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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 1,297 records · Page 72

V/STOL hover stability impact on hover control task

Longitudinal static stability requirements for V/STOL aircraft are discussed in terms of vertical landing on a small ship at night, response of the aircraft to air turbulence, and hovering flight. The increased pilot workload encountered under these flight conditions is considered. Results of a flight simulation study performed to evaluate a specific hover control task, two control systems - attitude rate command and translational velocity command, and the pilots' performance with and without turbulence are reported. It is concluded that the translational velocity command system provides the control requirements for good spot hovering capability and reduced pilot workload.

Whitaker, A. B.↗

Report on the subpanel on remapping procedures

Problems associated with remapping procedures are defined and research tasks are proposed. It is noted that the remapping/rectification process could be significantly aided through engineering systems improvements in attitude control, with subsequent improvement in spacecraft ephemeris modeling accuracy. There is a need for state-of-the-art technology assessments prior to initiation of major programs, and the high potential return from well formulated testing of algorithms on selected data sets of actual and synthetic imagery. In addition, there is a need for tasks that incorporate standard photogrammetric methodology and formulas and that more fully utilize platform and calibration data from current and proposed sensors to reproject digital imagery. The impact of improved platform stability and integration of global positioning system measurements on reduced ground segment processing needs to be critically assessed. Also highlighted is the need for a substantial effort in the development of remapping software and systems that are modular and transportable.

Source record↗

Manned Mars mission communication and data management systems

A manned Mars mission will involve a small crew and many complex tasks. The productivity of the crew and the entire mission will depend significantly on effective automation of these tasks and the ease with which the crew can interface with them. The technology to support a manned Mars mission is available today; however, evolving software and electronic technology are enabling many interesting possibilities for increasing productivity and safety while reducing life cycle cost. Some of these advanced technologies are identified.

White, Ronald E.↗

Controls structures interaction, an interdisciplinary challenge for large spacecraft

Controls structures interaction (CSI), a phenomenon which occurs when control forces interact with the flexible motion of a structure, can, if improperly treated in design and development, cause reduced performance or control instabilities. Properly applied, it can improve flexible spacecraft performance. In this paper, the NASA CSI technology program for future spacecraft applications is described. The program objectives and organization are outlined, and the nature of individual program tasks is described. The interdisciplinary aspects of CSI are also addressed.

Hanks, Brantley R.↗

A polar orbit for the Mars Global Network Mission

The purpose of the Global Network Mission (GNM) is to deploy simple landers on the Martian surface in late 1998. The objective is to create a globally distributed network of ground stations which will collect environmental data, perhaps for as long as several years. The GNM presents unique mission design challenges, which are addressed by the following essay. The GNM mission concept calls for two carrier spacecraft, each equipped with a number of simple landers. Some of the landers may be deployed from approach, either to reduce carrier mass prior to orbit insertion, or to reach latitudes not available from the carrier orbit. The remaining landers are deployed from orbit. One configuration for the Global Network Mission was proposed in a report from the Exploration Precursors Task Team to the Office of Space Science and Applications. This formed the basis of a previous orbit design for the GNM. This mission scenario is used as a point of reference, but results from the current study are generally applicable to a wide range of GNM mission variants. The analysis concluded that a 1/5 sol, polar orbit with a periapse altitude of 275 km offers the best circumstances for orbital deployment of the Global Network Mission landers. It allows easy polar access at nominal entry angles, and global dispersal of landing sites at lighting angles suitable for descent imaging. The polar orbit allows the option of deploying all the landers from orbit. A wait interval of 160 days after arrival is required before deployment can commence.

