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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Evidence of Carrier Localization in InAsSb/InSb Digital Alloy nBn Detector

Recently we have demonstrated a novel method of extending the cut-off wavelength of InAsSb nBn detectors, by incorporating a series of monolayers of InSb. Here we study photoluminescence and minority carrier lifetime of this InAsSb/InSb digital alloy. While increasing temperature from 15 K to 40 K we show a 14 meV blue shift of the photoluminescence peak energy and a decrease in lifetime. This deviation from the expected Varshni empirical relation indicates strong carrier localization. We contrast to photoluminescence and lifetime results in bulk InAsSb. We discuss implications of this localization for design of digital alloy InAsSb/InSb nBn detectors.

Pepper, Brian J.↗
NASA NTRS2020

The New Landsat Collection-2 Digital Elevation Model

The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset(NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from theCollection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 meters was measured. By using theses improved vertical values in a line of sight algorithm, horizonta improvements were noted in some of the most mountainous regions over multiple 30-meter Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.

Shannon Franks↗
NASA NTRSDate not supplied

Digital Lunar Exploration Sites (DLES)

It has been almost 50 years since humans last set foot on the Moon. With NASA’s Artemis program, the United States and its international and commercial partners are embarking on a new endeavor to explore the lunar surface. Before we return, we will have simulated every aspect of these future missions. Many of these models and simulations (M&S) will rely on well-known and commonly-used technologies, some of which trace their origins back to the Apollo program. However, M&S has advanced significantly, as have the underlying computational capabilities. As a result, we are able to model many more aspects of the Artemis vehicles and support systems with significantly improved detail and confidence. Accurately and efficiently modeling the lunar environment will be critical to simulating the Artemis elements and mission activities. This includes characterizing and modeling lunar topography, smaller craters, exposed surface rocks, lunar regolith, surface lighting, and ambient thermal environment. These are all necessary for understanding fundamental behaviors and performance of vehicles and support systems in the lunar environment and are often determining factors in the selection of exploration sites and defining mission profiles. The Astromaterials Research and Exploration Sciences (ARES) team in the Exploration Integration and Science Directorate at NASA’s Johnson Space Center (JSC) and the NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch at JSC are developing and maintaining the Digital Lunar Exploration Sites (DLES) data, documentation, and software packages. This data is being fed directly into a diverse collection of graphics and simulation environments, where it is used to construct the closest known truth for numerous potential Lunar South Pole landing sites. DLES is available to projects across NASA and particularly the Artemis program to support coordinated digital representations of the lunar environment. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

Lunar↗
NASA NTRS2021

The Deep-Time Digital Earth program: data-driven discovery in geosciences

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth’s evolution.

Chengshan Wang↗
NASA NTRS2023

Spacesuit Fit and Mobility Assessments by Digital Human Modeling

Spacesuit Fit and Mobility Assessments by Digital Human Modeling K. Han Kim (Leidos, Inc.) Elizabeth A. Benson (KBR, Inc.) Sudhakar L. Rajulu (NASA Johnson Space Center) Spacesuits are required to accommodate safe operations for astronauts across gender and a wide variety of body shapes and sizes. This goal has been of particular importance given the increasing diversity of NASA crewmembers for upcoming Missions. While testing with design prototypes is a critical step for spacesuit development, iterative mockup design, fabrication, and human subject tests can be extremely costly and time consuming. Moreover, testing with a limited subject pool has often raised questions for validity, as test subjects need to represent the entire astronaut population, not only of the past or current, but also the future. This study is aimed at demonstrating how digital human modeling (DHM) tools have been built and directly supported NASA spacesuit developments. With DHM, the computer aided design (CAD) model of a spacesuit was integrated with human body models. Two use scenarios are presented in this paper, namely fit and mobility. For fit assessments, the suit-to-body contact and compression patterns were estimated using 3D human body scan models virtually wearing a spacesuit model. A statistical fit classifier was made from the contact patterns and applied against a large database of body scans (N=2,500). With this technique, the NASA reference design spacesuit Exploration EVA Mobility Unit (xEMU)was verified to accommodate 90% of the astronaut-like population, with the critical dimensions covering 1stto 99thpercentiles of the target body measurements. A similar technique assessed XEMU mobility. The maximum reach envelopes were considered, within which the work objects and critical hardware interfaces should be located for safe and ergonomic operations. While the reach envelope geometry varies significantly with the suit wearer’s body size and strength, the existing test data did not include the subjects critically required to define suit mobility requirements, such as very small females or large males. Using the xEMU virtual model kinematically simulated and permuted for a hypothetical wearer, however, the existing data were statistically transformed and scaled. This method enabled for a parametric estimation of the reach envelopes from the 1stpercentile female or 99thpercentile male. The outcome was successfully incorporated for requirement developments. With the new DHM tools, human integration of the spacesuit was structurally simulated and predictively assessed, which would have been otherwise impossible. Also, the needs for iterative mockup and subject tests were significantly reduced, which resulted in time and cost saving. Additional work is in progress to integrate additional vehicles, tools, and hardware with DHM framework.

