Search NASA⌕ Search

SEARCH · Search NASA

Results for “Parameters optimization”

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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Flow properties of the solar wind obtained from white light data and a two-fluid model

The flow properties of the solar wind from 1 R(sub s) to 1 AU were obtained using a two fluid model constrained by density and scale height temperatures derived from white light observations, as well as knowledge of the electron temperature in coronal holes. The observations were obtained with the white light coronographs on SPARTAN 201-1 and at Mauna Loa (Hawaii), in a north polar coronal hole from 1.16 to 5.5 R(sub s) on 11 Apr. 1993. By specifying the density, temperature, Alfven wave velocity amplitude and heating function at the coronal base, it was found that the model parameters fit well the constraints of the empirical density profiles and temperatures. The optimal range of the input parameters was found to yield a higher proton temperature than electron temperature in the inner corona. The results indicate that no preferential heating of the protons at larger distances is needed to produce higher proton than electron temperatures at 1 AU, as observed in the high speed solar wind.

Habbal, Shadia Rifai↗
NASA NTRS2008

Developing Optimized Trajectories Derived from Mission and Thermo-Structural Constraints

In conjunction with NASA and the Department of Defense, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) has been investigating analytical techniques to address many of the fundamental issues associated with solar exploration spacecraft and high-speed atmospheric vehicle systems. These issues include: thermo-structural response including the effects of thermal management via the use of surface optical properties for high-temperature composite structures; aerodynamics with the effects of non-equilibrium chemistry and gas radiation; and aero-thermodynamics with the effects of material ablation for a wide range of thermal protection system (TPS) materials. The need exists to integrate these discrete tools into a common framework that enables the investigation of interdisciplinary interactions (including analysis tool, applied load, and environment uncertainties) to provide high fidelity solutions. In addition to developing robust tools for the coupling of aerodynamically induced thermal and mechanical loads, JHU/APL has been studying the optimal design of high-speed vehicles as a function of their trajectory. Under traditional design methodology the optimization of system level mission parameters such as range and time of flight is performed independently of the optimization for thermal and mechanical constraints such as stress and temperature. A truly optimal trajectory should optimize over the entire range of mission and thermo-mechanical constraints. Under this research, a framework for the robust analysis of high-speed spacecraft and atmospheric vehicle systems has been developed. It has been built around a generic, loosely coupled framework such that a variety of readily available analysis tools can be used. The methodology immediately addresses many of the current analysis inadequacies and allows for future extension in order to handle more complex problems.

Lear, Matthew H.↗
NASA NTRS1988

A new code for Galileo

Over the past six to eight years, an extensive research effort was conducted to investigate advanced coding techniques which promised to yield more coding gain than is available with current NASA standard codes. The delay in Galileo's launch due to the temporary suspension of the shuttle program provided the Galileo project with an opportunity to evaluate the possibility of including some version of the advanced codes as a mission enhancement option. A study was initiated last summer to determine if substantial coding gain was feasible for Galileo and, is so, to recommend a suitable experimental code for use as a switchable alternative to the current NASA-standard code. The Galileo experimental code study resulted in the selection of a code with constant length 15 and rate 1/4. The code parameters were chosen to optimize performance within cost and risk constraints consistent with retrofitting the new code into the existing Galileo system design and launch schedule. The particular code was recommended after a very limited search among good codes with the chosen parameters. It will theoretically yield about 1.5 dB enhancement under idealizing assumptions relative to the current NASA-standard code at Galileo's desired bit error rates. This ideal predicted gain includes enough cushion to meet the project's target of at least 1 dB enhancement under real, non-ideal conditions.

