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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Transmission overhaul and replacement predictions using Weibull and renewal theory

A method to estimate the frequency of transmission overhauls is presented. This method is based on the two-parameter Weibull statistical distribution for component life. A second method is presented to estimate the number of replacement components needed to support the transmission overhaul pattern. The second method is based on renewal theory. Confidence statistics are applied with both methods to improve the statistical estimate of sample behavior. A transmission example is also presented to illustrate the use of the methods. Transmission overhaul frequency and component replacement calculations are included in the example.

Savage, M.↗
NASA NTRS1991

Shedding patterns of the near-wake vortices behind a circular cylinder

The unsteady incompressible Navier-Stokes equations have been accurately solved for the laminar flow past a circular cylinder in the Reynolds number range 50-200. A direct elliptic solver called the SEVP is used to rapidly advance the streamfunction in time, facilitating the overall convergence to the fully periodic or quasi-steady state. A new integral-series method is developed for the far-field streamfunction condition on a finite two-dimensional computational domain. The use of fourth-order Hermitain relations for the convection terms in the conservation-form vorticity transport equation has also contributed to the good comparison of the present results with the earlier experimental data. The vortex-shedding patterns visualized by the experimentalist are numerically reproduced here in the given Reynolds number range. Discussions that may be helpful in interpreting the behavior of the shedding frequency are presented in the main text.

Sa, Jong-Youb↗
NASA NTRS1992

Adding dynamic rules to self-organizing fuzzy systems

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Buhusi, Catalin V.↗
NASA NTRS2007

A New Sea Ice Model: Pancakes to Metrics

We are developing, testing, and validating a new sea ice dynamics model that treats the ice cover as an elastic/decohesive material in the permanent pack and includes the correct frazil/pancake behavior in the marginal zone. Two salient features of present ice dynamics models are that they do not: 1) reproduce the oriented fracture patterns of openings and closings in the pack ice, and 2) accurately model the effects of frazil/pancake ice formation in the ice margin. These poorly modeled areas account for a substantial portion of the ice growth, turbulent heat flux to the atmosphere, salt flux to the ocean, and energy dissipation due to slippage, ridging, and rafting, in the Arctic. Existing sea ice models have shown limited success in predicting the degree to which a lead will open for prescribed or observed forcing conditions. An important aspect of the new model we are developing is that the existence of cracks, along with their orientation, opening, and closing, is predicted. To put this effort in perspective a short history of ice dynamics modeling and data collection is presented. The RGPS data set is used to validate the model. As part of the testing and validation of the model, we are working on a new metric for comparing linear features (leads and ridges) in the data and model to be used in data assimilation for this model. The model framework is presented as well as some results showing the creation and development of leads in a simulation of ice dynamics in the Beaufort Sea. Other presentations by the authors will show other results from this effort.

Coon, M.↗
NASA NTRS2012

Influence of Global Vegetation on Mid-Tropospheric CO2 Early Results

AIRS Mid-Tropospheric CO2 shows a high degree of horizontal variability. Ongoing efforts show AIRS data influenced by global circulation patterns including El Nino Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) What is the influence of global vegetation cycle on CO2 seasonal behavior? (1) Can we correlate mid-trop CO2 seasonal variability with global vegetation for different regions? (2) For now: First look at zonal averages and Land Vegetation (ocean biomass later) (3) Goal: Sanity Check on AIRS Data Seasonal Cycle, Solicit interest by carbon cycle community

climatology↗
DOE OSTI2020

Spatiotemporal Pattern Recognition in the PMU Signals in the WECC system

Phasor measurement unit (PMU) data has been used by multiple power system applications, including state estimation, post event analysis, oscillation detection, model validation, and many others. Still, due to its big data nature and availability to general research institutions, comprehensive understanding of the spatiotemporal patterns and underlying mechanisms are incomplete. This study applies a set of signal processing and machine learning approaches aiming at deciphering the characteristic behaviors of multiple phasor measurement units (PMUs) attributes (e.g., voltage, frequency, rate of change of frequency, phase angle), including their auto-correlation, cross-dependence, similarities and discrepancies across units and temporal scales, and distributions of anomalies and their linkages to potential external factors such as weather events. Data analytics are applied to PMUs from the U.S. Western Electricity Coordinating Council (WECC) system. The PMU measurements, recorded events, outages, and weather extremes are all from real world datasets. The findings from the study and mechanistic understanding of the PMU dynamics help provide guidance on system control or preventing blackouts. The derived metrics can be directly used for adjusting or filtering simulated PMU data used for advanced algorithm development.

