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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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This paper is a summary of the JAMMS project, which has resulted in a scientific data set of very high value -- a multi-season snapshot of one of the most difficult areas on Earth to monitor.
This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.
The Operations Engineering Laboratory (OEL) at JPL is developing new technologies that can provide more efficient and productive ways of doing business in flight operations. Over the past three years, we have worked closely with the Multi-Mission Control Team to develop automation tools, providing technology transfer into operations and resulting in substantial cost savings and error reduction. The OEL development philosophy is characterized by object-oriented design, extensive reusability of code, and an iterative development model with active participation of the end users. Through our work, the benefits of object-oriented design became apparent for use in mission control data systems. Object-oriented technologies and how they can be used in a mission control center to improve efficiency and productivity are explained. The current research and development efforts in the JPL Operations Engineering Laboratory are also discussed to architect and prototype a new paradigm for mission control operations based on object-oriented concepts.
This paper presents a predictive controller for a grid-interactive multi-zone building where the temperature dynamics are learned via Gaussian Process (GP) regression. We investigate the development of a learning-based predictive control with two main objectives: (i) continuously learn the temperature dynamics of the building based on data; and, (ii) use the learned dynamics to solve a multi-objective predictive control problem to guarantee occupants' comfort and energy efficiency during normal conditions and demand response events. We leverage the probabilistic non-parametric properties of GPs to estimate the (unknown) non-linear temperature dynamics of the building and to incorporate the uncertainty of those predictions in a multi-objective optimization problem. The GP-based predictive control is solved via a zero-order primal-dual projected-gradient algorithm. We evaluate numerically the performance of the proposed controller using a five-zone commercial building.
A primary science goal of the 6.5 m James Webb Space Telescope is to characterize the epoch of initial galaxy formation, observing the early universe as the first stars and galaxies formed. This program will be accomplished using a combination of multi-band imaging and spectroscopic measurements of large numbers of faint galaxies. Since these objects are in general sparse on the sky, a multi object spectrometer is required to enable this critical scientific investigation. We have developed a microshutter array which is to be used as a high contrast, remotely programmable field selector for the Near Infrared Spectrometer (NIRSpec) on JWST. This device allows slits to be opened at the locations of selected galaxies in the field of view, and blocks sources and background light from the rest of the field. The first flight design devices have been built and were tested. These first generation of devices were used to demonstrate performance and flight readiness. Devices of the same design will be delivered to ESA for installation into the NIRSpec instrument.
This paper describes an analytical approach and descriptive methodology that is adapted from Object-Oriented Analysis (OOA) techniques. The technique is described and then used to communicate key issues of system logical architecture. The essence of the approach is to limit the analysis to only service objects, with the idea of providing a direct mapping from the design to a client-server implementation. Key perspectives on the system, such as user interaction, data flow and management, service interfaces, hardware configuration, and system and data integrity are covered. A significant advantage of this service-oriented approach is that it permits mapping all of these different perspectives on the system onto a single common substrate. This services substrate is readily represented diagramatically, thus making details of the overall design much more accessible.
This paper describes an analytical approach and descriptive methodology that is adapted from Object-Oriented Analysis techniques.
The objective of this work was to investigate the use of a co-Kriging based multi-fidelity modeling approach with a Monte Carlo uncertainty quantification analyses of surface heating on hypersonic inflatable aerodynamic decelerator vehicles and adaptable, deployable entry placement technology vehicles in Mars entry. A previously developed co-Kriging based multi-fidelity modeling approach was used to model the laminar and turbulent convective and radiative heat fluxes along the vehicle. Monte Carlo analyses of surface heat load for nine different vehicle nose radii was performed for both vehicles, assuming the same thermal protection system is used for both vehicles. The maximum heat loads and heat load uncertainties were found to occur at either the stagnation point or the vehicle shoulder. The maximum 95% confidence intervals for the total heat load for the hypersonic inflatable aerodynamic decelerator vehicle were found to be [-9.27, 7.81] % of the nominal value and [-6.09, 13.1] % of the nominal value for laminar and turbulent flow, respectively. The maximum 95% confidence intervals for the total heat load for the adaptable, deployable entry placement technology vehicle were found to be [-8.85, 7.22] % of the nominal value and [-9.33, 9.35] % of the nominal value for laminar and turbulent flow, respectively. The difference in heating uncertainties based on vehicle geometry between the two vehicle technologies was found to be minimal.