Dolinar, S.↗
NASA NTRS2011

Optimal Asteroid Mass Determination from Planetary Range Observations: A Study of a Simplified Test Model

Mars ranging observations are available over the past 10 years with an accuracy of a few meters. Such precise measurements of the Earth-Mars distance provide valuable constraints on the masses of the asteroids perturbing both planets. Today more than 30 asteroid masses have thus been estimated from planetary ranging data (see [1] and [2]). Obtaining unbiased mass estimations is nevertheless difficult. Various systematic errors can be introduced by imperfect reduction of spacecraft tracking observations to planetary ranging data. The large number of asteroids and the limited a priori knowledge of their masses is also an obstacle for parameter selection. Fitting in a model a mass of a negligible perturber, or on the contrary omitting a significant perturber, will induce important bias in determined asteroid masses. In this communication, we investigate a simplified version of the mass determination problem. Instead of planetary ranging observations from spacecraft or radar data, we consider synthetic ranging observations generated with the INPOP [2] ephemeris for a test model containing ~25000 asteroids. We then suggest a method for optimal parameter selection and estimation in this simplified framework.

asteroids↗
NASA NTRS2012

Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

Simon, Donald L.↗
NASA NTRS1996

Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters

The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.

Pindera, Marek-Jerzy↗
NASA NTRS2011

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗
NASA NTRS1974

Optimal rocket thrust profile shaping using third degree spline function interpolation

Optimal solid-rocket thrust profiles for the parallel-burn, solid-rocket-assisted space shuttle are investigated. Solid-rocket thrust profiles are simulated by using third-degree spline functions, with the values of the thrust ordinates defined as parameters. The profiles are optimized parametrically, using the Davidon-Fletcher-Powell penalty function method, by minimizing propellant weight subject to state and control inequality constraints and to terminal boundary conditions. This study shows that optimizing a control variable parametrically by using third-degree spline function interpolation allows the control to be shaped so that inequality constraints are strictly adhered to and all corners are eliminated. The absence of corners, which is realistic in nature, makes this method attractive from the viewpoint of solid rocket grain design.

Johnson, I. L.↗
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https://cneos.jpl.nasa.gov/ pd/cs/pdc17/. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or lowthrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft/asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth/spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection

Barbee, Brent W.↗
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https:cneos.jpl.nasa.govpdcspdc17. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or low-thrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft, asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth-spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection.

Barbee, Brent W.↗
NASA NTRS1979

Local neighborhood transition probability estimation and its use in contextual classification

The problem of incorporating spatial or contextual information into classifications is considered. A simple model that describes the spatial dependencies between the neighboring pixels with a single parameter, Theta, is presented. Expressions are derived for updating the posteriori probabilities of the states of nature of the pattern under consideration using information from the neighboring patterns, both for spatially uniform context and for Markov dependencies in terms of Theta. Techniques for obtaining the optimal value of the parameter Theta as a maximum likelihood estimate from the local neighborhood of the pattern under consideration are developed.

Chittineni, C. B.↗
NASA NTRS2006

Static and Dynamic Model Update of an Inflatable/Rigidizable Torus Structure

The present work addresses the development of an experimental and computational procedure for validating finite element models. A torus structure, part of an inflatable/rigidizable Hexapod, is used to demonstrate the approach. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with optimization is used to modify key model parameters. Static test results are used to update stiffness parameters and dynamic test results are used to update the mass distribution. Updated parameters are computed using gradient and non-gradient based optimization algorithms. Results show significant improvements in model predictions after parameters are updated. Lessons learned in the areas of test procedures, modeling approaches, and uncertainties quantification are presented.

Horta, Lucas G.↗
NASA NTRS1991

Pultrusion process characterization

Pultrusion is a process through which high-modulus, lightweight composite structural members such as beams, truss components, stiffeners, etc., are manufactured. The pultrusion process, though a well-developed processing art, lacks a fundamental scientific understanding. The objective here was to determine, both experimentally and analytically, the process parameters most important in characterizing and optimizing the pultrusion of uniaxial fibers. The effects of process parameter interactions were experimentally examined as a function of the pultruded product properties. A numerical description based on these experimental results was developed. An analytical model of the pultrusion process was also developed. The objective of the modeling effort was the formulation of a two-dimensional heat transfer model and development of solutions for the governing differential equations using the finite element method.

