Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reference Model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

The 2006 Cape Canaveral Air Force Station Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the National Aeronautics and Space Administration's Space Shuttle

NASA's Space Shuttle utilizes atmospheric thermodynamic properties to evaluate structural dynamics and vehicle flight performance impacts by the atmosphere during ascent. Statistical characteristics of atmospheric thermodynamic properties at Kennedy Space Center (KSC) used in Space. Shuttle Vehicle assessments are contained in the Cape Canaveral Air Force Station (CCAFS) Range Reference Atmosphere (RRA) Database. Database contains tabulations for monthly and annual means (mu), standard deviations (sigma) and skewness of wind and thermodynamic variables. Wind, Thermodynamic, Humidity and Hydrostatic parameters 1 km resolution interval from 0-30 km 2 km resolution interval 30-70 km Multiple revisions of the CCAFS RRA database have been developed since initial RRA published in 1963. 1971, 1983, 2006 Space Shuttle program utilized 1983 version for use in deriving "hot" and "cold" atmospheres, atmospheric density dispersions for use in vehicle certification analyses and selection of atmospheric thermodynamic profiles for use in vehicle ascent design and certification analyses. During STS-114 launch preparations in July 2005 atmospheric density observations between 50-80 kft exceeded density limits used for aerodynamic ascent heating constraints in vehicle certification analyses. Mission specific analyses were conducted and concluded that the density bias resulted in small changes to heating rates and integrated heat loading on the vehicle. In 2001, the Air Force Combat Climatology Center began developing an updated RRA for CCAFS.

Decker, Ryan↗
NASA NTRS2008

The 2006 Cape Canaveral Air Force Station Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the National Aeronautics and Space Administration's Space Shuttle

Atmospheric parameters are essential in assessing the flight performance of aerospace vehicles. The effects of the Earth's atmosphere on aerospace vehicles influence various aspects of the vehicle during ascent ranging from its flight trajectory to the structural dynamics and aerodynamic heatmg on the vehicle. Atmospheric databases charactenzing the wind and thermodynamic environments, known as Range Reference Atmospheres (RRA), have been developed at space launch ranges by a governmental interagency working group for use by aerospace vehicle programs. The National Aeronantics and Space Administration's (NASA) Space Shuttle Program (SSP), which launches from Kennedy Space Center, utilizes atmosphenc statistics derived from the Cape Canaveral Air Force Station Range Reference Atmosphere (CCAFS RRA) database to evaluate environmental constraints on various aspects of the vehlcle during ascent.

Decker, Ryan K.↗
NASA NTRS2009

Robust Optimal Adaptive Control Method with Large Adaptive Gain

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Nguyen, Nhan T.↗
NASA NTRS2011

Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

Miller, Christopher J.↗
NASA NTRS1987

Adaptive control and noise suppression by a variable-gain gradient algorithm

An adaptive control system based on normalized LMS filters is investigated. The finite impulse response of the nonparametric controller is adaptively estimated using a given reference model. Specifically, the following issues are addressed: The stability of the closed loop system is analyzed and heuristically established. Next, the adaptation process is studied for piecewise constant plant parameters. It is shown that by introducing a variable-gain in the gradient algorithm, a substantial reduction in the LMS adaptation rate can be achieved. Finally, process noise at the plant output generally causes a biased estimate of the controller. By introducing a noise suppression scheme, this bias can be substantially reduced and the response of the adapted system becomes very close to that of the reference model. Extensive computer simulations validate these and demonstrate assertions that the system can rapidly adapt to random jumps in plant parameters.

