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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 847 records · Page 47

Integrative Analysis of Desert Dust Size and Abundance Suggests Less Dust Climate Cooling

Desert dust aerosols affect Earths global energy balance through interactions with radiation, clouds, and ecosystems. But the magnitudes of these effects are so uncertain that it remains unclear whether atmospheric dust has a net warming or cooling effect on global climate. Consequently, it is still uncertain whether large changes in atmospheric dust loading over the past century have slowed or accelerated anthropogenic climate change, and the climate impact of possible future alterations in dust loading is similarly disputed. Here we use an integrative analysis of dust aerosol sizes and abundance to constrain the climatic impact of dust through direct interactions with radiation. Using a combination of observational, experimental, and model data, we find that atmospheric dust is substantially coarser than represented in current climate models. Since coarse dust warms global climate, the dust direct radiative effect (DRE) is likely less cooling than the 0.4 W m superscript 2 estimated by models in a current ensemble. We constrain the dust DRE to -0.20 (-0.48 to +0.20) W m superscript 2, which suggests that the dust DRE produces only about half the cooling that current models estimate, and raises the possibility that dust DRE is actually net warming the planet.

Atmospheric chemistry↗

Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems

Uncertainty visualization plays a critical role in transforming ensemble simulation data into actionable insights by effectively communicating various dimensions of uncertainty within a system. The emergence of artificial intelligence-driven surrogate models trained on multirun ensemble data offers a transformative opportunity to replace computationally intensive simulations with fast estimates, enabling users to explore data spaces with unprecedented depth and interactivity. However, integrating ensemble data and surrogate models into decision-making workflows and tools introduces novel challenges for uncertainty visualization. These include reconciling and clearly communicating the unique uncertainties associated with ensembles and their surrogate model estimates, and leveraging these approximations to inform actionable decisions. This work explores these challenges in the context of high-dimensional data visualization, bridging discrete datasets with their continuous representations and addressing the complexities of systems that support iterative navigation between input and output spaces. We evaluate the role of uncertainty visualization in fostering intuitive, actionable interactions and identify critical hurdles in advancing this frontier of computational simulation.

97 MATHEMATICS AND COMPUTING↗

MEASURE: An integrated data-analysis and model identification facility

The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.

Singh, Jaidip↗

Proposed ozone reference models for the middle atmosphere

Since the publication of the last COSPAR International Reference Atmosphere (CIRA 72), large amounts of ozone data acquired from satellites have become available in addition to increasing quantities of rocketsonde, balloonsonde, Dobson, M83, and Umkehr measurements. From the available archived satellite data, models are developed for the new CIRA using 5 satellite experiments (Nimbus 7 SBUV and LIMS, AEM-2 SAGE, and SME IR and UVS) of the monthly latitudinal and altitudinal variations in the ozone mixing ratio in the middle atmosphere. Standard deviations and interannual variations are also quantified. The satellite models are shown to agree well with a previous reference model based on rocket and balloon measurements.

Keating, G. M.↗

A viscoplastic theory applied to copper

A phenomenologically based viscoplastic model is derived for copper. The model is thermodynamically constrained by the condition of material dissipativity. Two internal state variables are considered. The back stress accounts for strain-induced anisotropy, or kinematic hardening. The drag stress accounts for isotropic hardening. Static and dynamic recovery terms are not coupled in either evolutionary equation. The evolution of drag stress depends on static recovery, while the evolution of back stress depends on dynamic recovery. The material constants are determined from isothermal data. Model predictions are compared with experimental data for thermomechanical test conditions. They are in good agreement at the hot end of the loading cycle, but the model overpredicts the stress response at the cold end of the cycle.

