ECT compared to GS. The estimated harvesting system cost ($/PMH) was 4% higher as indicated by PATH compared to machine rate method. Higher operational productivity in GS can be attributed to the larger volume of logs, and shorter travel loaded distance than ECT. These findings can help forest managers make more informed decisions while implementing appropriate silvicultural prescriptions under varying conditions based on management objectives and market conditions.

Forestry↗
DOE OSTI2026

A Nonergodic Ground-Motion Model for the San Francisco Bay Area for Small-Magnitude Earthquakes

ABSTRACT Recently, generative models have become a computationally efficient alternative to physics-based numerical simulations of ground motions. Neural networks can learn from existing ground-motion data to generate unobserved ground-motion data at new source and site locations. A key challenge with generative models is ensuring that predicted ground motions remain within a physically realistic range. For this purpose, we developed an empirical, nonergodic ground-motion model (GMM) for small-magnitude earthquakes in the San Francisco Bay area based on about 5000 recordings per component for Mw ≤ 4 earthquakes. The nonergodic GMM predicts spatially varying median source, site, and path effects for both the Fourier amplitude spectrum (FAS) and the Fourier phase derivative (a proxy for duration), as well as the corresponding epistemic uncertainty for each term. For FAS, our model shows above-average source and site effects in the western part of the region and below-average effects in the eastern part, with regional effects exhibiting larger spatial correlation lengths with increasing frequency. For duration, the source term is negligible for small-magnitude earthquakes, and the site term leads to site-specific variations up to 5 s. Path effects for FAS and duration depend on the source–site pair and are extrapolated spatially using recent methods for path-effect modeling. The aleatory variability of the within-site within-path residuals is similar to the variability found in previous studies for other regions. The nonergodic model provides two key contributions: first, median adjustment terms that are transferable to larger magnitude earthquakes, further reducing aleatory variability in probabilistic seismic hazard analysis; second, region-specific criteria for validating machine learning-based ground-motion generators to evaluate whether synthetic ground motions exhibit physically realistic source, site, and path effects.

Lacour, Maxime↗
DOE OSTI2020

Efficient bi-directional coupling of 3D computational fluid-particle dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. Additionally, as a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. Overall, these methods can be used as the foundation for multi-scale modeling of the full respiratory system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Plasma surface modification coupled with thermal and step-over distance effects on significant fracture improvement of adhesively-bonded metal-$\mathrm{CFRTP}$ dissimilar materials

Here, this work proposes an approach to improve the interfacial bonding between carbon-fiber-reinforced thermoplastic polymers (CFRTP) and thermoset adhesive by using the surface modification with the combination of air plasma, thermal, and step-over effects. Thanks to the proper heating which causes the exposure of carbon fibers on the CFRTP surface, both polymer matrix and these exposed carbon fibers can have improved bonding with adhesive due to air plasma treatment. By conducting the Double Cantilever Beam (DCB) tests performed on adhesively-bonded AA5052/CFRP-PA66 dissimilar joints, it was shown in this work that the average Mode I specific fracture energy can be improved up to about 180% compared to non-treated counterparts. The foregoing improvement can be further increased by considering the step-over distance of the surface treatment, which triggers the tortuous damage path in the failure process of adhesively-bonded structures. By manipulating this treatment parameter, often overlooked in the literature, and other parameters (i.e., treatment speed, nozzle tip-to-surface distance, etc.) investigated in this study, the average Mode I specific fracture energy of adhesively-bonded AA5052/CFRP-PA66 dissimilar joints can be improved reaching up to about 410% compared to non-treatment counterparts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Geometry-independent microstructure optimization for electron beam powder bed fusion additive manufacturing

