Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Pattern”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Altimeter-era emergence of the patterns of forced sea-level rise in climate models and implications for the future

The satellite altimeter record has provided an unprecedented database for understanding sea-level rise and has recently reached a major milestone at 25 years in length. A challenge now exists in understanding its broader significance and its consequences for sea-level rise in the coming decades and beyond. A key question is whether the pattern of altimeter-era change is representative of longer-term trends driven by anthropogenic forcing. In this work, two multimember climate ensembles, the Community Earth System Model (CESM) and the Earth System Model Version 2M (ESM2M), are used to estimate patterns of forced change [also known as the forced response (FR)] and their magnitudes relative to internal variability. It is found that the spatial patterns of 1993–2018 trends in the ensembles correlate significantly with the contemporaneous FRs (0.55 ± 0.10 in the CESM and 0.61 ± 0.09 in the ESM2M) and the 1950–2100 FRs (0.43 ± 0.10 in the CESM and 0.51 ± 0.11 in the ESM2M). Unforced runs for each model show such correlations to be extremely unlikely to have arisen by chance, indicating an emergence of both the altimeter-era and long-term FRs and suggesting a similar emergence in nature. Projected patterns of the FR over the coming decades resemble those simulated during the altimeter era, suggesting a continuation of the forced pattern of change in nature in the coming decades. Notably, elevated rates of rise are projected to continue in regions that are susceptible to tropical cyclones, exacerbating associated impacts in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Arctic soil patterns analogous to fluid instabilities

Significance Slow-moving arctic soils form patterns resembling those found in common fluids, such as paint and cake icing drips. Inspired by fluid instabilities, we develop a conceptual model for soil patterns and use mathematical analysis to predict their wavelength. In particular, we propose that soil patterns arise due to competition between gravity and cohesion or the “stickiness” of soil grains. We compare our theoretical predictions with a dataset of soil features from Norway, finding that soil patterns are controlled by fluid-like properties as well as climate. Our work provides a physical explanation for a common pattern on both Earth and Mars, with implications for our understanding of landscapes and complex materials composed of both granular and fluid components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Influence of substrate pattern on the adsorption of HP lattice proteins

With the highly simplified hydrophobic-polar model representation of a protein, we can study essential qualitative physics without an unnecessarily large computational overhead. Using Wang-Landau sampling in conjunction with a set of efficient Monte Carlo trial moves, we studied the adsorption of short HP lattice proteins on various simple patterned substrates and in particular for checkered patterned surfaces. In this work, a set of single-site mutated HP proteins is used to investigate the role of hydrophobicity of a protein chain and surface pattern for substrates with various pattern cell sizes relative to the protein’s native configuration. For most cases, we found that the adsorption transition occurs at a lower temperature, while the hydrophobic core formation is less affected. Additionally, the flattening procedure after the HP protein is adsorbed is more sensitive to the change in surface patterns and single-site mutations. These observations stay valid for both strongly and weakly attractive surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Thermally unstable roosts influence winter torpor patterns in a threatened bat species

Abstract Many hibernating bats in thermally stable, subterranean roosts have experienced precipitous declines from white-nose syndrome (WNS). However, some WNS-affected species also use thermally unstable roosts during winter that may impact their torpor patterns and WNS susceptibility. From November to March 2017–19, we used temperature-sensitive transmitters to document winter torpor patterns of tricolored bats (Perimyotis subflavus) using thermally unstable roosts in the upper Coastal Plain of South Carolina. Daily mean roost temperature was 12.9 ± 4.9°C SD in bridges and 11.0 ± 4.6°C in accessible cavities with daily fluctuations of 4.8 ± 2°C in bridges and 4.0 ± 1.9°C in accessible cavities and maximum fluctuations of 13.8 and 10.5°C, respectively. Mean torpor bout duration was 2.7 ± 2.8 days and was negatively related to ambient temperature and positively related to precipitation. Bats maintained non-random arousal patterns focused near dusk and were active on 33.6% of tracked days. Fifty-one percent of arousals contained passive rewarming. Normothermic bout duration, general activity and activity away from the roost were positively related to ambient temperature, and activity away from the roost was negatively related to barometric pressure. Our results suggest ambient weather conditions influence winter torpor patterns of tricolored bats using thermally unstable roosts. Short torpor bout durations and potential nighttime foraging during winter by tricolored bats in thermally unstable roosts contrasts with behaviors of tricolored bats in thermally stable roosts. Therefore, tricolored bat using thermally unstable roosts may be less susceptible to WNS. More broadly, these results highlight the importance of understanding the effect of roost thermal stability on winter torpor patterns and the physiological flexibility of broadly distributed hibernating species.

