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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Giunta, Anthony A.↗
DOE OSTI2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Machine learning framework for assessment of microbial factory performance

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Manchester Coding Option for SpaceWire: Providing Choices for System Level Design

This paper proposes an optional coding scheme for SpaceWire in lieu of the current Data Strobe scheme for three reasons. First reason is to provide a straightforward method for electrical isolation of the interface; secondly to provide ability to reduce the mass and bend radius of the SpaceWire cable; and thirdly to provide a means for a common physical layer over which multiple spacecraft onboard data link protocols could operate for a wide range of data rates. The intent is to accomplish these goals without significant change to existing SpaceWire design investments. The ability to optionally use Manchester coding in place of the current Data Strobe coding provides the ability to DC balanced the signal transitions unlike the SpaceWire Data Strobe coding; and therefore the ability to isolate the electrical interface without concern. Additionally, because the Manchester code has the clock and data encoded on the same signal, the number of wires of the existing SpaceWire cable could be optionally reduced by 50. This reduction could be an important consideration for many users of SpaceWire as indicated by the already existing effort underway by the SpaceWire working group to reduce the cable mass and bend radius by elimination of shields. However, reducing the signal count by half would provide even greater gains. It is proposed to restrict the data rate for the optional Manchester coding to a fixed data rate of 10 Megabits per second (Mbps) in order to make the necessary changes simple and still able to run in current radiation tolerant Field Programmable Gate Arrays (FPGAs). Even with this constraint, 10 Mbps will meet many applications where SpaceWire is used. These include command and control applications and many instruments applications with have moderate data rate. For most NASA flight implementations, SpaceWire designs are in rad-tolerant FPGAs, and the desire to preserve the heritage design investment is important for cost and risk considerations. The Manchester coding option can be accommodated in existing designs with only changes to the FPGA.

Electrical Isolation↗
DOE OSTI2021

Scatter gather using key-value store

Scatter gather operation(s) are performed by accessing a shared memory that is shared amongst nodes interconnected through network(s) and having a CNS shared amongst the nodes. Data is gathered from multiple processes at corresponding multiple nodes into location(s) in the CNS, and tuple(s) having a same tuple name are created in the CNS. The tuple(s) have information referencing the gathered data in the location(s). Alternatively, data that has been gathered using the same tuple name is scattered to multiple processes participating in the CNS. The scattering uses the tuple(s) in the CNS, and is performed from the location(s) into other location(s) at one or multiple nodes for one or multiple processes at the corresponding one or multiple nodes. Both the gathering data and the scattering data may also be performed.

Jacob, Philip↗
NASA NTRS1974

Bone mineral computation with a rectilinear scanner

A portable rectilinear transmission scanner and associated computerized data reduction techniques for estimating bone mineral content are described. This unit can be easily disassembled for transport to various measurement sites and has been used to estimate the bone mineral content of the os calcis, radius, and ulna in the Apollo and Skylab astronauts. The scanner is used to obtain multiple rows of data from which a bone profile is derived. Bone edges are determined with the aid of a digital computer program which employs an algorithm that determines the greatest rate of change of the counting rate.

Ullman, J.↗
NASA NTRS2002

Probabilistic #D data fusion for multiresolution surface generation

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

3D data fusion multiresolution surface generation ↗
NASA NTRS1985

Preliminary science results from the Shuttle Imaging Radar-B

Preliminary results of analyzing digital radar imagery data obtained by the SIR-B aboard the Space Shuttle Challenger STS 41-G are presented. The data cover 5 million square kilometers of the earth surface between 57 deg north and south latitudes. Radar imagery of the same target at different incidence angles was used to classify surfaces by their backscatter response as a function of incidence angle. The SIR-B proved to be useful for collecting multiple incidence angle data sets over a broad range of targets, providing information in the areas of geology, archeology, forestry, agriculture, oceanography, geography, and hydrology. The analysis is also used to optimize radar parameters such as look angle for future missions.