Freed, Alan D.↗

Marshall Space Flight Center Propulsion Systems Department (PSD) KM Initiative

NASA Marshall Space Flight Center s Propulsion Systems Department (PSD) is four months into a fifteen month Knowledge Management (KM) initiative to support enhanced engineering decision making and analyses, faster resolution of anomalies (near-term) and effective, efficient knowledge infused engineering processes, reduced knowledge attrition, and reduced anomaly occurrences (long-term). The near-term objective of this initiative is developing a KM Pilot project, within the context of a 3-5 year KM strategy, to introduce and evaluate the use of KM within PSD. An internal NASA/MSFC PSD KM team was established early in project formulation to maintain a practitioner, user-centric focus throughout the conceptual development, planning and deployment of KM technologies and capabilities with in the PSD. The PSD internal team is supported by the University of Alabama's Aging Infrastructure Systems Center Of Excellence (AISCE), Intergraph Corporation, and The Knowledge Institute. The principle product of the initial four month effort has been strategic planning of PSD KM implementation by first determining the "as is" state of KM capabilities and developing, planning and documenting the roadmap to achieve the desired "to be" state. Activities undertaken to support the planning phase have included data gathering; cultural surveys, group work-sessions, interviews, documentation review, and independent research. Assessments and analyses have been performed including industry benchmarking, related local and Agency initiatives, specific tools and techniques used and strategies for leveraging existing resources, people and technology to achieve common KM goals. Key findings captured in the PSD KM Strategic Plan include the system vision, purpose, stakeholders, prioritized strategic objectives mapped to the top ten practitioner needs and analysis of current resource usage. Opportunities identified from research, analyses, cultural/KM surveys and practitioner interviews include: executive and senior management sponsorship, KM awareness, promotion and training, cultural change management, process improvement, leveraging existing resources and new innovative technologies to align with other NASA KM initiatives (convergence: the big picture). To enable results based incremental implementation and future growth of the KM initiative, key performance measures have been identified including stakeholder value, system utility, learning and growth (knowledge capture, sharing, reduced anomaly recurrence), cultural change, process improvement and return-on-investment. The next steps for the initial implementation spiral (focused on SSME Turbomachinery) have been identified, largely based on the organization and compilation of summary level engineering process models, data capture matrices, functional models and conceptual-level systems architecture. Key elements include detailed KM requirements definition, KM technology architecture assessment, evaluation and selection, deployable KM Pilot design, development, implementation and evaluation, and justifying full implementation (estimated Return-on-Investment). Features identified for the notional system architecture include the knowledge presentation layer (and its components), knowledge network layer (and its components), knowledge storage layer (and its components), User Interface and capabilities. This paper provides a snapshot of the progress to date, the near term planning for deploying the KM pilot project and a forward look at results based growth of KM capabilities with-in the MSFC PSD.

Caraccioli, Paul↗

Marshall Space Flight Center Propulsion Systems Department (PSD) Knowledge Management (KM) Initiative

NASA Marshall Space Flight Center's Propulsion Systems Department (PSD) is four months into a fifteen month Knowledge Management (KM) initiative to support enhanced engineering decision making and analyses, faster resolution of anomalies (near-term) and effective, efficient knowledge infused engineering processes, reduced knowledge attrition, and reduced anomaly occurrences (long-term). The near-term objective of this initiative is developing a KM Pilot project, within the context of a 3-5 year KM strategy, to introduce and evaluate the use of KM within PSD. An internal NASA/MSFC PSD KM team was established early in project formulation to maintain a practitioner, user-centric focus throughout the conceptual development, planning and deployment of KM technologies and capabilities within the PSD. The PSD internal team is supported by the University of Alabama's Aging Infrastructure Systems Center of Excellence (AISCE), lntergraph Corporation, and The Knowledge Institute. The principle product of the initial four month effort has been strategic planning of PSD KNI implementation by first determining the "as is" state of KM capabilities and developing, planning and documenting the roadmap to achieve the desired "to be" state. Activities undertaken to suppo~th e planning phase have included data gathering; cultural surveys, group work-sessions, interviews, documentation review, and independent research. Assessments and analyses have beon pedormed including industry benchmarking, related local and Agency initiatives, specific tools and techniques used and strategies for leveraging existing resources, people and technology to achieve common KM goals. Key findings captured in the PSD KM Strategic Plan include the system vision, purpose, stakeholders, prioritized strategic objectives mapped to the top ten practitioner needs and analysis of current resource usage. Opportunities identified from research, analyses, cultural1KM surveys and practitioner interviews include: executive and senior management sponsorship, KM awareness, promotion and training, cultural change management, process improvement, leveraging existing resources and new innovative technologies to align with other NASA KM initiatives (convergence: the big picture). To enable results based incremental implementation and future growth of the KM initiative, key performance measures have been identified including stakeholder value, system utility, learning and growth (knowledge capture, sharing, reduced anomaly recurrence), cultural change, process improvement and return-on-investment. The next steps for the initial implementation spiral (focused on SSME Turbomachinery) have been identified, largely based on the organization and compilation of summary level engineering process models, data capture matrices, functional models and conceptual-level svstems architecture. Key elements include detailed KM requirements definition, KM technology architecture assessment, - evaluation and selection, deployable KM Pilot design, development, implementation and evaluation, and justifying full implementation (estimated Return-on-Investment). Features identified for the notional system architecture include the knowledge presentation layer (and its components), knowledge network layer (and its components), knowledge storage layer (and its components), User Interface and capabilities. This paper provides a snapshot of the progress to date, the near term planning for deploying the KM pilot project and a forward look at results based growth of KM capabilities with-in the MSFC PSD.