Biodiversity & Conservation↗
DOE OSTI2024

The structure and interaction of polymers affects secondary cell wall banding patterns in Arabidopsis

Abstract Xylem tracheary elements (TEs) synthesize patterned secondary cell walls (SCWs) to reinforce against the negative pressure of water transport. VASCULAR-RELATED NAC-DOMAIN 7 (VND7) induces differentiation, accompanied by cellulose, xylan, and lignin deposition into banded domains. To investigate the effect of polymer biosynthesis mutations on SCW patterning, we developed a method to induce tracheary element transdifferentiation of isolated protoplasts, by transient transformation with VND7. Our data showed that proper xylan elongation is necessary for distinct cellulose bands, cellulose–xylan interactions are essential for coincident polymer patterns, and cellulose deposition is needed to override the intracellular organization that yields unique xylan patterns. These data indicate that a properly assembled cell wall network acts as a scaffold to direct polymer deposition into distinctly banded domains. We describe the transdifferentiation of protoplasts into TEs, providing an avenue to study patterned SCW biosynthesis in a tissue-free environment and in various mutant backgrounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Phase Pattern Formation in Grain Boundaries

Here, in this Letter, we derive conditions that predict the existence of two-phase periodic-pattern grain boundary structures that are stable against coarsening. While previous research has established that elastic effects can lead to phase pattern formation on crystal surfaces, the possibility of stable grain boundary structures composed of alternating grain boundary phases has not been previously analyzed. Our theory identifies the specific combination of grain boundary and materials properties that enable the emergence of patterned grain boundary states and shows that the dislocation content of grain boundary phase junctions, absent in surface phenomena, weakens the stability of the patterned structures. The predictions of the theory are tested using a model copper grain boundary that exhibits multiple phases and two-phase pattern formation. We discuss how, similarly to surfaces, elastic effects associated with grain boundary phase junctions have profound implications for how grain boundary phases transform.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2020

PLEXUS: A Pattern-Oriented Runtime System Architecture for Resilient Extreme-Scale High-Performance Computing Systems

For high-performance computing (HPC) system designers and users, meeting the myriad challenges of next-generation exascale supercomputing systems requires rethinking their approach to application and system software design. Among these challenges, providing resiliency and stability to the scientific applications in the presence of high fault rates requires new approaches to software architecture and design. As HPC systems become increasingly complex, they require intricate solutions for detection and mitigation for various modes of faults and errors that occur in these large-scale systems, as well as solutions for failure recovery. These resiliency solutions often interact with and affect other system properties, including application scalability, power and energy efficiency. Therefore, resilience solutions for HPC systems must be thoughtfully engineered and deployed.In previous work, we developed the concept of resilience design patterns, which consist of templated solutions based on well-established techniques for detection, mitigation and recovery. In this paper, we use these patterns as the foundation to propose new approaches to designing runtime systems for HPC systems. The instantiation of these patterns within a runtime system enables flexible and adaptable end-to-end resiliency solutions for HPC environments. The paper describes the architecture of the runtime system, named Plexus, and the strategies for dynamically composing and adapting pattern instances under runtime control. This runtime-based approach enables actively balancing the cost-benefit trade-off between performance overhead and protection coverage of the resilience solutions. Based on a prototype implementation of PLEXUS, we demonstrate the resiliency and performance gains achieved by the pattern-based runtime system for a parallel linear solver application.