Ruzek, M.↗
NASA NTRS2021

Secondary Science Teachers’ Implementation of a Curricular Intervention When Teaching With Global Climate Models

In the past decade, emphasis on promoting “climate literacy” in K-16 science classrooms has increased. Teachers play a critical role in cultivating these opportunities, especially in secondary science classrooms. However, most prior climate education research has focused on students and student learning; little is known about how teachers implement climate-focused curricular interventions. Here, we report findings from a concurrent mixed methods, multiple-case study of four secondary science teachers’ implementation of a new, NGSS-aligned, model-centric climate curriculum module grounded in the use of a data-driven, computer-based climate modeling tool—Easy Global Climate Model (EzGCM). We employ multiple data sources, including video-recorded classroom observations, interviews, and instructional artifacts, and both qualitative and quantitative analyses, to investigate how teachers implemented the curriculum. Findings show that, overall, teachers implemented the curriculum in ways that were less model-centric than designed, placing greater emphasis on EzGCM itself rather than using the model to investigate Earth’s changing climate. Additionally, we present detailed single-case studies of each participant teacher that highlight differences in teachers’ implementation of the curriculum module and their reasoning for making observed instructional decisions. This research sheds light on the design of secondary science learning environments by illustrating the varied ways teachers implement a climate-focused curriculum to support students’ developing climate literacy. This has important implications for the design of climate-focused curriculum and supports for teachers.

Secondary science teaching↗
NASA NTRS2004

Viewing ISS Data in Real Time via the Internet

EZStream is a computer program that enables authorized users at diverse terrestrial locations to view, in real time, data generated by scientific payloads aboard the International Space Station (ISS). The only computation/communication resource needed for use of EZStream is a computer equipped with standard Web-browser software and a connection to the Internet. EZStream runs in conjunction with the TReK software, described in a prior NASA Tech Briefs article, that coordinates multiple streams of data for the ground communication system of the ISS. EZStream includes server components that interact with TReK within the ISS ground communication system and client components that reside in the users' remote computers. Once an authorized client has logged in, a server component of EZStream pulls the requested data from a TReK application-program interface and sends the data to the client. Future EZStream enhancements will include (1) extensions that enable the server to receive and process arbitrary data streams on its own and (2) a Web-based graphical-user-interface-building subprogram that enables a client who lacks programming expertise to create customized display Web pages.

Myers, Gerry↗
NASA NTRS1990

Cooperating Expert Systems For Automated Monitoring And Diagnostics

Human operators freer to perform nonrepetitive tasks. Expert software system for monitoring multiple streams of sensory data from interacting equipment subsystems undergoing development. Organized hierarchically to monitor multiple equipment subsystems simultaneously. Each expert software subsystem responsible for one of equipment subsystems. Intended to assist human analysts in interpretation of telemetry data indicating operating statuses of subsystems of spacecraft, enables analysts to maintain desired mode(s) of operation, and helps to correct anomalies in subsystems or in overall spacecraft system. Other versions devised for industrial monitoring and analysis tasks similarly complicated.

Schwuttke, Ursula M.↗
NASA NTRS2009

Protocol for Communication Networking for Formation Flying

An application-layer protocol and a network architecture have been proposed for data communications among multiple autonomous spacecraft that are required to fly in a precise formation in order to perform scientific observations. The protocol could also be applied to other autonomous vehicles operating in formation, including robotic aircraft, robotic land vehicles, and robotic underwater vehicles. A group of spacecraft or other vehicles to which the protocol applies could be characterized as a precision-formation- flying (PFF) network, and each vehicle could be characterized as a node in the PFF network. In order to support precise formation flying, it would be necessary to establish a corresponding communication network, through which the vehicles could exchange position and orientation data and formation-control commands. The communication network must enable communication during early phases of a mission, when little positional knowledge is available. Particularly during early mission phases, the distances among vehicles may be so large that communication could be achieved only by relaying across multiple links. The large distances and need for omnidirectional coverage would limit communication links to operation at low bandwidth during these mission phases. Once the vehicles were in formation and distances were shorter, the communication network would be required to provide high-bandwidth, low-jitter service to support tight formation-control loops. The proposed protocol and architecture, intended to satisfy the aforementioned and other requirements, are based on a standard layered-reference-model concept. The proposed application protocol would be used in conjunction with conventional network, data-link, and physical-layer protocols. The proposed protocol includes the ubiquitous Institute of Electrical and Electronics Engineers (IEEE) 802.11 medium access control (MAC) protocol to be used in the datalink layer. In addition to its widespread and proven use in diverse local-area networks, this protocol offers both (1) a random- access mode needed for the early PFF deployment phase and (2) a time-bounded-services mode needed during PFF-maintenance operations. Switching between these two modes could be controlled by upper-layer entities using standard link-management mechanisms. Because the early deployment phase of a PFF mission can be expected to involve multihop relaying to achieve network connectivity (see figure), the proposed protocol includes the open shortest path first (OSPF) network protocol that is commonly used in the Internet. Each spacecraft in a PFF network would be in one of seven distinct states as the mission evolved from initial deployment, through coarse formation, and into precise formation. Reconfiguration of the formation to perform different scientific observations would also cause state changes among the network nodes. The application protocol provides for recognition and tracking of the seven states for each node and for protocol changes under specified conditions to adapt the network and satisfy communication requirements associated with the current PFF mission phase. Except during early deployment, when peer-to-peer random access discovery methods would be used, the application protocol provides for operation in a centralized manner.