K Han Kim↗
NASA NTRSDate not supplied

ECLSS Four-Bed CO2 Scrubber Digital Twin

The ECLSS Digital Twin is a cloud-based simulation of the Four-Bed CO2 Scrubber, currently one of the primary means of removing carbon dioxide onboard the International Space Station, that operationalizes SME-developed multi-physics models and replicates conditions of the actual hardware in near real-time. In addition to providing insight into the system’s performance, it will enable prognostics, diagnostics, predictive maintenance, and simulated off-nominal scenarios. By leveraging digital representations, projects can save resources and gain a better understanding of their physical systems with the goal of building robust and reliable hardware for future deep space exploration. The use of data infrastructure in the cloud allows for streamlined analysis and visualization on a much larger scale than is possible with current tools.

Jared Wilson↗
NASA NTRSDate not supplied

Harnessing the Digital Transformation for Development of Hybrid Electric Aircraft Propulsion Control Systems

Hybrid electric aircraft propulsion is an emerging technology that presents a variety of potential benefits along with technical integration challenges. Developing these new propulsion architectures with their complex control systems, and ultimately proving their benefit, is a multistep process that goes from concept, to analysis, to dynamic simulation, to hardware in the loop testing, to full scale testing and beyond. This effort is being revolutionized and indeed enabled by new digital tools that support the increasing technology readiness level throughout the maturation process. NASA has developed and made available a suite of digital tools that ease the path from concept to implementation. The three packages are the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), and the Thermal Systems Analysis Toolbox (TSAT). These tools are interactive, complementary, and compatible with each other. T-MATS is a modular thermodynamic modeling framework designed for creating custom component level models of jet engines. EMTAT is a modeling framework used to simulate a variety of power electronic devices, using both physics-based and power flow calculations. TSAT is a framework for modeling and analysis of dynamic heat transfer. These packages all consist of graphical, drag-and-drop, parameterizable building blocks representing various components of the system to be modeled, e.g., compressors, turbines, motors, energy storage devices, etc. They are designed to enable the user to model and simulate the end-to-end dynamic operation of a hybrid powertrain at the timescale of the turbomachinery, capturing mechanical, electrical, and thermal interactions. This paper will describe through multiple examples how these tools have been used successfully in several of the early stages of hybrid electric propulsion system development, from the initial system modeling to real-time interactive pilot-in-the-loop simulation to physical hardware-in-the-loop testing, each step bringing the technology closer to fruition.

Electrified Propulsion↗
NASA NTRS2024

The Knowledge-based Digital Platform Concept for Advanced Air Mobility Research and Development

National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers (SE) together across organizational boundaries. The overarching vision for the KbDP Concept for AAM R&D is a substantial undertaking. The initial concept and implementation will focus on UAM operations to tractably learn and adjust the concept with a manageable database. Lessons learned and best practices with a smaller scope will enable successful scalability to AAM R&D or even to the entire modes of transportation and logistics. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. Initial implementation of three KbDP concepts of use shows promising benefits to NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject. It is envisioned that the KbDP will manage an information database defined by mathematical, data science, and system engineering principles. AIML algorithms play a vital role in this KbDP concept by extracting meaningful knowledge from the information database, which the human user leverages to improve the efficiency and effectiveness of their research greatly.

