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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 181 records · Page 10
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NASA NTRS2009

Test Rack Development for Extended Operation of Advanced Stirling Convertors at NASA Glenn Research Center

The U.S. Department of Energy (DOE), Lockheed Martin Space Company (LMSC), Sun power Inc., and NASA Glenn Research Center (GRC) have been developing an Advanced Stirling Radioisotope Generator (ASRG) for use as a power system on space science missions. This generator will make use of free-piston Stirling convertors to achieve higher conversion efficiency than currently available alternatives. NASA GRC's support of ASRG development includes extended operation testing of Advanced Stirling Convertors (ASCs) developed by Sunpower Inc. In the past year, NASA GRC has been building a test facility to support extended operation of a pair of engineering level ASCs. Operation of the convertors in the test facility provides convertor performance data over an extended period of time. Mechanical support hardware, data acquisition software, and an instrumentation rack were developed to prepare the pair of convertors for continuous extended operation. Short-term tests were performed to gather baseline performance data before extended operation was initiated. These tests included workmanship vibration, insulation thermal loss characterization, low-temperature checkout, and fUll-power operation. Hardware and software features are implemented to ensure reliability of support systems. This paper discusses the mechanical support hardware, instrumentation rack, data acquisition software, short-term tests, and safety features designed to support continuous unattended operation of a pair of ASCs.

Dugala, Gina M.↗
NASA NTRS2016

Architectural, Mechanical, Electrical, Plumbing, and Site Documents Associated with Sustainability Base, N232

These files contain more precise and accurate representations of the architectural, mechanical, electrical, plumbing, and site information pertaining to Sustainability Base, aka Collaborative Support Facility, aka N232. These supersede the 'bid' drawings released in STI 8112 previously. They are useful for NASA researchers and collaborators in modeling the performance characteristics of the facility. Otherwise, they do not contain new data.

Buildings↗
NASA NTRS2011

Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.

composites↗
NASA NTRS2016

Planetary Exploration Reinvented

During the past 50 years, we have learned to explore and work in space. Much of what we know about the Solar System we owe to observations and sampling made by robotic spacecraft, landers, planetary rovers, and astronauts. As we look to the future, however, there is ample opportunity to reinvent planetary exploration: to develop new techniques and systems that will enhance and enable discovery.In this talk, I will describe how the NASA Ames Intelligent Robotics Group (IRG) is working to reinvent planetary exploration. First, I will present IRG's development of robots for human exploration. These robots are designed to perform work before, in parallel, and after human activity. Next, I will show how IRG is building automated planetary mapping systems to process the enormous amount of data that NASA collects from orbit. Finally, I will discuss how IRG is changing the way ground control software is created, particularly for supporting science operations.

robotics↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS2016

NASA Phase2 Unlimited Rights Final Report Research and Technology for Aerospace Propulsion Systems (RTAPS) Task Order: ERA Advanced Core Compressor Technology Program

As part of the NASA Integrated Systems Research Program (ISRP), Environmentally Responsible Aviation (ERA) Project, NASA GRC and GE Aviation have partnered to investigate the technology barriers associated with improved fuel economy of large gas turbine engines. Crucial to improving fuel economy is the increase in pressure ratio (PR) of the core high pressure compressor (HPC). A key enabler to increasing HPC pressure ratios are new technology front stage airfoil designs that have higher efficiency, higher pressure ratios and improvements in front stage part-power operability. The purpose of this work is to design and test two high pressure ratio, high efficiency front block designs. The baseline design, hereafter referred to as Build 1, is similar to what would be found in a high efficiency 30:1 PR class HPC. A redesigned front block with improved blading will also be tested and hereafter be referred to as Build 2. The goal of Build 2 is to increase stage aero loading (increase stage pressure ratio) beyond Build 1 while maintaining equivalent efficiency and stall margin. The detailed inter-stage and traverse data from the two builds will be used to improve understanding of the complex flow physics at high-speed and part-speed conditions that impact performance and operability. By addressing, understanding and solving the challenges associated with aerodynamic losses and stage matching better design strategies can be incorporated in future core compressors with higher efficiency, thereby enabling improvement in mission fuel burn while still meeting operability requirements.