Jennings, Esther↗
DOE OSTI2018

Resource Analysis for Deep Direct-Use Feasibility Study in East Texas

The National Renewable Energy Laboratory, Southern Methodist University Geothermal Laboratory, Eastman Chemical, Turbine Air Systems, and the Electric Power Research Institute are evaluating the feasibility of using geothermal heat to improve the efficiency of natural gas power plants. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of the Sabine Uplift. The study is focused on determining the potential for a geothermal reservoir within a 10 km radius of the site as defined by data from existing geological studies and cross-sections within the depths of 2,100 to 3,400 meters. Wells within a 20 km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, and oil and gas field porosity and permeability. The geothermal reservoir model is based on the multiple formation top data sources, published literature data, and well log interpretations within the 10 km radius. Area thickness estimates, reservoir extent bounding parameters, potential flow rates, and temperatures are combined to calculate a reservoir productivity index and develop a reservoir production model. Historical fluid volumes production data are used as an independent check for the reservoir productivity index and production model results. The reservoir parameters calculated here are being used for the surface engineering model to determine the economic viability of using geothermal fluids for a deep direct use application at this site. The data files are submitted as separate workbooks in 'content model' format, including: Well Fluid Production, Heat Flow, and Geologic Reservoir.

15 GEOTHERMAL ENERGY↗
NASA NTRS2013

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Shen, Suhung↗
DOE OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

OSIRIS-REx Earth Return Orbit Determination Analysis and Performance

Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) was a NASA New Frontiers–class asteroid sample return mission to (101955) Bennu. OSIRIS-REx performed a series of Trajectory Cor-rection Maneuver (TCM)s to target an Entry Interface (EI) point for Earth Return and entry, descent, and landing (EDL). On September 24, 2023, the Sample Re-turn Capsule (SRC) separated from the spacecraft, entered the atmosphere, and ultimately landed at the Utah Test and Training Range for recovery. This paper gives an overview of the updated orbit determination (OD) covariance analysis that went into the Earth return and reentry analysis after asteroid departure. Tracking data assumptions and multiple filter cases are analyzed to show performance. Operational OD results from TCM-9 and subsequent targeting maneuvers up to entry interface are provided. We show parameter error analysis contributions from the OD setup and their breakdown in the B-Plane error ellipses. Finally, we discuss the terminal OD solutions into EI and reconstruction results using onboard image data.

Jason M. Leonard↗
NASA NTRS2009

The 2nd Generation Real Time Mission Monitor (RTMM) Development

The NASA Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decisionmaking for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery and orbit data, radar and other surface observations (e.g., lightning location network data), airborne navigation and instrument data sets, model output parameters, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. In order to improve the usefulness and efficiency of the RTMM system, capabilities are being developed to allow the end-user to easily configure RTMM applications based on their mission-specific requirements and objectives. This second generation RTMM is being redesigned to take advantage of the Google plug-in capabilities to run multiple applications in a web browser rather than the original single application Google Earth approach. Currently RTMM employs a limited Service Oriented Architecture approach to enable discovery of mission specific resources. We are expanding the RTMM architecture such that it will more effectively utilize the Open Geospatial Consortium Sensor Web Enablement services and other new technology software tools and components. These modifications and extensions will result in a robust, versatile RTMM system that will greatly increase flexibility of the user to choose which science data sets and support applications to view and/or use. The improvements brought about by RTMM 2nd generation system will provide mission planners and airborne scientists with enhanced decision-making tools and capabilities to more efficiently plan, prepare and execute missions, as well as to playback and review past mission data. To paraphrase the old television commercial RTMM doesn t make the airborne science, it makes the airborne science easier.

Blakeslee, Richard↗
DOE OSTI2023

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

59 BASIC BIOLOGICAL SCIENCES↗