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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Graph Embedding Techniques for Bounding Condition Numbers of Incomplete Factor Preconditioning

We extend graph embedding techniques for bounding the spectral condition number of preconditioned systems involving symmetric, irreducibly diagonally dominant M-matrices to systems where the preconditioner is not diagonally dominant. In particular, this allows us to bound the spectral condition number when the preconditioner is based on an incomplete factorization. We provide a review of previous techniques, describe our extension, and give examples both of a bound for a model problem, and of ways in which our techniques give intuitive way of looking at incomplete factor preconditioners.

Guattery, Stephen↗
NASA NTRS2005

Software Would Largely Automate Design of Kalman Filter

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Chuang, Jason C. H.↗
NASA NTRS2015

RoboGlove: Initial Work Toward a Robotically Assisted EVA Glove

The RoboGlove is a device designed to provide additional grip strength or endurance for a user. In applying this Robonaut 2 spinoff technology to the Phase VI Space Suit glove, the project is using robotic tendons and actuators to regain some of the hand performance that is lost when wearing a pressurized glove. An array of sensors embedded into the finger softgoods provides input to the control system which retracts the tendons, helping to close the user's hand. While active, this system provides augmentation, but is nonintrusive to glove usage when disabled.

Rogers, Jonathan↗
NASA NTRS2018

Orion EM-2 TPS Radiometer & Spectrometer

Radiometers and Spectrometers embedded as flight instrumentation in a spacecraft's thermal protection system (TPS) can generate data on shock layer radiation to a spacecraft's surface for high-speed trajectories such as lunar return. Robust and accurate flight measurements of shock layer radiation can validate models and inform TPS selection and sizing, to reduce risk and TPS launch mass. Contamination from soot deposition and ablation products in the boundary layer condensing on a cold sapphire radiometer window or blocking open ports interferes with measurements. This poster describes characterization of the optical properties and performance of relevant materials, components, and contaminated windows, as well as investigation of contamination control strategies for the optics.

Ablation↗
NASA NTRSDate not supplied

Runtime Analysis with R2U2: A Tool Exhibition Report

We present R2U2 (Realizable, Responsive, Unobtrusive Unit), a hardware- supported tool and framework for the continuous monitoring of safetycritical and embedded cyber-physical systems.With the widespread advent of autonomous systems such as Unmanned Aerial Systems (UAS), satellites, rovers, and cars, real-time, on-board decision making requires unobtrusive monitoring of properties for safety, performance, security, and system health. R2U2 models combine past-time and future-time Metric Temporal Logic, “mission time” Linear Temporal Logic, probabilistic reasoning with Bayesian Networks, and modelbased prognostics. The R2U2 monitoring engine can be instantiated as a hardware solution, running on an FPGA, or as a software component. The FPGA realization enables R2U2 to monitor complex cyber-physical systems without any overhead or instrumentation of the flight software. In this tool exhibition report, we present R2U2 and demonstrate applications on system runtime monitoring, diagnostics, software health management, and security monitoring for a UAS. Our tool demonstration uses a hardware-based processor-in-the-loop “iron-bird” configuration.

Johann Martin Schumann↗
NASA NTRS2021

A Functional Interpolation Approach to Compute Period Orbits in the Circular Restricted Three-body Problem

In this paper, we develop a method to solve for periodic orbits, i.e., Lyapunov and Halo orbits, using a functional interpolation scheme called the Theory of Func- tional Connections (TFC). Using this technique, a periodic constraint is analyti- cally embedded into the TFC constrained expression. By doing this, the system of differential equations governing the three-body problem is transformed into an unconstrained optimization problem where simple numerical schemes can be used to find a solution, e.g., nonlinear least-squares is used. This allows for a simpler numerical implementation with comparable accuracy and speed to the traditional differential corrector method.