Hou, Zhangshuan↗
DOE OSTI2020

Winners are not keepers: Characterizing household engagement, gains, and energy patterns in demand response using machine learning in the United States

Demand-response programs can help utilities manage rapidly evolving electric grids, but these programs are subject to the complexities of human behavior. This paper explores a novel method for uncovering heterogeneity in households. In this work, we use a machine-learning method known as a Conditional Inference Tree (c-tree) algorithm to categorize households based on their energy behavior characteristics collected via smart meters, and explore how this translates through into heterogeneity in their real-world response to a DR program. Using data from randomized controlled trial, we generate estimates of the changes in energy use caused by the program within each household group. Our results show that the c-tree approach differentiates households by their energy-use characteristics in a way that increases the spread in enrollment rates and critical peak reduction among household groups, compared with the spreads achieved via several conventional segmentation methods. Thus, the c-tree analysis enables the most tailored targeting of major potential energy savers and could provide the greatest increase in cost-effectiveness of household recruitment into DR programs. Our results also offer fresh insights into the relationships between household energy behavior characteristics – such as peak energy use and “structural winningness” (the ability to save money under a DR program without changing energy-use behaviors) – and household decisions about enrolling in DR programs and reducing energy use. Our research also demonstrates the potential of smart meter data, combined with machine learning and econometric methods, to provide significant value to utilities, program implementers, researchers, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

Human performance cognitive-behavioral modeling: a benefit for occupational safety

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Occupational Health↗
DOE OSTI2015

In Situ TEM Study of Reversible and Irreversible Electroforming in Pt/Ti:NiO/Pt Heterostructures

Experimental verification of the microscopic origin of resistance switching in metal/oxide/metal heterostructures is needed for applications in non-volatile memory and neuromorphic computing. Numerous reports suggest that resistance switching in NiO is caused by local reduction of the oxide layer into nanoscale conducting filaments, but few reports have shown experimental evidence correlating electroforming with site-specific changes in composition. We have investigated the mechanisms of reversible and irreversible electroforming in 250–500 nm wide pillars patterned from a single Ta/Ti/Pt/Ti-doped NiO/Pt/Ta heterostructure and have shown that these can coexist within a single sample. We performed in situ transmission electron microscopy (TEM) electroform- ing and switching on each pillar to correlate the local electron transport behavior with microstructure and composition in each pillar. DFT calculations fitted to electron energy loss spectroscopy data showed that the Ti-doped NiO layer is partially reduced after reversible electroforming, with the formation of oxygen vacancies ordered into lines in the <110> direction. However, under the same probing conditions, adjacent pillars show irreversible electroforming caused by electromigration of metallic Ta to form a single bridge across the oxide layer. We propose that the different electroforming behaviors are related to microstructural variations across the sample and may lead to switching variability.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

EVs@Scale Next-Gen Profiles - Fleet Utilization 2024

As part of the U.S. Department of Energy’s EVs@Scale initiative, the Next-Gen Profiles (NGP) project provides a comprehensive, data-driven analysis of electric vehicle (EV) and electric vehicle supply equipment (EVSE) operations across real-world fleet deployments. This paper presents findings from the NGP’s Fleet Utilization study, which investigates operational behavior and asset usage across seventeen EV fleets and two EVSE fleets, encompassing a wide range of vehicle types and use cases. Data collected from diverse sources—varying in format and temporal resolution—are first reformatted into a unified structure. From this harmonized dataset, a suite of rigorously defined performance metrics is calculated at an hourly cadence, enabling consistent cross-comparison of charging, routing, and other key operational behaviors. Amid rapidly increasing EV adoption and growing demands for energy-efficient fleet operations, the analysis reveals clear utilization trends—including diurnal and weekly activity cycles, differences in short versus long charging session dependencies, and route-specific energy usage patterns. These findings highlight the need for tailored infrastructure strategies and the deployment of advanced energy management systems, such as Distributed Energy Resource Management Systems (DERMS) and Site Energy Management Systems (SEMS), which can optimize charging schedules and mitigate peak loads. By leveraging anonymized, harmonized datasets and standardized metrics, this study offers critical insights into fleet behavior and performance, providing a foundation to improve operational efficiency, reduce costs, and enable the scalable deployment of electrified transportation.

