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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

NASA NTRS1990

A curved beam test specimen for determining the interlaminar tensile strength of a laminated composite

A curved beam type of test specimen is evaluated for use in determining the through-the-thickness strength of laminated composites. Two variations of a curved beam specimen configuration (semi-circular and elliptical) were tested to failure using static and fatigue loads. The static failure load for the semi-circular specimens was found to be highly sensitive to flaw content, with the specimens falling into two distinct groups. This result supports the use of proof testing for structural validation. Static design allowables are derived based on the Weibull distribution. Fatigue data indicates no measured increase in specimen compliance prior to final fracture. All static and fatigue failures at room temperature dry conditions occurred catastrophically. The elliptical specimens demonstrated unusually high failure strengths indicating the presence of phenomena requiring further study. Results are also included for specimens exposed to a wet environment showing a matrix strength degradation due to moisture content. Further testing is under way to evaluate a fatigue methodology for matrix dominated failures based on residual static strength (wearout).

Hiel, Clement C.↗

NASA NTRS1991

Computer-based video digitizer analysis of surface extension in maize roots: kinetics of growth rate changes during gravitropism

We used a video digitizer system to measure surface extension and curvature in gravistimulated primary roots of maize (Zea mays L.). Downward curvature began about 25 +/- 7 min after gravistimulation and resulted from a combination of enhanced growth along the upper surface and reduced growth along the lower surface relative to growth in vertically oriented controls. The roots curved at a rate of 1.4 +/- 0.5 degrees min-1 but the pattern of curvature varied somewhat. In about 35% of the samples the roots curved steadily downward and the rate of curvature slowed as the root neared 90 degrees. A final angle of about 90 degrees was reached 110 +/- 35 min after the start of gravistimulation. In about 65% of the samples there was a period of backward curvature (partial reversal of curvature) during the response. In some cases (about 15% of those showing a period of reverse bending) this period of backward curvature occurred before the root reached 90 degrees. Following transient backward curvature, downward curvature resumed and the root approached a final angle of about 90 degrees. In about 65% of the roots showing a period of reverse curvature, the roots curved steadily past the vertical, reaching maximum curvature about 205 +/- 65 min after gravistimulation. The direction of curvature then reversed back toward the vertical. After one or two oscillations about the vertical the roots obtained a vertical orientation and the distribution of growth within the root tip became the same as that prior to gravistimulation. The period of transient backward curvature coincided with and was evidently caused by enhancement of growth along the concave and inhibition of growth along the convex side of the curve, a pattern opposite to that prevailing in the earlier stages of downward curvature. There were periods during the gravitropic response when the normally unimodal growth-rate distribution within the elongation zone became bimodal with two peaks of rapid elongation separated by a region of reduced elongation rate. This occurred at different times on the convex and concave sides of the graviresponding root. During the period of steady downward curvature the elongation zone along the convex side extended farther toward the tip than in the vertical control. During the period of reduced rate of curvature, the zone of elongation extended farther toward the tip along the concave side of the root. The data show that the gravitropic response pattern varies with time and involves changes in localized elongation rates as well as changes in the length and position of the elongation zone. Models of root gravitropic curvature based on simple unimodal inhibition of growth along the lower side cannot account for these complex growth patterns.

NASA Discipline Plant Biology↗

NASA NTRS2007

Effects of Gravity on Start-up of a Miniature Loop Heat Pipe with Multiple Evaporators and Multiple Condensers

This paper describes an experimental study on the effect of gravity on the start-up of a miniature loop heat pipe (MLHP) with two evaporators and two condensers. Each evaporator has an outer diameter of 9 mm and has its own integral compensation chamber (CC). The MLHP was placed under five configurations where the relative elevation and tilt among the loop components were varied. The four well-known initial conditions between the evaporator and CC prior to the LHP start-up were created in this experimental study through combinations of: 1) the test configuration; 2) the method of preconditioning the loop prior to start-up, and 3) the heat load distribution among the evaporators. A total of 165 start-ups were conducted under the five test configurations. All of these start-ups were successful. However, the effect of gravity on start-up transients was clearly seen under otherwise the same heat load distribution and sink temperatures. An analytical model was used to simulate the MLHP transient behaviors, and the model predictions agreed very well with the experimental results.