Knocke, Philip↗

Procedures for minimizing the effects of high solar activity on satellite tracking and ephemeris generation

We are currently experiencing a period of high solar radiation combined with wide short-term fluctuations in the radiation. The short-term fluctuations, especially when combined with highly energetic solar flares, can adversely affect the mission of U.S. Space Command's Space Surveillance Center (SSC) which catalogs and tracks the satellites in orbit around the Earth. Rapidly increasing levels of solar electromagnetic and/or particle radiation (solar wind) causes atmospheric warming, which, in turn, causes the upper-most portions of the atmosphere to expand outward, into the regime of low altitude satellites. The increased drag on satellites from this expansion can cause large, unmodeled, in-track displacements, thus undermining the SSC's ability to track and predict satellite position. On 13 March 1989, high solar radiation levels, combined with a high-energy solar flare, caused an exceptional amount of short-term atmospheric warming. The SSC temporarily lost track of over 1300 low altitude satellites--nearly half of the low altitude satellite population. Observational data on satellites that became lost during the days following the 13 March 'solar event' was analyzed and compared with the satellites' last element set prior to the event (referred to as a geomagnetic storm because of the large increase in magnetic flux in the upper atmosphere). The analysis led to a set of procedures for reducing the impact of future geomagnetic storms. These procedures adjust selected software limit parameters in the differential correction of element sets and in the observation association process and must be manually initiated at the onset of a geomagnetic storm. Sensor tasking procedures must be adjusted to ensure that a minimum of four observations per day are received for low altitude satellites. These procedures have been implemented and, thus far, appear to be successful in minimizing the effect of subsequent geomagnetic storms on satellite tracking and ephemeris computation.

Bredvik, Gordon D.↗

ACTS broadband aeronautical experiment

In the last decade, the demand for reliable data, voice, and video satellite communication links between aircraft and ground to improve air traffic control, airline management, and to meet the growing demand for passenger communications has increased significantly. It is expected that in the near future, the spectrum required for aeronautical communication services will grow significantly beyond that currently available at L-band. In anticipation of this, JPL is developing an experimental broadband aeronautical satellite communications system that will utilize NASA's Advanced Communications Technology Satellite (ACTS) as a satellite of opportunity and the technology developed under JPL's ACTS Mobile Terminal (AMT) Task to evaluate the feasibility of using K/Ka-band for these applications. The application of K/Ka-band for aeronautical satellite communications at cruise altitudes is particularly promising for several reasons: (1) the minimal amount of signal attenuation due to rain; (2) the reduced drag due to the smaller K/Ka-band antennas (as compared to the current L-band systems); and (3) the large amount of available bandwidth. The increased bandwidth available at these frequencies is expected to lead to significantly improved passenger communications - including full-duplex compressed video and multiple channel voice. A description of the proposed broadband experimental system will be presented including: (1) applications of K/Ka-band aeronautical satellite technology to U.S. industry; (2) the experiment objectives; (3) the experiment set-up; (4) experimental equipment description; and (5) industrial participation in the experiment and the benefits.

Abbe, Brian S.↗

Noise exposure reduction of advanced high-lift systems

The purpose of NASA Contract NAS1-20090 Task 3 was to investigate the potential for noise reduction that would result from improving the high-lift performance of conventional subsonic transports. The study showed that an increase in lift-to-drag ratio of 15 percent would reduce certification noise levels by about 2 EPNdB on approach, 1.5 EPNdB on cutback, and zero EPNdB on sideline. In most cases, noise contour areas would be reduced by 10 to 20 percent.

Haffner, Stephen W.↗

Linear static structural and vibration analysis on high-performance computers

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Baddourah, M. A.↗

A New Method for Estimating the Single Scattering Phase Functions of Regolith Grains

Hapke's photometric model has been widely used in solar system remote sensing applications for nearly two decades. Recently, Hapke extended his model to describe the coherent-backscatter opposition effect and multiple-scattering by particles with anisotropic single particle phase functions (SPPF's). A practical difficulty for retrieving Hapke's model parameters from typical planet, satellite, and asteroid photometry data sets is that the model employs a large number of adjustable parameters (at least eight) that can be reliably constrained only for a small number of planetary data sets in which both disk-resolved and whole-disk observations are available from opposition to very large phase angles. The present work aims to reduce the number of adjustable parameters and preserve (or even enhance) the model's accuracy and usefulness by expressing Hapke's parameters in terms of more fundamental physical properties on which they mutually depend. The most difficult part of this task, described here, is to develop a simple method for computing the effective SPPF for structurally complex regolith grains from optical constants, grain-size distribution, and average regolith porosity. The development of light-scattering models for irregularly shaped particles is a large, complex subject and many sophisticated methods, such as Discrete Dipole Approximation (DDA) and Monte-Carlo simulations, have been explored elsewhere. Many of these methods are computationally intensive and probably impractical for routine substitution in Hapke's model. Here, progress is reported in developing a practical, semi-empirical method for estimating the directional scattering behavior (i.e. SPPF) of irregular regolith grains. The method employs Optical Transfer Function (OTF) techniques to model how the structural complexity of regolith particles broaden and attenuate the angular distribution of scattered light relative to that expected from ideal spherical particles of equivalent size and composition.