The ability to manipulate the formation of microstructure is one of the potential advantages of additive manufacturing. Yet, the additive manufacturing process is riddled with complex interactions between processing parameters, geometry, and spot melting sequence which makes the task of controlling microstructure challenging. This paper proposes a method to solve the microstructure texture optimization problem by leveraging established optimization techniques and increasingly fast and accurate analytical heat transfer models. Respectively, we apply two different optimization algorithms, genetic algorithm and concurrent greedy line search, in order to induce arbitrarily shaped microstructure regions and we use a heat transfer model to evaluate the fitness of solutions in an iterative approach that is far more efficient than pure trial and error. The objective of the optimization algorithm is to control local thermal conditions – hence microstructure formation – during the melting process by manipulating the order and the dwell time of all the points of the infill pattern sequence. We then analyze the optimized sequence to determine important path characteristics that affect the microstructure formation. Through examples, we show that relative order and frequency, as measured by weighted average and variance of spot order, are important factors that influence the final characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities

We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗
DOE OSTI2026

Achievement of a high-density, high-confinement, and high-beta tokamak plasma regime in DIII-D, and implications for a lower-current path for ITER and FPP

Experiments on DIII-D have demonstrated a density-confinement synergy that enables sustainment of high performance in a previously unattained parameter regime of simultaneous very high energy confinement quality (H 98y2 ≥ 1.5), very high line-average density Greenwald fraction (ƒ Gr = πa 2 < n >/I P ≥ 1.4), and high toroidal beta (β T ≥ 3%). Tokamak operation in this regime is essential for a compact steady-state FPP, as well as for Q=10 with 500 MW of fusion power in ITER at I P << 15 MA. These experiments leveraged the knowledge that, in the high-poloidal-beta (β P ) regime, impurity and density gradients can enhance turbulence stabilization caused by high α MHD (α MHD ~(dβ P )⁄dr). This was described by theoretical predictions and gyrokinetic transport simulations [M.T. Kotschenreuther et al, 2024 Nucl. Fusion, 64 076033], and later confirmed by experiments on DIII-D [S. Ding et al, 2024 Nature 629 555]. To increase both β P and β T , the new experiments increased the ideal-wall stability β N -limit by using a smaller plasma-outer wall distance and higher triangularity in the plasma cross section (top/bottom average δ~0.9), enabled by the recent “shape & volume rise” (SVR) modification to the DIII-D divertor. The higher triangularity also contributed to achieving higher ƒ Gr by enabling higher pedestal density. At high density, the pedestal is ballooning limited and exhibits small and frequent ELMs, while the divertor is near detachment even without any impurity seeding. High plasma performance was attained and sustained reproducibly, with the eventual terminations brought about by an MHD mode destabilized as the current profile slowly continued to evolve. A path to stationary fully noninductive operation might include ECH injection to reduce both core impurity accumulation and the electron collisionality, thus increasing the bootstrap current. These experiments provide the first experimental demonstration of the ƒ Gr , H 98y2 , and β T values required simultaneously for ITER Q = 10 at I P < 10 MA, pointing to practical ways to improve the energy confinement in a fusion reactor.

Garofalo, Andrea M. [General Atomics, San Diego, C↗
DOE OSTI2026

Bypassing the yellow phase for extremely stable formamidinium lead iodide perovskite solar cells

