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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

GISS Model E2.2: A Climate Model Optimized for the Middle Atmosphere. Part 2: Validation of Large-Scale Transport and Evaluation of Climate Response

Here we examine the large‐scale transport characteristics of the new ``Middle Atmosphere" NASA Goddard Institute for Space Studies climate model (E2.2). First we evaluate the stratospheric transport circulation in historical atmosphere‐only simulations integrated with interactive trace gas and aerosol chemistry. Compared to lower vertical resolution model versions, E2.2 exhibits improved tropical ascent and older stratospheric mean ages that are more consistent with observed values. In the troposphere, poleward transport to the Arctic and interhemispheric mean ages in E2.2 are comparable to models participating in the Chemistry Climate Modeling Initiative. In addition to validating E2.2 we also assess its ``transport sensitivity" using the coupled atmosphere‐ocean abrupt 4xCO2 and transient 1%CO2 simulations submitted to the Coupled Model Intercomparison Project, Phase 6, along with a 2xCO2 simulation used to evaluate the linearity of the transport circulation's response to increased CO2. We show that decreases (increases) in a stratospheric mean age (idealized surface loss) tracer scale linearly with increased lower stratospheric upwelling, which also increases linearly with warming tropical sea surface temperatures (SSTs). Abrupt 2xCO2 and 4xCO2 experiments constrained with (fixed) pre‐industrial SSTs are also used to quantify the relative importance of rapid adjustments versus SST feedbacks to the transport circulation responses in the model. Finally, sensitivity experiments are presented to illustrate the impact of changes in the convective parameterization on stratospheric transport.

GISS Model E2.2↗
NASA NTRS1972

Structural model optimization using statistical evaluation

The results of research in applying statistical methods to the problem of structural dynamic system identification are presented. The study is in three parts: a review of previous approaches by other researchers, a development of various linear estimators which might find application, and the design and development of a computer program which uses a Bayesian estimator. The method is tried on two models and is successful where the predicted stiffness matrix is a proper model, e.g., a bending beam is represented by a bending model. Difficulties are encountered when the model concept varies. There is also evidence that nonlinearity must be handled properly to speed the convergence.

Collins, J. D.↗
NASA NTRS1974

Model optimization using statistical estimation

Program revises initial or prior estimate of stiffness and mass parameters to parameters yielding frequency and mode characteristics in agreement with test data. Variances are also calculated and consequently define uncertainties of final estimates.

Collins, J. D.↗
NASA NTRS1981

An optimization model for energy generation and distribution in a dynamic facility

An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.

Lansing, F. L.↗
NASA NTRS2006

Increasing Efficiency at the NTF by Optimizing Model AoA Positioning

The National Transonic Facility (NTF) at NASA Langley Research Center (LaRC) is a national resource for aeronautical research and development. The government, military and private industries rely on the capability of this facility for realistic flight data. Reducing the operation costs and keeping the NTF affordable is essential for aeronautics research. The NTF is undertaking an effort to reduce the time between data points during a pitch polar. This reduction is being driven by the operating costs of a cryogenic facility. If the time per data point can be reduced, a substantial cost savings can be realized from a reduction in liquid nitrogen (LN2) consumption. It is known that angle-of-attack (AoA) positioning is the longest lead-time item between points. In January 2005 a test was conducted at the NTF to determine the cause of the long lead-time so that an effort could be made to improve efficiency. The AoA signal at the NTF originates from onboard instrumentation then travels through a number of different systems including the signal conditioner, digital voltmeter, and the data system where the AoA angle is calculated. It is then fed into a closed loop control system that sets the model position. Each process along this path adds to the time per data point affecting the efficiency of the data taking process. Due to the nature of the closed loop feed back AoA control and the signal path, it takes approximately 18 seconds to take one pitch pause point with a typical AoA increment. Options are being investigated to reduce the time delay between points by modifying the signal path. These options include: reduced signal filtering, using analog channels instead of a digital volt meter (DVM), re-routing the signal directly to the AoA control computer and implementing new control algorithms. Each of these has potential to reduce the positioning time and together the savings could be significant. These timesaving efforts are essential but must be weighed against possible loss of data quality. For example, a reduction in filtering can introduce noise into the signal and using analog channels could result in some loss of accuracy. Data quality assessments need to be performed concurrently with timesaving techniques since data quality parameters are essential in maintaining facility integrity. This paper will highlight time saving efforts being undertaken or studied at the NTF. It will outline the instrumentation and computer systems involved in setting of the model pitch attitude then suggest changes to the process and discuss how these system changes would effect the time between data points. It also discusses the issue of data quality and how the potential efficiency changes in the system could affect it. Lastly, it will discuss the possibility of using an open loop control system and give some pros and cons of this method.