Caraccioli, Paul↗

HighDimMixedModels.jl: Robust high-dimensional mixed-effects models across omics data

High-dimensional mixed-effects models are an increasingly important form of regression in which the number of covariates rivals or exceeds the number of samples, which are collected in groups or clusters. The penalized likelihood approach to fitting these models relies on a coordinate descent algorithm that lacks guarantees of convergence to a global optimum. Here, we empirically study the behavior of this algorithm on simulated and real examples of three types of data that are common in modern biology: transcriptome, genome-wide association, and microbiome data. Our simulations provide new insights into the algorithm’s behavior in these settings, and, comparing the performance of two popular penalties, we demonstrate that the smoothly clipped absolute deviation (SCAD) penalty consistently outperforms the least absolute shrinkage and selection operator (LASSO) penalty in terms of both variable selection and estimation accuracy across omics data. To empower researchers in biology and other fields to fit models with the SCAD penalty, we implement the algorithm in a Julia package, HighDimMixedModels.jl .

Gorstein, Evan↗

Global and Zonal-Mean Hydrological Response to Early Eocene Warmth

Earth's hydrological cycle is expected to intensify in response to global warming, with a “wet-gets-wetter, dry-gets-drier” response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data-modeling approach to reconstruct global and zonal-mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep-Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid- (30°–60°N/S) and high-latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter-Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation-evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter-model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy-derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation-induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns.

Margot J. Cramwinckel↗

Countering Weapons of Mass Destruction Office (CWMD) Data Categorization Study: Chemical, Biological, Radiological, and Nuclear (CBRN) Detection Device Data

Pacific Northwest National Laboratory (PNNL) seeks to address critical questions related to chemical, biological, radiological, and nuclear (CBRN) detection devices. This research aims to enhance the security and understanding of these devices by investigating various aspects of their identification, communication, and functionality. The primary focus is on network security, malware detection, device identification, and intelligence gathering. CBRN data can be categorized in various ways depending on the purpose of CBRN detection devices and the specific context of the applications for analysis. Criteria that can be used to assist in this effort include but are not limited to data type, data protocol, source/destination, application, time, security, and content. This study will inform additional paths for data classification, data profiling, data mapping, and data modeling. This will help the Countering Weapons of Mass Destruction Office (CWMD) better understand their data and make informed decisions based on the insights gained from this study and their application. The CBRN Data Categorization study will include the identification of 5–10 different CBRN detection devices with unique characteristics for assessing and analyzing the data that is being produced by and transmitted from these devices.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Heat generation in aircraft tires under braked rolling conditions

An analytical model was developed to approximate the internal temperature distribution in an aircraft tire operating under conditions of unyawed braked rolling. The model employs an array of elements to represent the tire cross section and considers the heat generated within the tire to be caused by the change in strain energy associated with cyclic tire deflection. The additional heating due to tire slip and stresses induced by braking are superimposed on the previously developed free rolling model. An extensive experimental program was conducted to verify temperatures predicted from the analytical model. Data from these tests were compared with calculations over a range of operating conditions. The model results were in reasonably good agreement with measured values.