Wells, Landon↗
DOE OSTI2018

Large-scale Meteorological Organization of Extreme Weather Events: Final Technical Report

Although the occurrence of regional extreme weather events (EWEs) such as cold air outbreaks, heat waves, droughts and floods are known to be related to planetary climate modes (PCMs) such as the El-Nino Southern Oscillation or North Atlantic Oscillation, intermediate meteorological patterns (IMPs) such as jet stream blocking, cyclones, and high pressure systems are required to connect PCMs to EWEs. Our project has revealed a physical pathway for the interplay among EWEs, IMPs and PCMs. Under support of this award, we have characterized the behavior of IMPs that cause winter cold air outbreaks, extreme floods and warm season dry spells in the US. This includes formulating meteorological “fingerprints” for easily identifying IMPs. The research performed includes a parallel analysis of how well modern climate models are able to simulate IMP behavior. We have also developed a novel approach for characterizing PCM structures and identifying EWE-LMP-PCM linkages. We discovered that dry spells occurring during spring and summer over the US are affected by changes in the North Pacific Ocean temperature. We further revealed the physical origin of a critical jet stream pattern occurring over the North Pacific Ocean that provides a “bridge” between the water cycles of East Asia and North America, respectively. We developed an advanced diagnostic technique (called piecewise tendency diagnosis or PTD) to understand the physical causes for the IMP formation and EWE-LMP-PCM linkages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Glioblastoma Recurrence Patterns After Radiation Therapy With Regard to the Subventricular Zone

Purpose: We evaluated the influence of tumor location and tumor spread in primary glioblastoma (GBM), with respect to the subventricular zone (SVZ), on recurrence behavior, progression-free survival (PFS), and overall survival (OS). Methods and Materials: 607 patients (376 male and 231 female) with a median age of 61.3 years (range, 3.0-87.9 years) and primary GBM treated with radiation therapy (RT) from 2004 to 2012 at a single institution were included in this retrospective study. Preoperative images and follow-up examination results were assessed to evaluate tumor location. Tumors were classified according to the tumor location in relation to the SVZ. Results: The median PFS of the study population was 5.2 months (range, 1-91 months), and the median OS was 13.8 months (range, 1-102 months). Kaplan-Meier analysis showed that tumor location in close proximity to the SVZ was associated with a significant decline in PFS and OS (4.8 and 12.3 months, respectively; each P<.001). Furthermore, in cases where tumors were involved with the SVZ, distant cerebral progression (43.8%; P=.005) and multifocal progression (39.8%; P=.008) were more common. Interestingly, opening of the ventricle during the previous surgery showed no impact on PFS and OS. Conclusion: GBM in close proximity to the SVZ was associated with decreased survival and had a higher risk of multifocal or distant progression. Ventricle opening during surgery had no effect on survival rates.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1990

Artificial intelligence techniques for modeling database user behavior

The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

Tanner, Steve↗
DOE OSTI2021

Comparing LLC-Memory Traffic between CPU and GPU Architectures

The cache hierarchy in modern CPUs and GPUs is becoming increasingly complex, which makes understanding the handshake between the memory access patterns and the cache hierarchy difficult. Moreover, the details of different cache policies are not publicly available. Therefore, the research community relies on observation to understand the relationship between memory access patterns and cache hierarchy. Our previous studies delved into the different microarchitectures of Intel CPUs. In this study, GPUs from NVIDIA and AMD are considered. Even though the execution models in CPUs and GPUs are distinct, this study attempts to correlate the behavior of the cache hierarchy of CPUs and GPUs. Using the knowledge gathered from studying Intel CPUs, the similarities and dissimilarities between CPUs and GPUs are identified. Through model evaluation, this study provides a proof of concept that traffic between last-level cache and memory can be predicted for sequential streaming and strided access patterns on GPUs.

Monil, M. A. H.↗
DOE OSTI2015

Microstructure evolution and mechanical behavior of a high strength dual-phase steel under monotonic loading