Merhav, S. J.↗
NASA NTRS1976

A global reference atmospheric model for surface to orbital altitudes

An empirical atmospheric model has been developed which generates values for pressure, density, temperature and winds from surface levels to orbital altitudes. The output parameters consist of components for: (1) latitude, longitude, and altitude dependent monthly means; (2) quasi-biennial oscillations; and (3) random perturbations to partially simulate the variability due to synoptic, diurnal, planetary wave and gravity wave variations. The monthly mean models consist of: NASA's four dimensional worldwide model for height, latitude, and longitude dependent monthly means from the surface to 25 km; and a newly developed latitude-longitude dependent model which is an extension of the Groves latitude dependent model for the region between 25 and 90 km. The Jacchia 1970 model is used above 90 km and is faired with the modified Groves values between 90 and 115 km. Quasi-biennial and random variation perturbations are computed from parameters determined from various empirical studies, and are added to the monthly mean values.

Justus, C. G.↗
NASA NTRS1982

Robustness of adaptive control algorithms in the presence of unmodeled dynamics

This paper reports the outcome of an exhaustive analytical and numerical investigation of stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances. The class of adaptive algorithms considered are those commonly referred to as model-reference adaptive control algorithms, self-tuning controllers, and dead-beat adaptive controllers; they have been developed for both continuous-time systems and discrete-time systems. The existing adaptive control algorithms have been proven to be globally asymptotically stable under certain assumptions, the key ones being (1) that the number of poles and zeroes of the unknown plant are known, and (2) that the primary performance criterion is related to good command following. These theoretical assumptions are too restrictive from an engineering point of view. Real plants always contain unmodeled high-frequency dynamics and small delays, and hence no upper bound on the number of the plant poles and zeroes exists. Also real plants are always subject to unmeasurable output additive disturbances, although these may be guide small. Hence, it is important to critically examine the stability robustness properties of the existing adaptive algorithms when some of the theoretical assumptions are removed; in particular, their stability and performance properties in the presence of unmodeled dynamics and output disturbances. Previously announced in STAR as N83-16061

Rohrs, C. E.↗
NASA NTRS1983

Range reference atmosphere models

A description is given of the methods used to establish the statistical parameters and models for wind and various thermodynamic quantities at an altitude of 0-70 km for nine geographical locations. It is noted that wind is modeled as a vector quantity using the bivariate normal probability function. With the five parameters of the bivariate normal distribution, the distribution for wind speed is derived as a generalized Rayleigh distribution. In addition, the frequency of wind direction is derived, and the conditional distribution of wind speed given the wind direction is derived. It is pointed out that these and other wind models are consistent with the rigorous mathematical properties of the bivariate normal probability theory. The thermodynamic quantities are consistent with the hydrostatic equation and the equation of state for the mean values. With these methods, many statistical relationships can be derived.

Smith, O. E.↗
NASA NTRS1989

Global Reference Atmosphere Model (GRAM)

GRAM series of four-dimensional atmospheric model validated by years of data. GRAM program, still available. More current are Gram 86, which includes atmospheric data from 1986 and runs on DEC VAX, and GRAM 88, which runs on IBM 3084. Program generates altitude profiles of atmospheric parameters along any simulated trajectory through atmosphere, and also useful for global circulation and diffusion studies.

Woodrum, A. W.↗
NASA NTRS1989

CHIMERA II - A real-time multiprocessing environment for sensor-based robot control

A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.

Stewart, David B.↗
NASA NTRS1992

Mars global reference atmosphere model (Mars-GRAM)

Mars-GRAM is an empirical model that parameterizes the temperature, pressure, density, and wind structure of the Martian atmosphere from the surface through thermospheric altitudes. In the lower atmosphere of Mars, the model is built around parameterizations of height, latitudinal, longitudinal, and seasonal variations of temperature determined from a survey of published measurements from the Mariner and Viking programs. Pressure and density are inferred from the temperature by making use of the hydrostatic and perfect gas laws relationships. For the upper atmosphere, the thermospheric model of Stewart is used. A hydrostatic interpolation routine is used to insure a smooth transition from the lower portion of the model to the Stewart thermospheric model. Other aspects of the model are discussed.