Vaughan, James G.↗
NASA NTRS2013

Quasi-Linear Circuit

This work involved developing spacequalifiable switch mode DC/DC power supplies that improve performance with fewer components, and result in elimination of digital components and reduction in magnetics. This design is for missions where systems may be operating under extreme conditions, especially at elevated temperature levels from 200 to 300 degC. Prior art for radiation-tolerant DC/DC converters has been accomplished utilizing classical magnetic-based switch mode converter topologies; however, this requires specific shielding and component de-rating to meet the high-reliability specifications. It requires complex measurement and feedback components, and will not enable automatic re-optimization for larger changes in voltage supply or electrical loading condition. The innovation is a switch mode DC/DC power supply that eliminates the need for processors and most magnetics. It can provide a well-regulated voltage supply with a gain of 1:100 step-up to 8:1 step down, tolerating an up to 30% fluctuation of the voltage supply parameters. The circuit incorporates a ceramic core transformer in a manner that enables it to provide a well-regulated voltage output without use of any processor components or magnetic transformers. The circuit adjusts its internal parameters to re-optimize its performance for changes in supply voltage, environmental conditions, or electrical loading at the output

Bradley, William↗
NASA NTRS1991

Parameter estimation for distributed parameter models of complex, flexible structures

Distributed parameter modeling of structural dynamics has been limited to simple spacecraft configurations because of the difficulty of handling several distributed parameter systems linked at their boundaries. Although there is other computer software able to generate such models or complex, flexible spacecraft, unfortunately, neither is suitable for parameter estimation. Because of this limitation the computer software PDEMOD is being developed for the express purposes of modeling, control system analysis, parameter estimation and structure optimization. PDEMOD is capable of modeling complex, flexible spacecraft which consist of a three-dimensional network of flexible beams and rigid bodies. Each beam has bending (Bernoulli-Euler or Timoshenko) in two directions, torsion, and elongation degrees of freedom. The rigid bodies can be attached to the beam ends at any angle or body location. PDEMOD is also capable of performing parameter estimation based on matching experimental modal frequencies and static deflection test data. The underlying formulation and the results of using this approach for test data of the Mini-MAST truss will be discussed. The resulting accuracy of the parameter estimates when using such limited data can impact significantly the instrumentation requirements for on-orbit tests.

Taylor, Lawrence W., Jr.↗
NASA NTRS2018

A Markov Decision Process Framework for Optimal Airport Reconfiguration

The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.

runway reconfiguration↗
NASA NTRS2011

Nondimensional Representations for Occulter Design and Performance Evaluation

An occulter is a spacecraft with a precisely-shaped optical edges which ies in formation with a telescope, blocking light from a star while leaving light from nearby planets una ected. Using linear optimization, occulters can be designed for use with telescopes over a wide range of telescope aperture sizes, science bands, and starlight suppression levels. It can be shown that this optimization depends primarily on a small number of independent nondimensional parameters, which correspond to Fresnel numbers and physical scales and enter the optimization only as constraints. We show how these can be used to span the parameter space of possible optimized occulters; this data set can then be mined to determine occulter sizes for various mission scenarios and sets of engineering constraints.

Earth like planets↗
NASA NTRS1994

Modeling tropical Pacific sea surface temperature with satellite-derived solar radiative forcing

Two independent datasets for the solar radiation at the surface derived from satellites are compared. The data derived from the Earth Radiation Budget Experiment (ERBE) is for the net solar radiation at the surface whereas the International Satellite Cloud Climatology Project (ISCCP) data is for the downward flux only and was corrected with a space- and time-varying albedo. The ISCCP net flux is at all times higher than the ERBE flux. The difference can be divided into an offset that decreases with latitude and another component that correlates with high tropical cloud cover. With this latter exception the two datasets provide spatial patterns of solar flux that are very similar. A tropical Pacific Ocean model is forced with these two datasets and observed climatological winds. The upward heat flux is parameterized taking into account separately the longwave radiative, latent, and sensible heat fluxes. Best fit values for the uncertain parameters are found using an optimization procedure that seeks to minimize the difference between model and observed SST by varying the parameters within a reasonable range of uncertainty. The SST field the model produces with the best fit parameters is the best the model can do. If the differences between the model and data are larger than can be accounted for by remaining uncertainties in the heat flux parameterization and forcing data then the ocean model must be held to be at fault. Using this method of analysis, a fundamental model fault is identified. Inadequate treatment of mixed layer/entrainment processes in upwelling regions of the eastern tropical Pacific leads to a large and seasonally varying error in the model SST. Elsewhere the model SST is insufficiently different from observed to be able to identify model errors.

Seager, Richard↗