Clark, S. K.↗

Flight-Determined Subsonic Lift and Drag Characteristics of Seven Lifting-Body and Wing-Body Reentry Vehicle Configurations With Truncated Bases

This paper examines flight-measured subsonic lift and drag characteristics of seven lifting-body and wing-body reentry vehicle configurations with truncated bases. The seven vehicles are the full-scale M2-F1, M2-F2, HL-10, X-24A, X-24B, and X-15 vehicles and the Space Shuttle prototype. Lift and drag data of the various vehicles are assembled under aerodynamic performance parameters and presented in several analytical and graphical formats. These formats unify the data and allow a greater understanding than studying the vehicles individually allows. Lift-curve slope data are studied with respect to aspect ratio and related to generic wind-tunnel model data and to theory for low-aspect-ratio planforms. The proper definition of reference area was critical for understanding and comparing the lift data. The drag components studied include minimum drag coefficient, lift-related drag, maximum lift-to-drag ratio, and, where available, base pressure coefficients. The effects of fineness ratio on forebody drag were also considered. The influence of forebody drag on afterbody (base) drag at low lift is shown to be related to Hoerner's compilation for body, airfoil, nacelle, and canopy drag. These analyses are intended to provide a useful analytical framework with which to compare and evaluate new vehicle configurations of the same generic family.

Saltzman, Edwin J.↗

Aircraft Icing Weather Data Reporting and Dissemination System

The long-term operational concept of this research is to develop an onboard aircraft system that assesses and reports atmospheric icing conditions automatically and in a timely manner in order to improve aviation safety and the efficiency of aircraft operations via improved real-time and forecast weather products. The idea is to use current measurement capabilities on aircraft equipped with icing sensors and in-flight data communication technologies as a reporting source. Without requiring expensive avionics upgrades, aircraft data must be processed and available for downlink. Ideally, the data from multiple aircraft can then be integrated (along with other real-time and modeled data) on the ground such that aviation-centered icing hazard metrics for volumes of airspace can be assessed. As the effect of icing on different aircraft types can vary, the information should be displayed in meaningful ways such that multiple types of users can understand the information. That is, information must be presented in a manner to allow users to understand the icing conditions with respect to individual concerns and aircraft capabilities. This research provides progress toward this operational concept by: identifying an aircraft platform capable of digitally capturing, processing, and downlinking icing data; identifying the required in situ icing data processing; investigating the requirements for routing the icing data for use by weather products; developing an icing case study in order to gain insight into major air carrier needs; developing and prototyping icing display concepts based on the National Center for Atmospheric Research's existing diagnostic and forecast experimental icing products; and conducting a usability study for the prototyped icing display concepts.

Bass, Ellen J.↗

Aerodynamic Assessment of Flight-Determined Subsonic Lift and Drag Characteristics of Seven Lifting-Body and Wing-Body Reentry Vehicle Configurations

This report examines subsonic flight-measured lift and drag characteristics of seven lifting-body and wing-body reentry vehicle configurations with truncated bases. The seven vehicles are the full-scale M2-F1, M2-F2, HL-10, X-24A, X-24B, and X-15 vehicles and the Space Shuttle Enterprise. Subsonic flight lift and drag data of the various vehicles are assembled under aerodynamic performance parameters and presented in several analytical and graphical formats. These formats are intended to unify the data and allow a greater understanding than individually studying the vehicles allows. Lift-curve slope data are studied with respect to aspect ratio and related to generic wind-tunnel model data and to theory for low-aspect-ratio platforms. The definition of reference area is critical for understanding and comparing the lift data. The drag components studied include minimum drag coefficient, lift-related drag, maximum lift-to drag ratio, and, where available, base pressure coefficients. The influence of forebody drag on afterbody and base drag at low lift is shown to be related to Hoerner's compilation for body, airfoil, nacelle, and canopy drag. This feature may result in a reduced need of surface smoothness for vehicles with a large ratio of base area to wetted area. These analyses are intended to provide a useful analytical framework with which to compare and evaluate new vehicle configurations of the same generic family.