Hukerikar, Saurabh↗
DOE OSTI2016

Selective Area Growth of GaAs on Si Patterned Using Nanoimprint Lithography

Heteroepitaxial selective area growth (SAG) of GaAs on patterned Si substrates is a potential low-cost approach to integrate III-V and Si materials for tandem or multijunction solar cells. The use of nanoscale openings in a dielectric material can minimize nucleation-related defects and allow thinner buffer layers to be used to accommodate lattice mismatch between Si and an epitaxial III-V layer. For photovoltaic applications, the cost of patterning and growth, as well as the impact on the performance of the Si bottom cell must be considered. We present preliminary results on the use of soft nanoimprint lithography (SNIL) to create patterned nucleation templates for the heteroepitaxial SAG of GaAs on Si. We demonstrate that SNIL patterning of passivating layers on the Si substrate improves measured minority carrier properties relative to unprotected Si. Cost modeling of the SNIL process shows that adding a patterning step only adds a minor contribution to the overall cost of a tandem III-V/Si solar cell, and can enable significant savings if it enables thinner buffer layers.

14 SOLAR ENERGY↗
DOE OSTI2024

Object Proxy Patterns for Accelerating Distributed Applications

Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer—optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns—distributed futures, streaming, and ownership—that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. As a result, we evaluate our implementations through a suite of benchmarks and by applying them in three meaningful scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.

Distributed Computing↗
DOE OSTI2016

MO-FG-BRA-05: Dosimetric and Radiobiological Validation of Respiratory Gating in Conventional and Hypofractionated Radiotherapy of the Lung: Effect of Dose, Dose Rate, Gating Window and Breathing Pattern

Purpose: to evaluate the dosimetric and radiobiological consequences from having different gating windows, dose rates, and breathing patterns in gated VMAT lung radiotherapy. Methods: A novel 3D-printed moving phantom with central high and peripheral low tracer uptake regions was 4D FDG-PET/CT-scanned using ideal, patient-specific regular, and irregular breathing patterns. A scan of the stationary phantom was obtained as a reference. Target volumes corresponding to different uptake regions were delineated. Simultaneous integrated boost (SIB) 6 MV VMAT plans were produced for conventional and hypofractionated radiotherapy, using 30–70 and 100% cycle gating scenarios. Prescribed doses were 200 cGy with SIB to 240 cGy to high uptake volume for conventional, and 800 with SIB to 900 cGy for hypofractionated plans. Dose rates of 600 MU/min (conventional and hypofractionated) and flattening filter free 1400 MU/min (hypofractionated) were used. Ion chamber measurements were performed to verify delivered doses. Vials with A549 cells placed in locations matching ion chamber measurements were irradiated using the same plans to measure clonogenic survival. Differences in survival for the different doses, dose rates, gating windows, and breathing patterns were analyzed. Results: Ion chamber measurements agreed within 3% of the planned dose, for all locations, breathing patterns and gating windows. Cell survival depended on dose alone, and not on gating window, breathing pattern, MU rate, or delivery time. The surviving fraction varied from approximately 40% at 2Gy to 1% for 9 Gy and was within statistical uncertainty relative to that observed for the stationary phantom. Conclusions: Use of gated VMAT in PET-driven SIB radiotherapy was validated using ion chamber measurements and cell survival assays for conventional and hypofractionated radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Mobility Pattern Analysis for Power Restoration Activities Using Geo-Tagged Tweets