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Mesh generation has long been recognized as a bottleneck in the CFD process. While much research on automating the volume mesh generation process have been relatively successful,these methods rely on appropriate initial surface triangulation to work properly. Surface discretization has been one of the least automated steps in computational simulation due to its dependence on implicitly defined CAD surfaces and curves. Differences in CAD peometry engines manifest themselves in discrepancies in their interpretation of the same entities. This lack of "good" geometry causes significant problems for mesh generators, requiring users to "repair" the CAD geometry before mesh generation. The problem is exacerbated when CAD geometry is translated to other forms (e.g., IGES )which do not include important topological and construction information in addition to entity geometry. One technique to avoid these problems is to access the CAD geometry directly from the mesh generating software, rather than through files. By accessing the geometry model (not a discretized version) in its native environment, t h s a proach avoids translation to a format which can deplete the model of topological information. Our approach to enable models developed in the Denali software environment to directly access CAD geometry and functions is through an Application Programming Interface (API) known as CAPRI. CAPRI provides a layer of indirection through which CAD-specific data may be accessed by an application program using CAD-system neutral C and FORTRAN language function calls. CAPRI supports a general set of CAD operations such as truth testing, geometry construction and entity queries.
This was a quick &week effort to investigate the ability to detect changes along the flight path of an unmanned airborne vehicle (UAV) over time. Video was acquired by the UAV during several passes over the same terrain. Concurrently, GPS data and UAV attitude data were also acquired. The purpose of the research was to use information from all of these sources to detect if any change had occurred in the terrain encompassed by the flight path.
An essential application in intelligent transportation systems is multi-target multi-camera tracking (MTMCT), where the target’s activity is tracked from different cameras. Although the tracking-by-detection scheme is the primary paradigm in MTMCT, the object association information from the video frames is lost. This is mainly because the multi-camera multi-object matching uses the information from the video frames separately. To solve this problem and leverage this association information, we propose an MTMCT framework, where features are built in the form of a graph and a graph similarity algorithm is used to match multi-camera objects. In this paper, we focus on the real-time scenario, where only the past images are used to match an object. Our method achieves an IDF1 score (the ratio of the number of correctly identified objects to the number of ground truth and average objects) of 0.75 with a rate of 14 frames per second (fps).
The objective of the Multi-Path Redundant Avionics Suite (MPRAS) program is the development of a set of avionic architectural modules which will be applicable to the family of launch vehicles required to support the Advanced Launch System (ALS). To enable ALS cost/performance requirements to be met, the MPRAS must support autonomy, maintenance, and testability capabilities which exceed those present in conventional launch vehicles. The multi-path redundant or fault tolerance characteristics of the MPRAS are necessary to offset a reduction in avionics reliability due to the increased complexity needed to support these new cost reduction and performance capabilities and to meet avionics reliability requirements which will provide cost-effective reductions in overall ALS recurring costs. A complex, real-time distributed computing system is needed to meet the ALS avionics system requirements. General Dynamics, Boeing Aerospace, and C.S. Draper Laboratory have proposed system architectures as candidates for the ALS MPRAS. The purpose of this document is to report the results of independent performance and reliability characterization and assessment analyses of each proposed candidate architecture and qualitative assessments of testability, maintainability, and fault tolerance mechanisms. These independent analyses were conducted as part of the MPRAS Part 2 program and were carried under NASA Langley Research Contract NAS1-17964, Task Assignment 28.
In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.
The objective of this closely coordinated research project is to develop improved physical sub-models and innovative numerical algorithms to enable accurate and efficient predictions of multi-mode combustion to support EERE’s Co-Optima program. To this end, a research pro-gram is proposed that seeks • to develop accurate submodels for predicting multi-mode combustion regimes, wall-heat transfer, non-equilibrium plasma ignition, and combustion-mode transition, • to develop dynamic load-rebalancing algorithms and efficient semi-implicit time-integration schemes for enabling exascale computing, • to validate the computational submodels against experiments and direct numerical simulation (DNS) data in conjunction with sensitivity analysis, and • to support the direct transition of the resulting sub-models into other engine-simulation tools through the development of self-contained modules. All sub-models will be integrated into the open-source exascale engine-simulation platform Nek5000.