Axial Compressors↗
NASA NTRSDate not supplied

The Project “Analogs for VENus’s GEologically Recent Surfaces” (AVENGERS): Unveiling Active Volcanism on Venus

The recently selected missions to Venus opened a new era for the exploration of the Earth’s hellish twin sister. One of the key questions that the selected missions to Venus will address is whether the planet is volcanically active. The identification of ongoing volcanic activity on Venus can indeed unveil important clues on the geologic evolution of the planet, also helping us to better understand how volcanic and atmospheric processes work on Earth, especially those related to the climate change produced by greenhouse gases. To fully contextualize the higher resolution datasets to be provided by the future missions to Venus, we need to be able to exploit the wealth of data to be produced in the best possible way. Different types of instruments will indeed perform unprecedent orbiting and in-situ investigations of the surface and subsurface of Venus. To this regard, the Project “Analogs for VENus’s GEologically Recent Surfaces” (AVENGERS) aims to build a comprehensive database of Terrestrial active volcanoes which may act as suitable analogs for identifying ongoing volcanic activity on Venus. To do this, the project AVENGERS will combine the implementation of terrestrial orbiter radar data analysis techniques (i.e., radar interferometry) with infrared and laboratory analyses of lava flow samples from Terrestrial active volcanoes. As a first suitable analog of the Project AVENGERS, we selected Mount Etna in Sicily for a direct comparison with potentially active volcanic structures of Venus, and with Idunn Mons, one of the most promising possibly active volcanoes of Venus. Given its composite nature, Mount Etna offers the opportunity to identify and study multiple types of eruptive products (both effusive and explosive) from the analysis of high-resolution radar images. The frequent eruptions characterizing this volcano will also allow to test techniques of radar interferometry. Moreover, its ease of access facilitates geologic field trips and in-situ investigations with related sample retrieving. Ongoing infrared laboratory analysis on several altered and unaltered samples retrieved by Mount Etna will help to distinguish spectral signatures of fresh vs weathered volcanic deposits.

P. D’Incecco↗
NASA NTRS2013

Estimated Probability of a Cervical Spine Injury During an ISS Mission

Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a Monte Carlo wrapper (MATLAB) used to integrate the components of the module. Results: The probability of generating an AIS1 soft tissue neck injury from the extension/flexion motion induced by a low-velocity blunt impact to the superior posterior thorax was fitted with a lognormal PDF with mean 0.26409, standard deviation 0.11353, standard error of mean 0.00114, and 95% confidence interval [0.26186, 0.26631]. Combining the probability of an AIS1 injury with the probability of IES occurrence was fitted with a Johnson SI PDF with mean 0.02772, standard deviation 0.02012, standard error of mean 0.00020, and 95% confidence interval [0.02733, 0.02812]. The input factor sensitivity analysis in descending order was IES incidence rate, ITF regression coefficient 1, impactor initial velocity, ITF regression coefficient 2, and all others (equipment mass, crew 1 body mass, crew 2 body mass) insignificant. Verification and Validation (V&V): The IMM V&V, based upon NASA STD 7009, was implemented which included an assessment of the data sets used to build CSIM. The documentation maintained includes source code comments and a technical report. The software code and documentation is under Subversion configuration management. Kinematic validation was performed by comparing the biomechanical model output to established corridors.

Brooker, John E.↗
NASA NTRS2016

Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and Wind

Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.

uncertainty↗
NASA NTRS2012

Checkout and Standard Use Procedures for the Mark III Space Suit Assembly

The operational pressure range is the range to which the suit can be nominally operated for manned testing. The top end of the nominal operational pressure range is equivalent to 1/2 the proof pressure. Structural pressure is 1.5 times the specified test pressure for any given test. Proof pressure is the maximum unmanned pressure to which the suit was tested by the vendor prior to delivery. The maximum allowable working pressure (MAWP) is 90% of the proof pressure. The pressure systems RVs are set to keep components below their MAWPs. If the suit is pressurized over its MAWP, the suit will be taken out of service and an in-depth inspection/review of the suit will be performed before the suit is put back in service. The procedures outlined in this document should be followed as written. However, the suit test engineer (STE) may make redline changes real-time, provided those changes are recorded in the anomaly section of the test data sheet. If technicians supporting suit build-up, check-out, and/or test execution believe that a procedure can be improved, they should notify their lead. If procedures are incorrect to the point of potentially causing hardware damage or affecting safety, bring the problem to the technician lead and/or STE s attention and stop work until a solution (temporary or permanent) is authorized. Certain steps in the procedure are marked with a DV , for Designated Verifier. The Designated Verifier for this procedure is an Advanced Space Suit Technology Development Laboratory technician, not directly involved in performing the procedural steps, who will verify that the step was performed as stated. The steps to be verified by the DV were selected based on one or more of the following criteria: the step was deemed significant in ensuring the safe performance of the test, the data recorded in the step is of specific interest in monitoring the suit system operation, or the step has a strong influence on the successful completion of test objectives. Prior to all manned test activities, Advanced Suit Test Data Sheet (TDS) Parts A-E shall be completed to verify system and team are ready for test. Advanced Suit TDS Parts F-G shall be completed at the end of the suited activity. Appendix B identifies tha appropriate Mark III suit emergency event procedures.