ATM↗
NASA NTRSDate not supplied

Quality of Candidate Flights and Submission Prediction in Collaborative Digital Departure Reroute

Collaborative Digital Departure Reroute (CDDR) enables the reroute of flights using a flight operator proposed set of alternative route options, referred to as Trajectory Option Set (TOS), in order to reduce delay on the airport's surface and in the Metroplex environment. The reroute functionality is enabled through NASA's Digital Information Platform (DIP). TOS candidate flights are defined as flights with an alternative route with delay savings greater than the flight operator defined relative trajectory cost. This paper analyzes the TOS candidate flights at Dallas/Fort Worth International Airport (KDFW) in the North Texas Metroplex to gain insight into which candidate flights are higher quality through a scoring method. This insight will inform refinements to help CDDR focus on high quality reroute opportunities. Binary classification models for predicting the flight operator's submission of candidate flights are also explored in this paper.

Machine Learning↗
NASA NTRSDate not supplied

Novel Observing Strategies (NOS) and Earth System Digital Twins (ESDT) for Disaster Resilience

"Earth systems have now been observed continuously for more than 50 years, not only from space but also from airplanes, balloons and in-situ sensors. With the addition of commercial remote sensing providers, many more Internet-of-Things sensors and new NASA and international observatories being planned, these incredible amounts of data will soon be augmented by even larger amounts of diverse data and therefore will become more and more difficult to access, integrate, understand and utilize. At the same time, because of climate change and its impacts, in order to predict, manage, and mitigate the effects of extreme science events and disasters, the information produced by all of this data needs to be optimized, organized and analyzed in such a way that it can be utilized by traditional as well as many new non-traditional users. This calls for the development of observing systems that are agile, coordinated and responsive to events of interest, and for information systems to be dynamic, interactive and fast. With these objectives in mind, the Advanced Information Systems Technology (AIST) Program has been developing technologies that will allow for the development of Novel Observing Strategies (NOS) in a distributed, coordinated fashion (i.e., similar to an “Internet-of-Earth-Things”), as well as for the development of novel information systems or Earth System Digital Twins (ESDT) that will build a digital replica of the past and current states of the Earth systems, will derive forecasts of future states under nominal assumptions and will also offer the capability to investigate many hypothetical evolution scenarios under varying impact assumptions. Both NOS and ESDT will be facilitated by the unprecedented advances of Artificial Intelligence technologies, especially Machine Learning (ML), for extracting relevant information from these large amounts of data, for fusing and assimilating diverse data together and for running complex models faster. Together NOS and ESDT will help build the capabilities needed to anticipate, predict and mitigate the effects of future disasters."

Earth Science Remote Sensing; Information Systems↗
NASA NTRSDate not supplied

Quality of Candidate Flights and Submission Prediction in Collaborative Digital Departure Reroute

Collaborative Digital Departure Reroute (CDDR) enables the reroute of flights using a flight operator proposed set of alternative route options, referred to as Trajectory Option Set (TOS), in order to reduce delay on the airport's surface and in the Metroplex environment. The reroute functionality is enabled through NASA's Digital Information Platform (DIP). TOS candidate flights are defined as flights with an alternative route with delay savings greater than the flight operator defined relative trajectory cost. This paper analyzes the TOS candidate flights at Dallas/Fort Worth International Airport (KDFW) in the North Texas Metroplex to gain insight into which candidate flights are higher quality through a scoring method. This insight will inform refinements to help CDDR focus on high quality reroute opportunities. Binary classification models for predicting the flight operator's submission of candidate flights are also explored in this paper.

Machine Learning↗
NASA NTRSDate not supplied

Comprehensive Digital Twin of a Macro-fluidic Electrochemical Reactor to Optimize the Electrochemical-based Recovery of O2 from Metabolic CO2