Transmission electron microscopy (TEM) microstructures of a high-strength dual-phase steel DP800 have been examined after moderate plastic deformations in simple shear and uniaxial tension. Special attention has been paid to the effect of the intergranular hard phase (martensite) on the microstructure evolution in the near-grain boundary regions. Quantitative parameters of dislocation patterning have been determined and compared with the similar characteristics of previously examined single-phase steels. The dislocation patterning in the interiors of the ferrite grains in DP800 steel is found to be similar to that already observed in the single-phase IF (Interstitial Free) steel whereas the martensite-affected zones present a delay in patterning and display very high gradients of continuous (gradual) disorientations associated with local internal stresses. The above stresses are shown to control the work-hardening of dual-phase materials at moderate strains for monotonic loading and are assumed to influence their microstructure evolution and mechanical behavior under strain-path changes. - Highlights: • The microstructure evolution has been studied by TEM in a DP800 steel. • It is influenced by both martensite and dislocations in the initial state. • The DP800 steel presents a high work-hardening rate due to internal stresses.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Diabatic visualization shows effects of micro-fins on evaporation of R410A: Smooth, axial micro-fin, and helical micro-fin tubes

A novel approach to visualize the flow boiling inside a clear micro-fin tube under diabatic conditions is presented. Transparent smooth, axial micro-fin, and helical micro-fin tubes are made by 3D printing. The 3D printed tube is placed inside a glass tube and heated by the transparent secondary fluid flowing between the two tubes for providing the evaporation conditions and transparency. R410A flow boiling and the flow patterns in the three geometries captured with a high speed camera are compared. The experimental results show that micro-fin geometry influences flow behavior. Bubbles are mainly generated in the groove region due to a higher superheat than the fin region. Some of the liquid refrigerant is trapped in the grooves of the upper part of the micro-fin tube when the slug flow is present, and bubbles are generated in this thin liquid layer. In addition, the bubbles in the helical micro-fin tube are easier to merge because of the obstacle of the fin geometry for the bubble flowing path. As the two bubble merge, the conversion of surface free energy causes the bubble to travel with a higher velocity.

3D printed↗
DOE OSTI2020

Tailoring ductile-phase toughened tungsten hierarchical microstructures for plasma-facing materials

Biological materials, such as bones, nacre, etc., have been found to show attractive and unique combinations of stiffness, strength and fracture toughness. Research has been conducted in various engineering areas to mimic the naturally hierarchical microstructures or nanostructures of these materials to produce materials with optimum stiffness, high strength and fracture toughness for their intended structural applications. In the same objective, this work applies a multiscale microstructural approach recently developed to investigate the deformation and fracture behavior of ductile phase toughened tungsten (W) materials such as tungsten-nickel/iron (W-Ni/Fe) composites that possess lamellar-like and hierarchical “brick-and-mortar” (BAM) microstructures. First, the approach is used to simulate tensile loading of W-Ni/Fe specimens cut out from hot-rolled W-Ni/Fe plates which possess lamellar-like microstructures. The finite element model of the gage section of the specimen consists of a W-Ni/Fe dual-phase microstructural domain in which the constitutive behaviors of W and Ni/Fe phases are described by an elastic-plastic damage model. The predicted material stress-strain response and crack pattern development as a function of loading are then compared to the corresponding experimental results to determine the constitutive model parameters for W and Ni/Fe. Subsequently, the model parameters are used to analyze W-Ni/Fe BAM microstructures that are artificially created to investigate the effects of microstructural features and morphologies on the composite stress-strain response, damage, and fracture patterns. The modeling shows that regular BAM microstructures that experience bridging mechanism combined with crack penetration across W-phase regions exhibit significantly higher strengths than the rather random lamellar-like microstructures. More significantly, however adjusting the brick’s length-to-height ratio, the BAM microstructure can be designed to allow a more distributed damage zone which leads to increased strength, ductility and fracture energy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Side Chain Regioisomers that Dictate Optical Properties and Mechanofluorochromism through Crystal Packing

Designing strong interactions into $π$-conjugated materials can direct their typically uncontrolled molecular packing and is an important strategy toward tuning their technologically relevant properties in the solid state. In this paper we demonstrate unconventional control over solid-state fluorescence and mechanofluorochromism (MFC) through regiochemical substitutions in side chains of 12 three-ring phenylene ethynylenes (PEs) that employ fluoroarene–arene (ArF–ArH) interactions between tetrafluoro ArF pendants and PE main chains to direct crystal packing, with single-atom variations of the lone proton in ArF pendants between 4-hydro, 5-hydro, and 6-hydro substitution yielding in two cases dramatically different fluorescence and MFC behavior. X-ray crystal structures reveal key intermolecular interactions of ArF rings, including their lone protons, which vary as a function of substitution pattern and contribute to optical properties in solids. Rarely reported, particularly with such dramatic results, this systematic study on regiochemical effects over solid-state properties demonstrates the versatility of using discrete, directional interactions of side chains for noncovalent control in conjugated materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