Valish, Dana J.↗
NASA NTRSDate not supplied

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS1972

Earth resources data analysis system

The Earth Resources Laboratory Data Analysis System provides a valuable research tool in the evaluation of multispectral, radiometric, photographic, and passive microwave imagery data. The system has been in operational use for several months and has performed quite well. Emphasis on versatility of both the hardware and software design facilitates system expansion to many specialized data analysis tasks. The many independent software handlers provide building blocks for major processing programs.

Source record↗
NASA NTRS1985

WEST-3 wind turbine simulator development. Volume 1: Summary

This report is a summary description of WEST-3, a new real-time wind turbine simulator developed by Paragon Pacific Inc. WEST-3 is an all digital, fully programmable, high performance parallel processing computer. Contained in the report are descriptions of the WEST-3 hardware and software. WEST-3 consists of a network of Computational Units (CUs) working in parallel. Each CU is a custom designed high speed digital processor operating independently of other CUs. The CU, which is the main building block of the system, is described in some detail. A major contributor to the high performance of the system is the use a unique method for transferring data among the CUs. The software aspects of WEST-3 covered in the report include the preparation of the simulation model (reformulation, scaling and normalization), and the use of the system software (Translator, Linker, Assembler and Loader). Also given is a description of the wind turbine simulation model used in WEST-3, and some sample results from a study conducted to validate the system. Finally, efforts currently underway to enhance the user friendliness of the system are outlined; these include the 32-bit floating point capability, and major improvements in system software.

Sridhar, S.↗
NASA NTRS1998

Rocketdyne Advanced Reusable Technologies Program Update

NASA Marshall Space Flight Center Advanced Reusable Technologies/Rocket Based Combined Cycle (RBCC) program has enabled: (1) the creation of unique trajectory simulation facility; (2) development of basic operability and performance data; (3) results to date: (a) rocket thrusters performing as designed (P(sub c), MR, q, etc); (b) AAR performance data measured at M = 0 and 3; (c) rocket mode performance at simulated vacuum conditions; and (d) data reduction in progress; (4) completing testing; M = 0, 3 and trajectory M = 3 to 3.7; and (5) next logical steps: build flight type engine and flight demonstrate RBCC.

Ratekin, Gary↗
NASA NTRS2018

NASA ACC High Energy Dynamic Impact Methodology and Outcomes

High fidelity analysis methods known as Progressive Damage Analysis (PDA) methods, capable of reliably predicting the onset and progression of damage in composite materials, are being developed for HEDI event simulation. Four state-of-the-art PDA methods are being investigated: LS-DYNA MAT162, LS-DYNA MAT261, Smooth-Particle Galerkin (SPG), and EMU Peridynamics. Validation of these PDA models aims to follow a building block approach, starting with coupon- and component-level development. As part of the overall effort, material characterization testing was performed to bridge gaps between existing experimental data and the material property inputs required to predict ballistic impact behavior at the component-level. The material models were updated with the results of the coupon-level testing and were then used to predict panel behavior and damage in ballistic impact events. To assess the accuracy of the PDA methods, these pre-test predictions were compared to the results of ballistic impact testing.

Hunziker, Kenneth J.↗
NASA NTRSDate not supplied

Preliminary Findings of the Experimental Development Unit Cold Flow Test for a Generation Zero Nuclear Propulsion Engine

Nuclear thermal propulsion (NTP) technology will greatly benefit human travel to Mars by significantly shortening transit times, improving crew safety, and providing more mission flexibility than traditional chemical rockets. As part of DRACO follow-on work to develop, build, and fly a generation zero NTP engine, a full scale flight-like experimental design unit (EDU) reactor was constructed to collect sufficient on-ground performance data to characterize flow induced vibrations (FIV) of critical reactor structures/components, inform development of the engine and reactor control algorithm, and collect pressure drop and flow distribution data across the reactor. The fluid conditions for the test program were designed to achieve system responses equivalent to that of an operational engine through all phases of engine operation including reactor startup, mainstage operation, reactor shutdown, and reactor cooldown. Over 100 tests were executed, flowing either GN2 or GHe through the EDU at varying flow rates and pressures. This experiment provided early validation of flow behavior and vibration risks before nuclear testing, boosted critical subsystem TRLs, informed design iterations, and reduced future test costs. The steady-state flow parameters for the experiment were modeled in Ansys Thermal Desktop, allowing rapid tuning and experiment-informed updates to a flight-like test matrix. The EDU dynamic environment was characterized with accelerometers, strain gauges, and high-frequency pressure transducers all sampled at 20 kHz. While many narrow-band oscillations were identified, no significant FIV occurred; the reactor structural responses tend to be enveloped by typical launch vehicle ascent vibration environments (defined up to 2 kHz), although significant energy is also present at higher frequencies.

Flow Induced Vibration↗