Future long-duration missions will require a sustainable and efficient system capable of yielding a minimum of 75% O 2 recovery from metabolic CO 2 to achieve self-sufficiency for long space missions beyond Earth's low orbit. A Macro-fluidic Electrochemical Reactor (MFECR) development effort to electrochemically recover O 2 from CO 2 is underway at NASA Marshall Space Flight Center (MSFC) to increase current O 2 recovery efficiency and reduce air revitalization (AR) system complexity at the International Space Station (ISS) habitat and future long missions. The authors have developed and deployed a digital twin of an actual single cell of the MFECR via a comprehensive 3D multiphysics model that thoroughly replicates the exact configuration and fluid/material domains of the MFECR. This model's electrochemical physics consists of multicomponent-multiphase electrochemical-driven reactions leading to CO 2 conversion to C 2 H 4 and CO along with the formation of H 2 on the cathode in parallel with the generation of O 2 and H 2 O on the anode. This electrochemical model is coupled with all the physics phenomena involved in the process, including but not limited to fluid and non-ideal mass transfer of reactant and product species in free and porous media, convective/conduction/radiative heat transfer, and conduction of DC electrical current with Joule heating generation. The digital twin has proved to be an essential tool for performing different qualitative studies, including the effect of reducing the height (increasing the respect ratio) of the serpentine walls, leading to a further redesign of the EDU (the newly redesigned MFECR EDU has been fabricated and is expected to be used in future tests), the evaluation of setting different MFECRs connected in series, and the assessment of feeding air directly to the MFECR skipping the preceding metabolic CO 2 separation from air. The MFECR's test stand is fully automated and equipped with several inline measurements (flow, pressure, temperature, pH, component concentration) systems on all six MFECR's IO streams, allowing reliable experimental validation of the model, parametric determination of all electrochemical reactions, and process optimization.

Jesus A Dominguez↗
NASA NTRSDate not supplied

Digital Engineering for HabWorlds

New role within HWOTM: Digital Architect, meant to help the program set up and execute digital engineering ONLY as appropriate for mission success. Reports directly to the Systems Engineering team. First principles look at engineering, collaboration, & communication requirements. Analysis of alternatives presented to the MSE and project team for decisions.

Jama↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRSDate not supplied

NASA Earth System Digital Twins (ESDT) Prototypes

NASA IST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Earth System Digital Twins (ESDTs) are information systems for understanding, forecasting, and conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. In order to define ESDT's technologies and architectures that will be needed for developing future operational ESTDs, the IST Program is developing several ESDT prototypes representing various use case domains and technological/architectural needs.

Earth Science Remote Sensing↗
NASA NTRSDate not supplied

Technology for Earth System Digital Twins

NASA IST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Earth System Digital Twins (ESDTs) are information systems for understanding, forecasting, and conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. This presentation will address the main technology and architecture challenges that need to be addressed to develop end-to-end ESDTs; along with these challenges, some of the solutions proposed by IST projects will be discussed.

Earth Science Remote Sensing; Information Systems↗
NASA NTRS2024

Real-Time Temperature Field State Observer and Digital Replica to Support Cyber-Physical Testing

Cyber-physical testing is a class of experimental methods in which a system is partitioned into physical and numerical components to study its overall behavior. Transfer systems are typically needed to capture relevant interactions by enforcing appropriate interface conditions between the physical and numerical portions. While cyber-physical testing is often performed using lumped-parameter systems, thermomechanical cyber-physical testing requires the use of thermal actuators as transfer systems to apply a thermal condition over a spatially distributed region or surface. Thus, the interactions between the numerical and physical components are of a distributed nature, i.e., a field rather than point values. In this paper, we develop and experimentally validate a state observer for temperature fields to enable thermomechanical cyber-physical testing. The state observer provides continuous estimates of temperature over a surface of the thermal actuator using only temperature measurements at discrete locations. The estimated temperature field is then leveraged to account for localized mechanical defects in the interface condition. The method consists of building a digital replica of one portion of the control plant. By imposing defects in the digital replica it is used to generate and output the response of a thermal load pattern that represents that of a physical system with mechanical defects.

Manuel Salmeron↗
DOE OSTI2011

Using the transverse digital damper as a real-time tune monitor for the Booster synchrotron at Fermilab

The Fermilab Booster is a fast ramping (15Hz) synchrotron which accelerates protons from 400MeV to 8GeV. During commissioning of a transverse digital damper system, it was shown that the damper could provide a measurement of the machine tune throughout the cycle by exciting just 1 of the 84 bunches with minimal impact on the machine operation. The algorithms used to make the measurement have been incorporated into the damper FPGA firmware allowing for real-time tune monitoring of all Booster cycles. A new Booster tune monitor was implemented in the digital damper which has minimal impact on the Booster operation. The tune measures the tunes in two planes over the energy ramping cycle with an accuracy of 0.01 in real time.

43 PARTICLE ACCELERATORS↗