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Results for “pattern scaling”

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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental investigation of surface roughness/wettability pattern effect on crystallization fouling over falling-film flow

In many industries, including desalination, scaling in heat exchangers is a persistent issue, and most methods of scaling control involve environmentally hazardous chemical additives. Exploiting the effects of surface features and flow-imposed shear on salt deposition might introduce a new approach to scale management, opening the possibility of self-cleaning surfaces. In this work, we experimentally explore surface roughness and wettability patterns interaction with salt deposition and flow shear. Heat transfer and scale mass deposition on flat surfaces are measured during thin-film evaporation of calcium sulfate solution. A wide range of surface roughness (0.027–2.66 μm) is studied at fixed flow and heat flux conditions. Due to improved mixing, heat transfer is enhanced with rougher surfaces initially; however, degrades more quickly than smoother surfaces. Following a period of initial mass deposition fluctuation, a steady scaling stage is observed, with rough surfaces scaling more than smooth surfaces. Wettability patterned surfaces can suppress crystal nucleation without sacrificing overall surface wetting, resulting in antifouling performance and heat transfer enhancement. Scale mass deposition on a patterned surface is reduced by 60 %, and 27 % heat transfer improvement over the baseline surface is found. Furthermore, this study provides guidance to surface manipulation for heat transfer improvement and fouling mitigation.

42 ENGINEERING↗
DOE OSTI2025

Predicting multi-nodal in-nozzle particle interactions in high-viscosity fluid mediums for acoustophoretic direct-ink writing of line-patterned composites

Patterned functional materials offer improved properties (electrical, thermal, etc.) over their bulk counterparts in many applications, including energy storage, flexible electronics, and sensors. However, manufacturing approaches for patterning materials over large areas with features on the order of hundreds of microns or less are limited. Acoustophoresis, which uses acoustic forces to control particle arrangement in a fluid medium, is a pathway to address this challenge. This process is dependent on particle and fluid properties and enables patterning of a broad range of materials. Herein, a model with experimental validation is presented to demonstrate that acoustophoresis can be combined with direct-ink writing (DIW) to fabricate line patterns over large cm-scale areas. An in-nozzle particle interaction model was developed to investigate the impact of processing conditions on multi-nodal acoustophoretic DIW. The model predicts patterned line widths within a factor of two relative to experimental results for a high viscosity case study. Here, the model was used to investigate the impact of frequency, particle loading, particle radius, and acoustic pressure on line width and patterning time, providing critical feedback regarding the processing conditions suitable for a target application. Model results illustrate that frequency has the greatest impact on line patterns: increasing from 1 to 3 MHz resulted in a greater than 65% reduction in line width and a greater than 85% reduction in patterning time. Additionally, experiments were conducted with an alumina-epoxy ink and a ~21 cm 2 area pattern was rastered in ~5.5 minutes, demonstrating a path towards large-area line-patterned composite fabrication.

25 ENERGY STORAGE↗
NASA NTRS2011

Seafloor Control on Sea Ice

The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

Nghiem, S. V.↗
DOE OSTI2020

DNA Reaction–Diffusion Attractor Patterns

Living systems can form and recover complex chemical patterns with precisely sized features in the ranges of tens or hundreds of microns. We show how designed reaction-diffusion processes can likewise produce precise patterns, termed attractor patterns, that reform their precise shape after being perturbed. We use oligonucleotide reaction networks, photolithography and microfluidic delivery to form precisely controlled attractor patterns and study the responses of these patterns to different localized perturbations. Linear and ‘hill’-shaped patterns formed and stabilized into shapes and at time scales consistent with reaction-diffusion models. When patterns were perturbed in particular locations with UV light, they reliably reformed their steady state profiles. Recovery also occurred after repeated perturbations. As a result, by designing the far-from-equilibrium dynamics of a chemical system, this study shows how it is possible to design spatial patterns of molecules that are sustained and regenerated by continually evolving towards a specific steady state configuration

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

Helicopter Model Rotor-Blade Vortex Interaction Impulsive Noise: Scalability and Parametric Variations

Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade-vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model-scale data were compared with averaged full-scale, in-flight acoustic data under similar non-dimensional test conditions using an improved data analysis technique. At low advance ratios (mu = 0.164 - 0.194), the BVI impulsive noise data scale remarkably well in level, waveform, and directivity patterns. At moderate advance ratios (mu = 0.224 - 0.270), the scaling deteriorates, suggesting that the model-scale rotor is not adequately simulating the full-scale BVI noise. Presently, no proved explanation of this discrepancy exists. Measured BVI noise radiation is highly sensitive to all of the four governing nondimensional parameters--hover tip Mach number, advance ratio, local inflow ratio, and thrust coefficient.