Mortari, Daniele↗
NASA NTRS2006

A High-Throughput Processor for Flight Control Research Using Small UAVs

There are numerous autopilot systems that are commercially available for small (<100 lbs) UAVs. However, they all share several key disadvantages for conducting aerodynamic research, chief amongst which is the fact that most utilize older, slower, 8- or 16-bit microcontroller technologies. This paper describes the development and testing of a flight control system (FCS) for small UAV s based on a modern, high throughput, embedded processor. In addition, this FCS platform contains user-configurable hardware resources in the form of a Field Programmable Gate Array (FPGA) that can be used to implement custom, application-specific hardware. This hardware can be used to off-load routine tasks such as sensor data collection, from the FCS processor thereby further increasing the computational throughput of the system.

Klenke, Robert H.↗
NASA NTRS1987

SOLON: An autonomous vehicle mission planner

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Dudziak, M. J.↗
NASA NTRS1993

Session on validation of coupled models

The session on validation of coupled models is reviewed. The current use of a mesoscale model with a grid size of 20-km during STORM-FEST in 1992 has proven to be extremely valuable. The availability of forecast products at a much higher temporal and spatial resolution was very helpful for mesoscale forecasting, mission planning, and the guidance of research aircraft. Recent numerical simulation of ocean cyclones and mesoscsle convective systems using nonhydrostatic cloud/mesoscale models with a grid size as small as 2-km have demonstrated the potential of these models for predicting mesoscale convective systems, squall lines, hurricane rainbands, mesoscale gravity waves, and mesoscale frontal structures embedded within an extratropical cyclone. Although mesoscale/cloud scale models have demonstrated strong potential for use in operational forecasting, very limited quantitative evaluation (and verification) of these models were performed. As a result, the accuracy, the systematic biases, and the useful forecasts limits were not properly defined for these models. Also, no serious attempts were made to use these models for operational prediction of mesoscale convective systems.

Kuo, Bill↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

A formulation is presented for identification of linear multivariable from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identifications, by extension of the repetition domain concept to include shifting time intervals. This method contrasts with existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate.

Phan, Minh↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

This paper presents a formulation for identification of linear multivariable systems from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identification, by extension of the repetition domain concept to include shifting time intervals. This contrasts existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate the proposed method.

Phan, Minh↗
NASA NTRS1998

Dark Matter and Extragalactic Gas Clouds in the NGC 4532/DDO 137 System

H I synthesis mapping of NGC 4532 and DDO 137, a pair of Sm galaxies on the edge of the Virgo cluster, is used to determine rotation curves for each of the galaxies and to resolve the structure and kinematics of three extragalactic H I clouds embedded in an extended envelope of diffuse HI discovered in earlier Arecibo studies of the system.

Dark Matter Extragalactic Gas Clouds mappinig↗
NASA NTRS2000

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗
NASA NTRSDate not supplied

Developing Wear-Resistant Coatings for Lunar Dust Tolerant Applications

Materials resistant to the harsh lunar environment are needed to support long duration, sustainable missions on the Moon’s surface. Lunar dust poses a significant threat to the durability of components and vehicles due to its fine, jagged morphology and highly abrasive nature. These properties result in particles eroding, adhering and/or embedding onto component surfaces and into device confined geometries (e.g., gear housing, interlocking systems, etc.) potentially leading to premature failure. The aim of this work is to identify and characterize wear-resistant materials for use as protective coatings to minimize abrasion caused by lunar dust.Concurrently, testing and evaluation methods will be devised to elucidate and mimic aspects of lunar dust degradation, including particle embedding, gouging and erosion caused by high velocity impact events. Discussion on balancing the need for dust management and tolerance versus dust adhesion mitigation will be shared in context of relevant lunar applications within the NASA Lunar Occupancy Dust Surface Separation Technologies (LO-DuSST) effort, which is part of a NASA-wide effort to enable a sustained lunar presence through the Lunar Surface Innovation Initiative (LSII).