Saltzman, Edwin J.↗

Prebreathe Protocol for Extravehicular Activity Technical Consultation Report

In the performance of EVA by that National Aeronautics and Space Administration (NASA) astronauts, there exists a risk of DCS as the suit pressure is reduced to 4.3 pounds per square inch, absolute (psia) from the International Space Station (ISS) pressure of 14.7 psia. Several DCS-preventive procedures have been developed and implemented. Each of these procedures involve the use of oxygen (O2) prebreathe to effectively washout tissue nitrogen (N2).The management of the ISS Programs convened an expert independent peer review Team to conduct a review of the Decompression Sickness (DCS) risks associated with the Extra Vehicular Activity (EVA) Campout Prebreathe (PB) protocol for its consideration for use on future missions. The major findings and recommendations of the expert panel are: There is no direct experimental data to confirm the potential DCS risks of the Campout PB protocol. However, based on model data, statistical probability, physiology, and information derived from similar PB protocols, there is no compelling evidence to suggest that the Campout PB protocol is less safe than the other NASA approved PB protocols.

Ross, Jerry↗

Atmospheric Carbon Cycle Dynamics Over the Above Domain: an Integrated Analysis Using Aircraft Observations (Arctic-CA) and Model Simulations (GEOS)

The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project conducted six airborne surveys of Alaska and northwestern Canada between April and November 2017 to capture the spatial and temporal gradients of northern high-latitude carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) as part of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4 and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. We observed vertical gradients of CO2, CH4 and CO that vary by eco-region and duration of the sampling period, which spanned the majority of the seasonal cycle. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons with GEOS simulations of atmospheric CO2, CH4 and CO highlight the potential of these multi-species observations to inform improvements in surface flux estimates and the representation of atmospheric transport. GEOS simulations provide estimates of the near surface average CO2 and CH4 enhancements that are well correlated with aircraft observations (R=0.74 and R=0.60 respectively), suggesting that GEOS has reasonable fidelity over this complex and heterogeneous region. This model-data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broadscale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are observed. The study also provides a framework for benchmarking a global model at regional scales, which is needed to use climate models as tools to investigate high-latitude carbon-climate feedbacks.

C Sweeney↗

Jupiter Global Reference Atmospheric Model (Jupiter-GRAM): User Guide

This Technical Memorandum (TM) presents the Jupiter Global Reference Atmospheric Model (Jupiter-GRAM) and the updated features of the GRAMs. Jupiter-GRAM is an engineering-oriented atmospheric model that estimates mean values of atmospheric properties for Jupiter. This TM summarizes the atmospheric data model in Jupiter-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Jupiter-GRAM input and output files and how to interpret Jupiter-GRAM results are also provided.

atmospheric models↗

Human Interfaces and Management of Information (HIMI) Challenges for “In-time” Aviation Safety Management Systems (IASMS)

The envisioned transformation of the National Airspace System to integrate an In-time Aviation Safety Management System(IASMS)to assure safety in Advanced Air Mobility(AAM)brings unprecedented challenges to the design of human interfaces and management of safety information. Safety in design and operational safety assurance are critical factors for how humans will interact with increasingly autonomous systems. The IASMS Concept of Operations builds from traditional commercial operator safety management and scales in complexity to AAM. The transformative changes in future aviation systems pose potential new critical safety risks with novel types of aircraft and other vehicles having different performance capabilities, flying in increasingly complex airspace, and using adaptive contingencies to manage normal and non-normal operations. These changes compel development of new and emerging capabilities that enable innovative ways for humans to interact with data and manage information. In-creasing complexity of AAM corresponds with use of predictive modeling, data analytics, machine learning, and artificial intelligence to effectively address known hazards and emergent risks. The roles of humans will dynamically evolve in increments with this technological and operational evolution. The interfaces for how humans will interact with increasingly complex and assured systems designed to operate autonomously and how information will need to be presented are important challenges to be resolved.

Lawrence J Prinzel↗