Ku, Jentung↗

NASA NTRS2011

Software Architecture to Support the Evolution of the ISRU RESOLVE Engineering Breadboard Unit 2 (EBU2)

The In-Situ Resource Utilization (ISRU) Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) software provides operation of the physical plant from a remote location with a high-level interface that can access and control the data from external software applications of other subsystems. This software allows autonomous control over the entire system with manual computer control of individual system/process components. It gives non-programmer operators the capability to easily modify the high-level autonomous sequencing while the software is in operation, as well as the ability to modify the low-level, file-based sequences prior to the system operation. Local automated control in a distributed system is also enabled where component control is maintained during the loss of network connectivity with the remote workstation. This innovation also minimizes network traffic. The software architecture commands and controls the latest generation of RESOLVE processes used to obtain, process, and quantify lunar regolith. The system is grouped into six sub-processes: Drill, Crush, Reactor, Lunar Water Resource Demonstration (LWRD), Regolith Volatiles Characterization (RVC) (see example), and Regolith Oxygen Extraction (ROE). Some processes are independent, some are dependent on other processes, and some are independent but run concurrently with other processes. The first goal is to analyze the volatiles emanating from lunar regolith, such as water, carbon monoxide, carbon dioxide, ammonia, hydrogen, and others. This is done by heating the soil and analyzing and capturing the volatilized product. The second goal is to produce water by reducing the soil at high temperatures with hydrogen. This is done by raising the reactor temperature in the range of 800 to 900 C, causing the reaction to progress by adding hydrogen, and then capturing the water product in a desiccant bed. The software needs to run the entire unit and all sub-processes; however, throughout testing, many variables and parameters need to be changed as more is learned about the system operation. The Master Events Controller (MEC) is run on a standard laptop PC using Windows XP. This PC runs in parallel to another laptop that monitors the GC, and a third PC that monitors the drilling/ crushing operation. These three PCs interface to the process through a CompactRIO, OPC Servers, and modems.

Moss, Thomas↗

NASA NTRS2012

A Bayesian Framework for Reliability Analysis of Spacecraft Deployments

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.

Evans, John W.↗

NASA NTRS2013

Investigation of Abnormal Grain Growth in a Friction Stir Welded and Spin-Formed Al-Li Alloy 2195 Crew Module

In order to improve manufacturing efficiency and reduce structural mass and costs in the production of launch vehicle structures, NASA is pursuing a wide-range of innovative, near-net shape manufacturing technologies. A technology that combines friction stir welding (FSW) and spin-forming has been applied to manufacture a single-piece crew module using Aluminum-Lithium (AL-Li) Alloy 2195. Plate size limitations for Al-Li alloy 2195 require that two plates be FSW together to produce a spin-forming blank of sufficient size to form the crew module. Subsequent forming of the FSW results in abnormal grain growth (AGG) within the weld region upon solution heat treatment (SHT), which detrimentally impacts strength, ductility, and fracture toughness. The current study seeks to identify microstructural factors that contribute to the development of AGG. Electron backscatter diffraction (EBSD) was used to correlate driving forces for AGG, such as stored energy, texture, and grain size distributions, with the propensity for AGG. Additionally, developmental annealing treatments prior to SHT are examined to reduce or eliminate the occurrence of AGG by promoting continuous, or uniform, grain growth

Tayon, Wesley A.↗

NASA NTRS2014

H Diffusion in Olivine and Pyroxene from Peridotite Xenoliths and a Hawaiian Magma Speedometer

