SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
In this activity, students will record and graph temperature data to learn about NASA's Mars Microprobe Mission, Deep Space 2, and how the properties of a material affect the transfer of heat.
For long-duration missions on other planetary bodies, the use of in situ materials will become increasingly critical. As man's presence on these bodies expands, so must the structures to accommodate them, including habitats, laboratories, berms, radiation shielding for surface reactors, garages, solar storm shelters, greenhouses, etc. The use of in situ materials will significantly offset required launch upmass and volume issues. Under the auspices of the In Situ Fabrication & Repair (ISFR) Program at NASA/Marshall Space Flight Center (MSFC), the Surface Structures project has been developing materials and construction technologies to support development of these in situ structures. This paper will report on the development of several of these technologies at MSFC's Prototype Development Laboratory (PDL). These technologies include, but are not limited to, development of extruded concrete and inflatable concrete dome technologies based on waterless and water-based concretes, development of regolith-based blocks with potential radiation shielding binders including polyurethane and polyethylene, pressure regulation systems for inflatable structures, production of glass fibers and rebar derived from molten lunar regolith simulant, development of regolithbag structures, and others, including automation design issues. Results to date and lessons learned will be presented, along with recommendations for future activities.
In the past, flight and ground systems have been developed largely-independently, with the flight system taking the lead, and dominating the development process. Operability issues have been addressed poorly in planning, requirements, design, I&T, and system-contracting activities. In many cases, as documented in lessons-learned, this has resulted in significant avoidable increases in cost and risk. With complex missions and systems, operability is being recognized as an important end-to-end design issue. Never-the-less, lessons-learned and operability concepts remain, in many cases, poorly understood and sporadically applied. A key to effective application of operability concepts is adopting a 'mission system' paradigm. In this paradigm, flight and ground systems are treated, from an engineering and management perspective, as inter-related elements of a larger mission system. The mission system consists of flight hardware, flight software, telecom services, ground data system, testbeds, flight teams, science teams, flight operations processes, procedures, and facilities. The system is designed in functional layers, which span flight and ground. It is designed in response to project-level requirements, mission design and an operations concept, and is developed incrementally, with early and frequent integration of flight and ground components.
Excessive vibration of turbomachinery blades causes high cycle fatigue problems which require damping treatments to mitigate vibration levels. One method is the use of piezoelectric materials as passive or active dampers. Based on the technical challenges and requirements learned from previous turbomachinery rotor blades research, an effort has been made to investigate the effectiveness of a shunted piezoelectric for the turbomachinery rotor blades vibration control, specifically for a condition with centrifugal rotation. While ample research has been performed on the use of a piezoelectric material with electric circuits to attempt to control the structural vibration damping, very little study has been done regarding rotational effects. The present study attempts to fill this void. Specifically, the objectives of this study are: (a) to create and analyze finite element models for harmonic forced response vibration analysis coupled with shunted piezoelectric circuits for engine blade operational conditions, (b) to validate the experimental test approaches with numerical results and vice versa, and (c) to establish a numerical modeling capability for vibration control using shunted piezoelectric circuits under rotation. Study has focused on a resonant damping control using shunted piezoelectric patches on plate specimens. Tests and analyses were performed for both non-spinning and spinning conditions. The finite element (FE) shunted piezoelectric circuit damping simulations were performed using the ANSYS Multiphysics code for the resistive and inductive circuit piezoelectric simulations of both conditions. The FE results showed a good correlation with experimental test results. Tests and analyses of shunted piezoelectric damping control, demonstrating with plate specimens, show a great potential to reduce blade vibrations under centrifugal loading.
The ISS partnership has seen a substantial increase in research accomplished, crew efforts devoted to research, and results of ongoing research and technology development. The ISS laboratory is providing a unique environment for research and international collaboration that benefits humankind. Benefits come from the engineering development, the international partnership, and from the research results. Benefits can be of three different types: scientific discovery, applications to life on Earth, and applications to future exploration. Working across all ISS partners, we identified key themes where the activities on the ISS improve the lives of people on Earth--not only within the partner nations, but also in other nations of the world. Three major themes of benefits to life on earth emerged from our review: benefits to human health, education, and Earth observation and disaster response. Other themes are growing as use of the ISS continues. Benefits to human health range from advancements in surgical technology, improved telemedicine, and new treatments for disease. Earth observations from the ISS provide a wide range of observations that include: marine vessel tracking, disaster monitoring and climate change. The ISS participates in a number of educational activities aimed to inspire students of all ages to learn about science, technology, engineering and mathematics. To date over 63 countries have directly participated in some aspect of ISS research or education. In summarizing these benefits and accomplishments, ISS partners are also identifying ways to further extend the benefits to people in developing countries for the benefits of humankind.