Helfenstein, P.↗

Linear Static Structural and Vibration Analysis on High-Performance Computers

Parallel computers offer the opportunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on a massively-parallel computers hereafter referred to as Scalable High Performance Computers (SHPC) for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. Models of high speed civil transport). The goal of this research is to develop new efficient technique which extend structural analysis to SHPC and make large-scale structural analyses tractable.

Baddourah, Majdi↗

Interoperability Trends in Extravehicular Activity (EVA) Space Operations for the 21st Century

No other space operations in the 21 st century more comprehensively embody the challenges and dependencies of interoperability than EVA. This discipline is already functioning at an W1paralleled level of interagency, inter-organizational and international cooperation. This trend will only increase as space programs endeavor to expand in the face of shrinking budgets. Among the topics examined in this paper are hardware-oriented issues. Differences in design standards among various space participants dictate differences in the EVA tools that must be manufactured, flown and maintained on-orbit. Presently only two types of functional space suits exist in the world. However, three versions of functional airlocks are in operation. Of the three airlocks, only the International Space Station (ISS) Joint Airlock can accommodate both types of suits. Due to functional differences in the suits, completely different operating protocols are required for each. Should additional space suit or airlock designs become available, the complexity will increase. The lessons learned as a result of designing and operating within such a system are explored. This paper also examines the non-hardware challenges presented by interoperability for a discipline that is as uniquely dependent upon the individual as EVA. Operation of space suits (essentially single-person spacecrafts) by persons whose native language is not that of the suits' designers is explored. The intricacies of shared mission planning, shared control and shared execution of joint EVA's are explained. For example, once ISS is fully functional, the potential exists for two crewmembers of different nationality to be wearing suits manufactured and controlled by a third nation, while operating within an airlock manufactured and controlled by a fourth nation, in an effort to perform tasks upon hardware belonging to a fifth nation. Everything from training issues, to procedures development and writing, to real-time operations is addressed. Finally, this paper looks to the management challenges presented by interoperability in general. With budgets being reduced among all space-faring nations, the need to expand cooperation in the highly expensive field of human space operations is only going to intensify. The question facing management is not if the trend toward interoperation will continue, but how to best facilitate its doing so. Real-world EVA interoperability experience throughout the ShuttlelMir and ISS Programs is discussed to illustrate the challenges and

Miller, Gerald E.↗

Predictive based monitoring of nuclear plant component degradation using support vector regression

Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component’s respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗

SC-228 Inclusion of DAA Warning Alert for TCAS Interoperability

This white paper summarizes NASA research results that have informed Special Committee 228 (SC-228) discussions and decisions regarding the inclusion of a warning-level alert within the detect and avoid (DAA) alerting structure for unmanned aircraft systems (UAS). For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgments about a potential threat of a loss of well clear with another aircraft. As a result, the DAA traffic display will be the primary source of information that the PIC can use to execute the three primary well clear functions: 1) detect a potential loss of well clear, 2) determine a resolution maneuver, and 3) upload that maneuver to the aircraft via the ground control station (GCS). In addition, pilots are required to coordinate with air traffic control (ATC) prior to maneuvering off of their approved flight plan. In determining an appropriate resolution maneuver to avoid a loss of well clear, the PIC must decide both when and how to maneuver, and both the timeliness and the accuracy (i.e., correctness) of the maneuver are critical to reducing the likelihood and/or severity of a loss of well clear. Alerting information is one of three critical components of the DAA display, along with traffic information elements (e.g., relative heading, speed and altitude) and maneuver guidance. Alerting information and maneuver guidance, in particular, have been found to have a significant impact, both statistically and practically, on pilots' ability to avoid and minimize the severity of losses of well clear While all three display components are key to pilots performing the traffic avoidance task of remaining well clear, in general, alerting information provides crucial information about when a resolution maneuver is required while maneuver guidance assists the pilot in determining how best to maneuver. A fundamental task of the DAA alerting system is to provide critical timing information to the pilot about the potential for a loss of well clear with another aircraft. This is done by employing both temporal and spatial thresholds that indicate to the pilot the likelihood and imminence of a loss of well clear. The design of the DAA alerting thresholds is a balancing act between eliciting the desired pilot response in real loss of well clear threat events and reducing excessive, unnecessary, and/or uncoordinated UAS maneuvering within the air traffic environment; larger thresholds, both spatially and temporally, may increase the likelihood of a pilot avoiding a loss of well clear, but it can also increase the frequency of maneuvering - especially in cases where a maneuver is not actually needed to maintain well clear. A series of human in the loop (HITL) simulations have been conducted as part of NASA's Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) project. The purpose of these HITLs has been to provide empirical results in order to inform development of the minimum human-machine interface requirements for the DAA system. This white paper will present those results which provide evidence of a human performance benefit (in terms of response times and ability to remain well clear of other aircraft) of the DAA warning alert both with and without a collision avoidance system on board the aircraft.