One of the James Webb Space Telescope's (JWST) primary science goals is to characterize the epoch of galaxy formation in the universe and observe the first galaxies and clusters of galaxies. This goal requires multi-band imaging and spectroscopic data in the near infrared portion of the spectrum for large numbers of very faint galaxies. Because such objects are sparse on the sky at the JWST resolution, a multi-object spectrograph is necessary to efficiently carry out the required observations. We have developed a fully programmable microshutter array that will be used as the field selector for the Near Infrared Spectrograph (NIRSpec) on JWST. This device allows slits to be opened at the locations of selected galaxies in the field of view while blocking other unwanted light from the sky background and bright sources. In practice, greater than 100 objects within the field of view will be observed simultaneously. In this paper, we describe the microshutter arrays, their development, fabrication, testing, and progress toward delivery of flight qualified devices to the NIRSpec instrument team in 2008.
One of the James Webb Space Telescope's (JWST) primary science goals is to characterize the epoch of galaxy formation in the universe and observe the first galaxies and clusters of galaxies. This goal requires multi-band imaging and spectroscopic data in the near infrared portion of the spectrum for large numbers of very faint galaxies. Because such objects are sparse on the sky at the JWST resolution, a multi-object spectrograph is necessary to efficiently carry out the required observations. We have developed a fully programmable microshutter array that will be used as the field selector for the Near Infrared Spectrograph (NIRSpec) on JWST. This device allows slits to be opened at the locations of selected galaxies in the field of view while blocking other unwanted light from the sky background and bright sources. In practice, greater than 100 objects within the field of view will be observed simultaneously. In this paper, we describe the microshutter arrays, their development, fabrication, testing, and progress toward delivery of flight qualified devices to the NIRSpec instrument team in 2008.
The NASA HyspIRI mission is planned to provide global solar reflected energy spectroscopic measurement of the terrestrial and shallow water regions of the Earth every 19 days will all measurements downlinked. In addition, HyspIRI will provide multi-spectral thermal measurements with a single band in the 4 micron region and seven bands in the 8 to 12 micron region with 5 day day/night coverage. A direct broadcast capability for measurement subsets is also planned. This HyspIRI mission is one of those designated in the 2007 National Research Council (NRC) Decadal Survey: Earth Science and Applications from Space. In the Decadal Survey, HyspIRI was recognized as relevant to a range of Earth science and science applications, including climate: "A hyperspectral sensor (e.g., FLORA) combined with a multispectral thermal sensor (e.g., SAVII) in low Earth orbit (LEO) is part of an integrated mission concept [described in Parts I and II] that is relevant to several panels, especially the climate variability panel." The HyspIRI science study group was formed in 2008 to evaluate and refine the mission concept. This group has developed a series of HyspIRI science objectives: (1) Climate: Ecosystem biochemistry, condition & feedback; spectral albedo; carbon/dust on snow/ice; biomass burning; evapotranspiration (2) Ecosystems: Global plant functional types, physiological condition, and biochemistry including agricultural lands (3) Fires: Fuel status, fire frequency, severity, emissions, and patterns of recovery globally (4) Coral reef and coastal habitats: Global composition and status (5) Volcanoes: Eruptions, emissions, regional and global impact (6) Geology and resources: Global distributions of surface mineral resources and improved understanding of geology and related hazards These objectives are achieved with the following measurement capabilities. The HyspIRI imaging spectrometer provides: full spectral coverage from 380 to 2500 at 10 nm sampling; 60 m spatial sampling with a 150 km swath; and fully downlinked coverage of the Earth's terrestrial and shallow water regions every 19 days to provide seasonal cloud-free coverage of the terrestrial surface. The HyspIRI Multi-Spectral Thermal instrument provides: 8 spectral bands from 4 to 12 microns; 60 m spatial sampling with a 600 km swath; and fully downlinked coverage of the Earth's terrestrial shallow water regions every 5 days (day/night) to provide nominally cloud-free monthly coverage. The HyspIRI mission also includes an on-board processing and direct broadcast capability, referred to as the Intelligent Payload Module (IPM), which will allow users with the appropriate antenna to download a subset of the HyspIRI data stream to a local ground station. These science and science application objectives are critical today and uniquely addressed by the combined imaging spectroscopy, thermal infrared measurements, and IPM direct broadcast capability of HyspIRI. Two key objectives are: (1) The global HyspIRI spectroscopic measurements of the terrestrial biosphere including vegetation composition and function to constrain and reduce the uncertainty in climate-carbon interactions and terrestrial biosphere feedback. (2) The global 8 band thermal measurements to provide improved constraint of fire related emissions. In this paper the current HyspIRI mission concept that has been reviewed and refined to its current level of maturity with a Data Products Symposium, Science Workshop and NASA HWorkshop is presented including traceability between the measurements and the science and science application objectives.