Boxwell, D. A.↗
DOE OSTI2020

Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features—including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones—that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both extreme values of SLS environmental parameters and synoptic-scale features in the ERA5 reanalysis and in the Community Atmosphere Model, version 6 (CAM6), historical simulation during 1980–2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in convective available potential energy over the eastern United States primarily due to a high bias in surface moisture and, to a lesser extent, storm-relative helicity due to enhanced low-level winds. Additionally, composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, our results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Space shuttle orbital maneuvering engine platelet injector program

A platelet face injector for the Orbit Maneuvering Engine (OME) on the space shuttle was evaluated as a means of obtaining additional design margin and lower cost. The program was conducted in three phases. The first phase evaluated single injection elements, or unielements; it involved visual flow studies, mixing experiments using propellant simulants, and hot firings to assess combustion efficiency, chamber wall compatibility, and injector face temperatures. In the second phase, subscale units producing 600 lbf thrust were used to further evaluate the orifice patterns chosen on the basis of unielement testing. In addition to combustion efficiency, chamber and injector heat transfer, the subscale testing provided a preliminary indication of injector stability. Full scale testing of the selected patterns at 6,000 lbf thrust was performed in the third phase. Performance, heat transfer, and combustion stability were evaluated over the anticipated range of OMS operating conditions. The effects on combustion stability of acoustic cavity configuration, including cavity depth, open area, inlet contour, and other parameters, were investigated.

Source record↗
NASA NTRS2009

VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

Fang, Wai-Chi↗
DOE OSTI2021

Tensor Text-Mining Methods for Malware Identification and Detection, Malware Dynamics Characterization, and Hosts Ranking

Malware is one of the most persistent and costly cyber threats endangering reputation, confidentiality, integrity, and availability for organizations and national security. Consequently, many of the incident detection and prevention systems, and incident responders have begun to utilize machine learning as a helper in the fight against malware and other cyber threats. However, cyber defenders rely on interpretability and generalizability, yet the popular machine learning methods are black-box and often use traditional supervised solutions that do not generalize to novel malware. Therefore, there is a need to improve the existing solutions. At the same time, the majority of the prior research ignored essential evaluation criteria when reporting the results of their methods, which disables the safe reproducibility of the methods in a production environment. Tensor decomposition, on the other hand, enables interpretable unsupervised analysis of the large-scale data for the discovery of hidden patterns. Our findings, performed on real-world and large-scale experiments, show that tensor factorization-based methods yield performance results that surpasses or competes with existing supervised solutions with the added benefit of interpretability and generalizability. With the ability to analyze complex and large-scale data using tensors, we report results that reflect real-world production environments. We propose to develop new game- changing tools for malware identification and characterization that can trace malware evolution, rank the infected or malicious hosts, and streamline the work of incident response teams, malware analysts, and incident detection and prevention systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗
NASA NTRS2004