As a key instrument for NASA s Earth Observing System (EOS), the Moderate Resolution Imaging Spectroradiometer (MODIS) has made significant contributions to the remote sensing community with its unprecedented amount of data products continuously generated from its observations and freely distributed to users worldwide. MODIS observations, covering spectral regions from visible (VIS) to long-wave infrared (LWIR), have enabled a broad range of research activities and applications for studies of the earth s interactive system of land, oceans, and atmosphere. In addition to extensive pre-launch measurements, developed to characterize sensor performance, MODIS carries a set of on-board calibrators (OBC) that can be used to track on-orbit changes of various sensor characteristics. Most importantly, dedicated and continuous calibration efforts have been made to maintain sensor data quality. This paper provides an overview of the MODIS calibration program, on-orbit calibration activities, methods, and performance. Key calibration results and lessons learned from the MODIS calibration effort are also presented in this paper.
The ISS partnership has seen a substantial increase in research accomplished, crew efforts devoted to research, and results of ongoing research and technology development. The ISS laboratory is providing a unique environment for research and international collaboration that benefits humankind. Benefits come from the engineering development, the international partnership, and from the research results. Benefits can be of three different types: scientific discovery, applications to life on Earth, and applications to future exploration. Working across all ISS partners, we identified key themes where the activities on the ISS improve the lives of people on Earth -- not only within the partner nations, but also in other nations of the world. Three major themes of benefits to life on earth emerged from our review: benefits to human health, education, and Earth observation and disaster response. Other themes are growing as use of the ISS continues. Benefits to human health range from advancements in surgical technology, improved telemedicine, and new treatments for disease. Earth observations from the ISS provide a wide range of observations that include: marine vessel tracking, disaster monitoring and climate change. The ISS participates in a number of educational activities aimed to inspire students of all ages to learn about science, technology, engineering and mathematics. To date over 63 countries have directly participated in some aspect of ISS research or education. In summarizing these benefits and accomplishments, ISS partners are also identifying ways to further extend the benefits to people in developing countries for the benefits of humankind.
The STEM on Station team is part of Education which is part of the External Relations organization (ERO). ERO has traditional goals based around BHAG (Big Hairy Audacious Goal). The BHAG model is simplified to a saying: Everything we do stimulates actions by others to advance human space exploration. The STEM on Station education initiate is a project focused on bringing off the earth research and learning into classrooms. Educational resources such as lesson plans, activities to connect with the space station and STEM related contests are available and hosted by the STEM on Station team along with their partners such as Texas Instruments. These educational activities engage teachers and students in the current happenings aboard the international space station, inspiring the next generation of space explorers.
Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.
The DEVELOP Program, part of NASA’s Earth Applied Sciences’ Capacity Building Program, conducts 50-70 feasibility studies each year that utilize Earth observations to address local decision-making challenges and help inform action. DEVELOP uses these projects as the mechanism to build skills in its participants and partner organizations to assess and apply satellite data insights to environmental decision-making processes. While organized by thematic focus (ex. water resource management, ecological forecasting, disaster management), projects use a multidisciplinary team approach with teams of students, recent graduates, early career professionals, and transitioning career professionals, bringing different disciplines, life experience, and perspectives to execute projects that have been collaboratively designed with end-user partner organizations (federal agencies, state and local governments, non-profit and for-profit organizations, and international organizations). Projects are interdisciplinary in nature as they integrate methods from multiple disciplines, with a focus on the incorporation of satellite data with other data sources such as socioeconomic and demographic data, in situ measurements, model outputs, and partners’ knowledge, and take place under the guidance of science advisors from NASA, academia, and other partner organizations. The culmination of these multidisciplinary teams working on projects that draw from interdisciplinary methods and approaches, is a transdisciplinary solution for the partner organizations to explore further for potential adoption. This presentation will highlight the DEVELOP model of co-production and collaboration, lessons learned integrating people and project methodologies, and impact assessment activities surrounding the program’s efforts.
For over two decades, NASA Glenn Research Center (GRC) has been supporting the development of Radioisotope Power Systems (RPS). NASA desires higher conversion efficiency RPS options that are reliable and robust with long life design. Dynamic conversion, such as Stirling offer the potential for higher conversion efficiencies than current RPS but have yet to be demonstrated in a flight application. GRC developed a non-nuclear representation of a RPS consisting of a pair of Advanced Stirling Convertors (ASC), a Dual Convertor Controller (DCC), and associated support equipment. The DCC was designed by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL) to actively control a pair of ASCs. Based on lessons learned, three generations of DCCs were developed over the past decade. After each generation of the DCC was completed, tests were performed to verify functionality. These tests include acceptance testing, fault testing, characterization testing, and testing with the Radioisotope Power System Systems Integration Laboratory (RSIL). Acceptance testing verifies that the DCC can control a pair of ASCs to produce full convertor power output. The fault testing verifies that the DCC can maintain control of the ASCs during either internal or external faults. Characterization testing verifies the functionality of the DCC over a range of bus voltage values. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The DCC design, development, lessons learned, test results, and future work are presented in this paper.