Materials, Coatings, lunar dust management/mitigat↗
NASA NTRSDate not supplied

Embedding Differential Dynamic Logic in PVS

Differential dynamic logic (dL) is a formal framework for specifying and reasoning about hybrid systems, i.e., dynamical systems that exhibit both continuous and discrete behaviors. These kinds of systems arise in many safety- and mission-critical applications. This paper presents a formalization of dL in the Prototype Verification System (PVS) that includes the semantics of hybrid programs and dL’s proof calculus. The formalization embeds dL into the PVS logic, resulting in a version of dL whose proof calculus is not only formally verified, but is also available for the verification of hybrid programs within PVS itself. This embedding, called Plaidypvs (Properly Assured Implementation of dL for Hybrid Program Verification and Specification), supports standard dL style proofs, but further leverages the capabilities of PVS to allow reasoning about entire classes of hybrid programs. The embedding also allows the user to import the well-established definitions and mathematical theories available in PVS.

PVS↗
NASA NTRSDate not supplied

Characteristics and Origins of Frontal Convection During IMPACTS on 25 January 2020

This presentation will discuss the characteristics of frontal convection and its estimation from the ER-2 multifrequency nadir reflectivity and Doppler velocity from a warm-occlusion frontal system that traversed across the Northeast U.S. on 25 January 2020. This system that occurred during the IMPACTS field deployment, brought widespread clouds and precipitation to the Northeast. The system brought primarily rain in most areas of more intense rainfall associated with embedded convection near the frontal band and some freezing rain and/or snowfall in the northern regions or higher terrain due to the pre-existing low-level cold air. The NASA ER-2 instrumented with multifrequency radar and the NASA P-3 with in situ microphysics measurements both collected data from this system. The focus of this presentation is on the estimation of vertical velocity in convective and non-convective regions using the ER-2 nadir Doppler measurements. Vertical velocities are inherently difficult to estimate in frontal systems at mesoscale and below other than from direct in situ measurement because of their small magnitudes and errors in the measurements. Estimates from nadir Doppler measurements such as from the ER-2 are challenging because of both Doppler velocity uncertainties and the need to estimate particle fallspeed since the Doppler measurement is the vertical velocity plus the hydrometeor fallspeed. In the presentation, the vertical velocity estimation, its associated errors, and a possible mitigation scheme are described. The characteristics of the convective and stratiform regions on 25 January 2020 are discussed. The vertical velocity estimated from the nadir Doppler measurements are compared with P-3 in situ measurements. Estimation of vertical velocity is one of the goals for upcoming spaceborne missions such as EarthCare and ACCP.

Gerald M. Heymsfield↗
NASA NTRSDate not supplied

Flow Boiling in Microgap Coolers - Suborbital Flight Results

Flow Boiling in Microgap Coolers (FBMC) is a thermal management technique that provides embedded, on-site heat removal for power dense electronic components and systems. The dielectric coolant undergoes liquid-to-vapor phase change as it passes through channels integrated within or between devices. By facilitating direct contact between the coolant and heat-generating devices and relying on phase change, the system provides tight temperature control, hot spot mitigation, very high heat transfer coefficients, and low pumping power. Ground tests demonstrated removal of high heat fluxes (up to 500 kW/m2), very high coefficients of performance (up to 40 W of heat transferred per W of pumping power), and consistent performance across five evaporator orientations under the appropriate conditions. As a follow-on study and to better assess the role of gravity on such two-phase systems, the FBMC payload was developed and flown twice aboard the Blue Origin New Shepard space vehicle in January and May 2019. Each flight exposed the payload to weightlessness (150 seconds below 0.01 g) and shorter periods of high-g during ascent (up to 3 g) and descent (up to 5 g). The flow boiling performance was consistent independent of the acceleration levels, which provides confidence that such systems will provide consistent performance when tested on the ground, orbiting or traveling through weightlessness, and operating on the surface of the Moon, Mars, and other planetary bodies. Details of the flight results, payload development, flight environment, and planned future testing will be presented.

Flow boiling↗