Ground Ice at the Phoenix Landing Site: A Preflight Assessment

One of the objectives of the Mars Scout mission, Phoenix, is to characterize the present state of water in the martian environment, in a location where water may play a significant role in the present and past habitability of Mars. Given the generally dry and cold climate of Mars today any substantial amount of water is expected to occur in the form of ground ice (subsurface ice) within the regolith. The Mars Odyssey Gamma Ray Spectrometer has indicated abundant subsurface hydrogen and inferred ground ice at high latitudes. Therefore, the Phoenix mission will be targeted to land in the northern high latitudes (approximately 65 degrees N - 75 degrees N) where ground ice is expected to be abundantly available for analysis. The lander will be capable of excavating, sampling, and analyzing, dry and water-rich/icy soils. The location and depth of excavation necessary to achieve the goals of sampling and analysis of icy material become important parameters to assess. In the present work we ask two key questions: 1) At what depth within the regolith do we expect to find ice? 2) How might this depth vary over the region of potential landing sites? Numerous lines of evidence can be employed to provide an indication of the presence or absence of shallow ground ice at the potential landing sites. For example geomorphology, neutrons, gamma rays, and theory each contribute clues to an overall understanding of the distribution of ice. Orbital observations provide information on a variety of spatial scales, typically 10 s of meters (patterned ground) to 100 s of kilometers (gamma rays). While information on all of these scales are important, of particular interest is how the presence and depth of ground ice might vary on spatial scales comparable to the lander and its work area. While ground ice may be stable (and present) on a regional scale, local-scale slopes and changes in the physical characteristics of soils can result in significant variations in the distribution of ice.

Mellon, M. T.↗
DOE OSTI2025

Drosophila melanogaster pigmentation demonstrates adaptive phenotypic parallelism over multiple spatiotemporal scales

Abstract Populations are capable of responding to environmental change over ecological timescales via adaptive tracking. However, the translation from patterns of allele frequency change to rapid adaptation of complex traits remains unresolved. We used abdominal pigmentation in Drosophila melanogaster as a model phenotype to address the nature, genetic architecture, and repeatability of rapid adaptation in the field. We show that D. melanogaster pigmentation evolves as a highly parallel and deterministic response to shared environmental variation across latitude and season in natural North American populations. We then experimentally evolved replicate, genetically diverse fly populations in field mesocosms to remove any confounding effects of demography and/or cryptic structure that may drive patterns in wild populations; we show that pigmentation rapidly responds, in parallel, in fewer than 15 generations. Thus, pigmentation evolves concordantly in response to spatial and temporal climatic axes. We next examined whether phenotypic differentiation was associated with allele frequency change at loci with established links to genetic variance in pigmentation in natural populations. We found that across all spatial and temporal scales, phenotypic patterns were associated with variation at pigmentation-related loci, and the sets of genes we identified at each scale were largely nonoverlapping. Therefore, our findings suggest that parallel phenotypic evolution is associated with distinct components of the polygenic architecture shifting across each environmental axis to produce redundant adaptive patterns.

Evolutionary Biology↗
NASA NTRS1988

Intraseasonal and interannual variations of tropical convection - A possible link between the 40-50 day oscillation and ENSO?

Twelve-years of NOAA data on outgoing longwave radiation (OLR) are used to trace intraseasonal variations of tropical convection by examining the spatial patterns of OLR variance in the 1-5 day, 20-70 day, and longer-than-180 day bands separately for the northern summer and winter. Based on these patterns, the relative importance of these bands are evaluated and the natural variability of the climate signal and the geographical distribution of potential predictability is assessed. The results of empirical orthogonal functional analyses show that multiple time scales exist in the most dominant patterns of tropical convection variation. These time scales can be identified with those of the 40-50-day oscillation, the El Nino/Southern Oscillation, and the annual cycle. Interpretation of the results in terms of possible interaction between these various time scales is presented.

Lau, Ka-Ming↗
NASA NTRS2005

Scaling device for photographic images

A scaling device projects a known optical pattern into the field of view of a camera, which can be employed as a reference scale in a resulting photograph of a remote object, for example. The device comprises an optical beam projector that projects two or more spaced, parallel optical beams onto a surface of a remotely located object to be photographed. The resulting beam spots or lines on the object are spaced from one another by a known, predetermined distance. As a result, the size of other objects or features in the photograph can be determined through comparison of their size to the known distance between the beam spots. Preferably, the device is a small, battery-powered device that can be attached to a camera and employs one or more laser light sources and associated optics to generate the parallel light beams. In a first embodiment of the invention, a single laser light source is employed, but multiple parallel beams are generated thereby through use of beam splitting optics. In another embodiment, multiple individual laser light sources are employed that are mounted in the device parallel to one another to generate the multiple parallel beams.

Rivera, Jorge E.↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
NASA NTRS2017

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