In this study, we analyzed mobility patterns of at-risk populations affected by an extreme event using geotagged tweets to geo-target power restoration efforts. Unlike other studies that have used tweets to facilitate emergency management activities, we used 1.5 million geotagged tweets generated during Hurricane Sandy (2012) to determine the mobility patterns and geospatial distribution of impacted populations who experienced power outage before, during and after the hurricane. We implemented a three-step analytical framework to: (i) analyze tweet contents with visual methods, including dendrograms, word clouds to identify common keywords pertaining to power outage; (ii) identify target users whose tweets contained information about power outages; and (iii) create a user-tweet locations matrix and an origin-destination matrix to examine clusters of target users and their mobility patterns. Preliminary results indicate that potential clusters were present in and around New York city, Philadelphia, Washington D.C. and Baltimore, which were used as potential evacuation destination cities after hurricane Sandy. The travel pattern and destination information can be used to (i) mobilize restoration efforts by utility companies and (ii) address resource allocation needs both in impacted and destination cities. Future work will focus on analyzing potential destinations for different origins and travel-time to identify evacuation routing patterns.

Kar, Bandana↗
DOE OSTI2023

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

25 ENERGY STORAGE↗
DOE OSTI2020

Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models

Radiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. In this study, we investigate intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the West Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Deep phylogenomics of a tandem-repeat galectin regulating appendicular skeletal pattern formation

Background A multiscale network of two galectins Galectin-1 (Gal-1) and Galectin-8 (Gal-8) patterns the avian limb skeleton. Among vertebrates with paired appendages, chondrichthyan fins typically have one or more cartilage plates and many repeating parallel endoskeletal elements, actinopterygian fins have more varied patterns of nodules, bars and plates, while tetrapod limbs exhibit tandem arrays of few, proximodistally increasing numbers of elements. We applied a comparative genomic and protein evolution approach to understand the origin of the galectin patterning network. Having previously observed a phylogenetic constraint on Gal-1 structure across vertebrates, we asked whether evolutionary changes of Gal-8 could have critically contributed to the origin of the tetrapod pattern. Results Translocations, duplications, and losses of Gal-8 genes in Actinopterygii established them in different genomic locations from those that the Sarcopterygii (including the tetrapods) share with chondrichthyans. The sarcopterygian Gal-8 genes acquired a potentially regulatory non-coding motif and underwent purifying selection. The actinopterygian Gal-8 genes, in contrast, did not acquire the non-coding motif and underwent positive selection. Conclusion These observations interpreted through the lens of a reaction-diffusion-adhesion model based on avian experimental findings can account for the distinct endoskeletal patterns of cartilaginous, ray-finned, and lobe-finned fishes, and the stereotypical limb skeletons of tetrapods.

Evolutionary Biology↗
DOE OSTI2015

PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.

Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of human perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations.

58 GEOSCIENCES↗
DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

58 GEOSCIENCES↗
DOE OSTI2017

Embedded Spiral Patterns in the Cool Core of the Massive Cluster of Galaxies Abell 1835

We present the properties of an intracluster medium (ICM) in the cool core of the massive cluster of galaxies, Abell 1835, obtained with the data from the Chandra X-ray Observatory. We find distinctive spiral patterns with a radius of 70 kpc (or 18″) as a whole in the residual image of the X-ray surface brightness after the two-dimensional ellipse model of surface brightness is subtracted. The size is smaller by a factor of 2–4 than that of other clusters that are known to have a similar pattern. The spiral patterns consist of two arms. One of them appears as positive, and the other appears as negative excesses in the residual image. Their X-ray spectra show that the ICM temperatures in the positive- and negative-excess regions are 5.09{sub −0.13}{sup +0.12} keV and 6.52{sub −0.15}{sup +0.18} keV, respectively. In contrast, no significant difference is found in the abundance or pressure, the latter of which suggests that the ICM in the two regions of the spiral patterns is near or is in pressure equilibrium. The spatially resolved X-ray spectroscopy of the central region (r<40{sup ′′}), divided into 92 sub-regions indicates that Abell 1835 is a typical cool core cluster. We also find that the spiral patterns extend from the cool core out to the hotter surrounding ICM. The residual image reveals some lumpy substructures in the cool core. The line of sight component of the disturbance velocity that is responsible for the substructures is estimated to be lower than 600 km s{sup −1}. Abell 1835 may now be experiencing an off-axis minor merger.

79 ASTRONOMY AND ASTROPHYSICS↗