Hydrogen is present as a trace element in olivine and pyroxene and its content distribution in the mantle results from melting and metasomatic processes. Here we examine how these H contents can be disturbed during decompression. Hydrogen was analyzed by FTIR in olivine and pyroxene of spinel peridotite xenoliths from Salt Lake Crater (SLC) nephelinites which are part of the rejuvenated volcanism at Oahu (Hawaii) [1,2]. H mobility in pyroxene resulting from spinel exsolution during mantle upwelling Most pyroxenes in SLC peridotites exhibit exsolutions, characterized by spinel inclusions. Pyroxene edges where no exsolution are present have less H then their core near the spinel. Given that H does not enter spinel [3], subsolidus requilibration may have concentrated H in the pyroxene adjacent to the spinel exsolution during mantle upwelling. H diffusion in olivine during xenolith transport by its host magma and host magma ascent rates Olivines have lower water contents at the edge and near fractures compared to at their core, while the concentrations of all other chemical elements appear homogeneous. This suggests that some of the initial water has diffused out of the olivine. Water loss from the olivine is thought to occur during host-magma ascent and xenolith transport to the surface [4-6]. Diffusion modeling matches best the data when the initial water content used is that measured at the core of the olivines, implying that mantle water contents are preserved at the core of the olivines. The 3225 cm(sup -1) OH band at times varies independantly of other OH bands, suggesting uneven H distribution in olivine defects likely acquired during mantle metasomatism just prior to eruption and unequilibrated. Diffusion times (1-48 hrs) combined with depths of peridotite equilibration or of magma start of degassing allow to calculate ascent rates for the host nephelinite of 0.1 to 27 m/s.

Peslier, A. H.↗

DOE OSTI2022

Estimation of Sea Spray Aerosol Surface Area Over the Southern Ocean Using Scattering Measurements

This study focuses on methods to estimate dry marine aerosol surface area (SA) from bulk optical measurements. Aerosol SA is used in many models' ice nucleating particle (INP) parameterizations, as well as influencing particle light scattering, hygroscopic growth, and reactivity, but direct observations are scarce in the Southern Ocean (SO). Two campaigns jointly conducted in austral summer 2018 provided co-located measurements of aerosol SA from particle size distributions and lidar to evaluate SA estimation methods in this region. Mie theory calculations based on measured size distributions were used to test a proposed approximation for dry aerosol SA, which relies on estimating effective scattering efficiency (Q) as a function of Ångström exponent (å). For distributions with dry å < 1, Q = 2 was found to be a good approximation within ±50%, but for distributions with dry å > 1, an assumption of Q = 3 as in some prior studies underestimates dry aerosol SA by a factor of 2 or more. We propose a new relationship between dry å and Q, which can be used for –0.2 < å < 2, and suggest å = 0.8 as the cutoff between primary and secondary marine aerosol-dominated distributions. Application of a published methodology to retrieve dry marine aerosol SA from lidar extinction profiles overestimated aerosol SA by a factor of 3–5 during these campaigns. Using Microtops aerosol optical thickness measurements, we derive alternative lidar conversion parameters from our observations, applicable to marine aerosol over the SO.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Distributed parameter modeling for the control of flexible spacecraft

The use of FEMs of spacecraft structural dynamics is a common practice, but it has a number of shortcomings. Distributed-parameter models offer an alternative, but present both advantages and difficulties. First, the model order does not have to be reduced prior to the inclusion of control system dynamics. This advantage eliminates the risk involved with model 'order reduction'. Second, distributed parameter models inherently involve fewer parameters, thereby enabling more accurate parameter estimation using experimental data. Third, it is possible to include the damping in the basic model, thereby increasing the accuracy of the structural damping. The difficulty in generating distributed parameter models of complex spacecraft configurations has been greatly alleviated by the use of PDEMOD, BUNVIS-RG, or DISTEL. PDEMOD is being developed for simultaneously modeling structural dynamics and control system dynamics.

Taylor, Lawrence W., Jr.↗

NASA NTRSDate not supplied

Implications of seagrass changes on manatee distributions in the Indian River Lagoon waters surrounding NASA’s Kennedy Space Center

The presentation will discuss Kennedy Space Center’s (KSC) long term monitoring of seagrass and manatees in the Banana River (BR) prior to 2010, the remarkable decline in seagrass habitat that occurred thereafter, and the notable shift in manatee distribution. For Banana River, from 2010 to 2015, seagrass declined while manatee presence increased, with an average of 525 manatees per flight in 2015. After 2016, both seagrasses and manatee presence declined. Concurrently, increasing manatee numbers were reported for Mosquito Lagoon (ML), where historical manatee occurrence was relatively low. In 2016, aerial surveys were expanded to include the southern half of ML to document this significant distribution shift. By 2022, ML had become the hub of manatee occurrence on KSC, with an average of 946 manatees per flight and only 48 per flight in BR. These data enhance information for IRL stakeholders regarding seagrass habitat and manatee protection in the northern IRL.