INTRODUCTION Formamidinium lead iodide (FAPI) emerged as an ideal material for single-junction perovskite solar cells owing to its near optimal bandgap of 1.45 to 1.5 eV and outstanding thermal stability. However, the photoactive cubic α-phase (3C-FAPI) of FAPI is structurally unstable and undergoes a reconstructive phase transition to the nonperovskite yellow hexagonal δ-phase (2H-FAPI) at ambient temperature. The phase reconstruction from 3C-FAPI to 2H-FAPI could be prevented by alloying methylammonium (MA) or Cs or both at the A-site and Br at the halide site, but this limits long-term durability owing to phase segregation or materials instability. Addressing these challenges requires a rational design strategy to stabilize 3C-FAPI by restricting lattice reconstruction without compromising thermal stability. RATIONALE Two main strategies have emerged to improve the phase stability and film quality of FAPI. Here, the first is a lattice-templating approach, which enables the slow formation of perovskite but it eventually degrades through the formation of yellow phases. The second approach, which has been widely explored, involves additive engineering, using alkyl ammonium halide or mostly chloride-based additives, which provide better control over the crystallization route. However, the FAPI films fabricated using these additives are often alloyed and compromise long-term stability. Moreover, the exact role of Cl has been unclear and speculative, specifically when Cl-based additives are used. Even after using a high additive concentration, the incorporation of Cl in perovskite lattice is rare. RESULTS Guided by synergistic modeling and experimental studies, we developed a coadditive strategy using 15 mol % FACl and 0.5 mol % BA 2 PbI 4 perovskites in combination (where BA is butylammonium) to enable a highly oriented (100) Cl-doped FAPI film with exceptional durability. Synchrotron-based in situ wide-angle x-ray scattering revealed a favorable transition for the coadditive-treated FAPI (FAPI-CA) to the corner-sharing 3C black phase through a progressive transformation through the 2H, 4H, 6H, and 8H phases. Moreover, solid-state 35 Cl nuclear magnetic resonance (NMR) revealed Cl incorporation in the perovskite lattice and, as predicted by modeling, indicated that Cl plays a key role in altering the energetics of both the formation and degradation pathways. The Cl-doped perovskite can completely bypass the expected and energetically favorable degradation pathway via the yellow phase or the 2H-PbI 2 phase. Instead, it undergoes degradation only upon exposure to harsh conditions such as 15-sun illumination and 90°C through the energetically uphill 3R-PbI 2 phase path. A p-i-n device fabricated with FAPI-CA film demonstrated a power conversion efficiency (PCE) of 25.1% with an average of 24.1% (40 devices). The notable film stability translated to other devices and retained 98% of its initial PCE under open-circuit conditions at 85° ± 5°C for 1200 hours. CONCLUSION Our study highlights the decisive role of chloride in regulating both the formation and degradation pathways. This regulation is critical for creating a perovskite film with commercially relevant durability.

Garai, Rabindranath [Rice Univ., Houston, TX (Unit↗
DOE OSTI2021

Liquid Containing Clouds at the North Slope of Alaska Demonstrate Sensitivity to Local Industrial Aerosol Emissions

Abstract Cloud condensation nucleus control alter cloud solar albedo through cloud droplet size. Here, we leverage anthropogenic emissions at the North Slope of Alaska as a natural laboratory to study relationships between aerosols and Arctic liquid‐containing clouds. Averaging 14 years of MODIS observations, we found a reduction in temporally averaged cloud effective radius ( ) of up to 1.0 μm related to localized pollution. Pronounced regional gradients in cloud frequency of occurrence and liquid water path prohibit the detection of potential changes of these variables. Observed changes of alter radiative fluxes and increase cloud‐reflected shortwave radiation by up to 0.8 W m − 2 in the Prudhoe Bay area for the period covered by observations (April–September). Due to the frequent occurrence of liquid‐containing clouds, this implies that enhanced local emissions in Arctic regions can impact climate processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effect of loading path on grain misorientation and geometrically necessary dislocation density in polycrystalline aluminum under reciprocating shear

Solid phase processing (SPP) is a promising alloy fabrication technique to produce fine and homogeneous grain structures for high-performance alloys. However, there is very limited modeling capability to understand and predict the grain refinement during SPP. In this work, the crystal plasticity theory was used to study elastic-plastic deformation in polycrystalline aluminums under large shear deformation. Two approaches, kernel averaged misorientation (KAM) and grain reference orientation deviation (GROD), were used to assess the grain misorientations. The geometrically necessary dislocation (GND) density was computed with the plastic strain rate. The deformation simulations were carried out under two loading conditions to investigate the effect of loading paths on the evolutions of grain misorientation and GND density. The results show that the regions with high misorientation and GND density first appear near grain boundaries. These regions then extend toward interior grains. The loading path affects dislocation system activation and dislocation recovery, hence dislocation evolution and misorientation. In conclusion, both two- and three-dimensional simulations showed that the spatial and temporal evolutions of GROD, KAM, and GND density in are closely correlated, which indicates they all can be used as criteria of grain refinement or recrystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2026

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