Crawford, Bradley L.↗
NASA NTRS1995

Modeling using optimization routines

Modeling using mathematical optimization dynamics is a design tool used in magnetic suspension system development. MATLAB (software) is used to calculate minimum cost and other desired constraints. The parameters to be measured are programmed into mathematical equations. MATLAB will calculate answers for each set of inputs; inputs cover the boundary limits of the design. A Magnetic Suspension System using Electromagnets Mounted in a Plannar Array is a design system that makes use of optimization modeling.

Thomas, Theodore↗
NASA NTRS2020

Review: Strategies for Using Satellite-Based Products in Modeling PM2.5 and Short-Term Pollution Episodes

Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This brief review of using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some R code for data processing and modeling.

Meytar Sorek-Hamer↗
NASA NTRS1983

Optimal symmetric flight with an intermediate vehicle model

Optimal flight in the vertical plane with a vehicle model intermediate in complexity between the point-mass and energy models is studied. Flight-path angle takes on the role of a control variable. Range-open problems feature subarcs of vertical flight and singular subarcs. The class of altitude-speed-range-time optimization problems with fuel expenditure unspecified is investigated and some interesting phenomena uncovered. The maximum-lift-to-drag glide appears as part of the family, final-time-open, with appropriate initial and terminal transient exceeding level-flight drag, some members exhibiting oscillations. Oscillatory paths generally fail the Jacobi test for durations exceeding a period and furnish a minimum only for short-duration problems.

Menon, P. K. A.↗
NASA NTRS1977

Prediction of pilot opinion ratings using an optimal pilot model

A brief review of some of the more pertinent applications of analytical pilot models to the prediction of aircraft handling qualities is undertaken. The relative ease with which multiloop piloting tasks can be modeled via the optimal control formulation makes the use of optimal pilot models particularly attractive for handling qualities research. To this end, a rating hypothesis is introduced which relates the numerical pilot opinion rating assigned to a particular vehicle and task to the numerical value of the index of performance resulting from an optimal pilot modeling procedure as applied to that vehicle and task. This hypothesis is tested using data from piloted simulations and is shown to be reasonable. An example concerning a helicopter landing approach is introduced to outline the predictive capability of the rating hypothesis in multiaxis piloting tasks.

Hess, R. A.↗
NASA NTRS2010

Comparison of Iterative and Non-Iterative Strain-Gage Balance Load Calculation Methods

The accuracy of iterative and non-iterative strain-gage balance load calculation methods was compared using data from the calibration of a force balance. Two iterative and one non-iterative method were investigated. In addition, transformations were applied to balance loads in order to process the calibration data in both direct read and force balance format. NASA's regression model optimization tool BALFIT was used to generate optimized regression models of the calibration data for each of the three load calculation methods. This approach made sure that the selected regression models met strict statistical quality requirements. The comparison of the standard deviation of the load residuals showed that the first iterative method may be applied to data in both the direct read and force balance format. The second iterative method, on the other hand, implicitly assumes that the primary gage sensitivities of all balance gages exist. Therefore, the second iterative method only works if the given balance data is processed in force balance format. The calibration data set was also processed using the non-iterative method. Standard deviations of the load residuals for the three load calculation methods were compared. Overall, the standard deviations show very good agreement. The load prediction accuracies of the three methods appear to be compatible as long as regression models used to analyze the calibration data meet strict statistical quality requirements. Recent improvements of the regression model optimization tool BALFIT are also discussed in the paper.

Ulbrich, N.↗
NASA NTRS1989

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

Zipf, Mark E.↗
NASA NTRS2006

Problem Formulation for Optimal Array Modeling and Planning

In this paper we describe an optimal modeling and planning framework for the future large array of DSN antennas. This framework takes into account the array link performance models, reliability models, constrain models, and objective functions, and determines the optimal sub-array clusters configuration that will support the maximum number of concurrent missions based on mission link properties, antenna element reliabilities, mission requests, and array operation constraints. ..

modeling↗
NASA NTRS1976

A method for generating numerical pilot opinion ratings using the optimal pilot model

A method for generating numerical pilot opinion ratings using the optimal pilot model is introduced. The method is contained in a rating hypothesis which states that the numerical rating which a human pilot assigns to a specific vehicle and task can be directly related to the numerical value of the index of performance resulting from the optimal pilot modeling procedure as applied to that vehicle and task. The hypothesis is tested using the data from four piloted simulations. The results indicate that the hypothesis is reasonable, but that the predictive capability of the method is a strong function of the accuracy of the pilot model itself. This accuracy is, in turn, dependent upon the parameters which define the optimal modeling problem. A procedure for specifying the parameters for the optimal pilot model in the absence of experimental data is suggested.

Hess, R. A.↗
NASA NTRS2010

Analysis of Sting Balance Calibration Data Using Optimized Regression Models

Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.

Ulbrich, N.↗
NASA NTRS1993

Bayesian image reconstruction - The pixon and optimal image modeling

In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

Pina, R. K.↗