Seagrass↗

NASA NTRSDate not supplied

Implications of Seagrass Changes on Manatee Distributions in the Indian River Lagoon Waters Surrounding NASA's Kennedy Space Center

Indian River Lagoon↗

DOE OSTI2024

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Electric Utility Distribution Costs: Scoping Study on Trends, Drivers, and Possible Response Strategies [Slides]

This scoping study synthesizes information that will help stakeholders understand the scope, scale, and drivers of recent increases in investor-owned utility (IOU) expenditures on local distribution power grids, while providing regulators and other decision-makers with potential strategies to keep electricity bills down. The study includes five distinct components. Drawing first on data from FERC Form 1, it summarizes key trends in past and recent IOU distribution costs. Next, through a review of a sample of distribution-system plans, it characterizes material drivers of planned distribution expenditures. Ultimately, regulators must approve cost recovery for IOU expenditures, including those for the distribution system. The study therefore also: examines trends in utility requests and regulatory approvals related to changes in retail rates and return on equity; identifies areas where utility shareholder and customer incentives may be misaligned; and develops a menu of options that state regulators might consider to optimize distribution system expenditures. Some of the key findings include: - IOU distribution spending at a national level has grown by 6%/yr since 2014 in real dollar terms, 4x faster than in the prior 20 years and consisting mostly of capital (not operating) expenditure. - On a per-kWh basis, increases in IOU distribution costs since 2014 represent over 30% of the overall national-average increase in retail electricity rates. - Regional spending growth has ranged from 2-8%/yr, with larger estimated rate impacts in CAISO, then NYISO & ISO-NE, and then the Southeast, MISO & PJM (see figure). - Some utilities are planning for significantly increased distribution system spending. Planned spending on managing the existing system (asset replacement, safety & reliability, and resilience are all important drivers) exceeds that for capacity expansion. - IOU rate increase requests ($18 billion in 2025) and public utility commission (PUC) approval levels (average of 64% of requested amounts from 2021-2025) have recently hit multi-decadal highs. - PUCs in New England and the Southeast have recently approved a greater fraction of rate requests (>75%, on average) than in ther regions, while PUCs in California and the Southeast have generally authorized higher equity returns than in other regions. - Regulators have many tools to tackle potential misalignments between utility and customer interests and, more specifically, to optimize and reduce distribution costs. Shorter-term options include those related to return on equity, capital structure, depreciation, trackers, construction work in progress, and securitization. Longer-term options include performance-based regulation and a wide variety of planning-related requirements. All options embed important tradeoffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗

NASA NTRS2023

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counterintuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfvén waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, α = 2 as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed >600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: preflare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that α = 1.63 ± 0.03. This is below the critical threshold, suggesting that Alfvén waves are an important driver of coronal heating.

Astrostatistics distributions↗

NASA NTRS2010

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

A new approach for distribution of grid points on the surface and in the volume has been developed. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Pirzadeh, Shahyar↗

NASA NTRS2019

Effect of Latitude Bias in Entry Angle on Ground Casualty Risk from Naturally Decaying Space Objects

An improvement to the long-term estimation of ground casualties from naturally decaying space objects is the refinement to the distribution of entry angle at the entry interface as a function of latitude. Previous analyses were based on an assumed "small angle," typically -0.1°, and entry interface at the equator. This study expands on work by Bacon and Matney that indicated there is significant latitude bias in the location of reentries, compared to prior assumptions of equal temporal probability. A new model has been developed, which describes the distribution of entry angle as a function of orbital inclination and argument of latitude. This model has been used to generate inputs for ODPO’s certified reentry survivability software, Object Reentry Survival Analysis Tool (ORSAT). These new results are compared with the prior standard model to assess the magnitude of the effects on reentry casualty risk.

Ostrom, Chris L.↗

DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