NASA’s Earth Science Division (ESD) is committed to empower Environmental Justice (EJ) communities by expanding awareness, accessibility, and use of Earth science data to enable contributions to Earth science research and applications. To that end, the NASA Earth Science Data Systems (ESDS) Program developed an EJ Data Catalog, a simple guide to NASA datasets and socioeconomic datasets that may be useful in EJ research. The EJ Data Catalog is divided by topics—such as disasters, urban flooding, extreme heat, food availability, water availability, climate, and health and air quality—and possible use cases for each dataset. The new version of the EJ Data Catalog is now integrated into NASA’s Science Discovery Engine (SDE), an open-source science infrastructure to enable collaborative and interdisciplinary science. In this workshop you will learn about NASA’s Equity and Environmental Justice (EEJ) activities and opportunities as well as participate on an interactive live demo of the new Science Discovery Engine for Environmental Justice.
This report accompanies is a set of charts that will be presented at the 2024 LEARN Forum. This report is the result of an activity sponsored by Dr. Wanda Peters, Deputy Associate Administrator of Programs, who tasked Florence Tan and Carolyn Mercer with gathering insights from SmallSat/ Class D missions that could be extrapolated to enhance Class A-C missions.
Airline pilots must anticipate potential threats to passenger safety and efficient flight. Such anticipation needs to occur at both the system and individual levels, yet no formal training for these anticipatory behaviors currently exists. The emerging field of resilience engineering provides a framework to explore this problem. Given the complex nature of this problem, the assessment portion of the project constituted a challenge. Simulator time is expensive as simulators are costly to run, and they are extremely limited in number. Also, by the nature of their work, pilots as a group are hard to connect with in person; thus, asynchronous methods were adopted. Further, to ensure that authentic pilot behaviors were observed, task-based scenarios were used rather than focus group or interview protocols. This session explores the design of asynchronous learning and a measure for assessing pilot anticipatory behaviors outside of a simulator to help design learning opportunities for pilots. The scenario-based and active assessment items will be discussed in detail, and demonstrations of these items will be shared. These items constitute the bulk of the challenge for this work. At the time of this writing, data is being collected to assess the effectiveness of the interactive training module and validate the measures. This data will be analyzed and presented as part of the session. This will include any linkages between the scenario-based and traditional assessment items.
The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.
Teachers in today s classrooms are bound by state required skills, education standards, and high stakes testing. How can they gain skills and confidence to replace units or individual activities with curriculum that incorporates project and inquiry-based learning and promotes authentic research in the classroom? The key to promoting classroom authentic research experiences lies in educator professional development that is structured around teacher needs. The Expedition Earth and Beyond Program is a new geosciences program based at the NASA Johnson Space Center designed to engage, inspire and educate teachers and students in grades 5-14. The program promotes authentic research experiences for classrooms and uses strategies that will help NASA reach its education goals while still allowing educators to teach required standards. Teachers will have access to experts in terrestrial and planetary remote sensing and geoscience; this will enhance their use of content, structure, and relevant experiences to gain the confidence and skills they need to actively engage students in authentic research experiences. Integrated and powerful educational strategies are used to build skills and confidence in teachers. The strategies are as follows: 1) creating Standards-aligned, inquiry-based curricular resources as ready-to-use materials that can be modified by teachers to fit their unique classroom situation; 2) providing ongoing professional development opportunities that focus on active experiences using curricular materials, inquiry-based techniques and expanding content knowledge; 3) connecting science experts to classrooms to deepen content knowledge and provide relevance to classroom activities and real world applications; 4) facilitating students sharing research with their peers and scientists reinforcing their active participation and contributions to research. These components of the Expedition Earth and Beyond Education Program will be enhanced by providing exciting and diverse research opportunities that are inspired by views of Earth from space taken by astronauts on board the International Space Station. The interest and connection to viewing our home planet from space will inevitably spark questions that will drive students to pursue their research investigations, as well as forming a basis for comparisons to the exploration of other planetary bodies in our solar system.
We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.
Understanding the 3-dimensional structure of clouds is of crucial importance to modeling our changing climate. Active sensors, such as radar and lidar, provide accurate vertical cloud profiles, but are mostly restricted to along-track sampling. Passive sensors can capture a wide swath, but struggle to see beneath cloud tops. In essence, both types of products are restricted to two dimensions: as a cross-section in the active case, and an image in the passive case. However, multi-angle sensor configurations contain implicit information about 3D structure, due to parallax and atmospheric path differences. Extracting that implicit information can be challenging, requiring computationally expensive radiative transfer techniques. Machine learning, as an alternative, may be able to capture some of the complexity of a full 3D radiative transfer solution with significantly less computational expense. In this work, we make three contributions towards understanding 3D cloud structure from multi-angle polarimetry. First, we introduce a large-scale, publicly available dataset that fuses existing cloud products into a format more amenable to machine learning. This dataset treats multi-angle polarimetry as an input, and radar-based vertical cloud profiles as an output. Second, we describe and evaluate strong baseline machine learning models based that predict these profiles from the passive imagery. Notably, these models are trained only on center-swath labels, but can predict cloud profiles over the entire passive imagery swath. Third, we leverage the information-theoretic nature of machine learning to draw conclusions about the relative utility of various sensor configurations, including spectral channels, viewing angles, and polarimetry. These findings have implications for Earth-observing missions such as NASA’s Plankton, Aerosol, Cloud-ocean Ecosystem (PACE) and Atmosphere Observing System (AOS) missions, as well as in informing future applications of computer vision to atmospheric remote sensing.