TCAS interoperability↗

Low Emissions Alternative Power (LEAP) Project Office Business Team of the Aeropropulsion Research Program Office (ARPO) Org. 0140

The program for which I am working at this summer is Propulsion and Power/Low Emissions Alternative Power (P&P/LEAP). It invests in a fundamental TRL 1-6 research and technology portfolio that will enable the future of: Alternative fuels and/or alternative propulsion systems, non-combustion (electric) propulsion systems. P&P/LEAP will identify and capitalize on the highest potential concepts generated both internal and external to the Agency. During my 2004 summer at NASA Glenn Research Center, I worked with my mentor Barbara Mader, in the Project Office with the Business Team completing various tasks for the project and personnel. The LEAP project is a highly matrixed organization. The Project Office is responsible for the goals advocacy and dollar (budget) of the LEAP project. The objectives of the LEAP Project are to discover new energy sources and develop unconventional engines and power systems directed towards greatly reduced emissions, enable new vehicle concepts for public mobility, new science missions and national security. The Propulsion and PowerLow Emissions Alternative Power directly supports the environmental, mobility, national security objectives of the Vehicle Systems Program and the Aeronautics Technology Theme. Technology deliverables include the demonstration through integrated ground tests, a constant volume combustor in an engine system, and UAV/small transport aircraft all electric power system. My mentor serves as a key member of the management team for the Aeropropulsion Research Program Office (ARPO). She has represented the office on numerous occasions, and is a member of a number of center-wide panels/teams, such as the Space management Committee and is chair to the Business Process Consolidation Team. She is responsible for the overall coordination of resources for the Propulsion and Power Project - from advocacy to implementation. The goal for my summer at NASA was to document processes and archive program documents from the past years. I used the computer and office machines, and also worked with personnel in setting up a Cost Estimation Plan. I gained office experience in Word, Excel, and Power Point, with the completion of a variety of tasks. I made spreadsheets that pertained to the budget plan for Journey to Tomorrow, to name a few I have supported the office by tracking resource information: including programmatic travel, project budget at the center level to budgets for individual research sub-projects and grants. I also assisted the Program Support Office in their duties including, representing the office on numerous occasions on center-wide team/panels, such as the Space management committee, IFMP Budget Formulation, Journey to Tomorrow Committee, and the Vehicle Systems Program Business Process Team.

Buttler, Jennifer A.↗

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗

Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data

Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making it possible to provide a high level of detail for incoming and recent data while providing contextual information about recent history. Visual aggregation reduces data resolution in order to show the context of data over large periods of time within a limited display space. With a controlled experiment, we evaluated the effectiveness of different types of aggregation for four types of stream-analysis tasks. Overall, the results show that a focus-plus-context design has little negative impact on the ability to successfully monitor and analyze streaming data, making it possible to show longer periods of time than other approaches. However, visual aggregation can be problematic for trend recognition tasks. This research demonstrates how the effectiveness of the visualization depends on the specifics of the analysis task.

Ragan, Eric↗