Justus, C. G.↗
NASA NTRS1993

Global Reference Atmosphere Model (GRAM)

4D model provides atmospheric parameter values either automatically at positions along linear path or along any set of connected positions specified by user. Based on actual data, GRAM provides thermal wind shear for monthly mean winds, percent deviation from standard atmosphere, mean vertical wind, and perturbation data for each position.

Johnson, D. L.↗
NASA NTRS1993

Global Reference Atmospheric Model - 1990

GRAM-90, improvement on original model, provides values of atmospheric parameters, either automatically at positions along linear path or along any set of connected positions specified by user. Parameters produced include monthly total and mean values of pressure, density, temperature, and wind, as well as perturbation values and magnitudes. Also provides thermal wind shear for monthly mean winds, percent deviation from standard atmosphere, mean vertical wind, and perturbation data for each position. Perturbation data consist of values of quasi-biennial and random perturbations. Written in FORTRAN 77.

Justus, C. G.↗
NASA NTRS2007

Earth Global Reference Atmospheric Model (GRAM99): Short Course

Earth-GRAM is a FORTRAN software package that can run on a variety of platforms including PC's. For any time and location in the Earth's atmosphere, Earth-GRAM provides values of atmospheric quantities such as temperature, pressure, density, winds, constituents, etc.. Dispersions (perturbations) of these parameters are also provided and have realistic correlations, means, and variances - useful for Monte Carlo analysis. Earth-GRAM is driven by observations including a tropospheric database available from the National Climatic Data Center. Although Earth-GRAM can be run in a "stand-alone" mode, many users incorporate it into their trajectory codes. The source code is distributed free-of-charge to eligible recipients.

Leslie, Fred W.↗
NASA NTRS2007

Empirical Storm-Time Correction to the International Reference Ionosphere Model E-Region Electron and Ion Density Parameterizations Using Observations from TIMED/SABER

The response of the ionospheric E-region to solar-geomagnetic storms can be characterized using observations of infrared 4.3 micrometers emission. In particular, we utilize nighttime TIMED/SABER measurements of broadband 4.3 micrometers limb emission and derive a new data product, the NO+(v) volume emission rate, which is our primary observation-based quantity for developing an empirical storm-time correction the IRI E-region electron density. In this paper we describe our E-region proxy and outline our strategy for developing the empirical storm model. In our initial studies, we analyzed a six day storm period during the Halloween 2003 event. The results of this analysis are promising and suggest that the ap-index is a viable candidate to use as a magnetic driver for our model.

Mertens, Christoper J.↗
NASA NTRS2008

Earth Global Reference Atmospheric Model 2007 (Earth-GRAM07)

GRAM is a Fortran software package that can run on a variety of platforms including PC's. GRAM provides values of atmospheric quantities such as temperature, pressure, density, winds, constituents, etc. GRAM99 covers all global locations, all months, and heights from the surface to approx. 1000 km). Dispersions (perturbations) of these parameters are also provided and are spatially and temporally correlated. GRAM can be run in a stand-alone mode or called as a subroutine from a trajectory program. GRAM07 is diagnostic, not prognostic (i.e., it describes the atmosphere, but it does not forecast). The source code is distributed free-of-charge to eligible recipients.

Leslie, Fred W.↗
NASA NTRS2008

Utilizing Mars Global Reference Atmospheric Model (Mars-GRAM 2005) to Evaluate Entry Probe Mission Sites

Engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM s perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL)1. Traditional Mars-GRAM options for representing the mean atmosphere along entry corridors include: a) TES Mapping Years 1 and 2, with Mars-GRAM data coming from MGCM model results driven by observed TES dust optical depth; and b) TES Mapping Year 0, with user-controlled dust optical depth and Mars-GRAM data interpolated from MGCM model results driven by selected values of globally-uniform dust optical depth. From the surface to 80 km altitude, Mars-GRAM is based on NASA Ames Mars General Circulation Model (MGCM). Mars-GRAM and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA), with altitudes referenced to the MOLA areoid, or constant potential surface. Mars-GRAM 2005 has been validated2 against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES)

Justh, Hilary L.↗