Strategies for Uncertainty Modeling and Optimization Under Uncertainty
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Strategies for↗
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Results for “Model 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.
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A quasi-Newton procedure for identifying pilot-related parameters of the optimal control model
The development and application of a quasi-Newton gradient search procedure for identifying independent pilot related parameters of the optimal control model for pilot/vehicle systems is reported. A sensitivity analysis procedure which determines whether a given model parameter is required to match a specific experimental result, and which experimentally induced parameter changes are required to account for behavioral and performance differences, is described. Application of the identification scheme to training effects in a manual control task is described.
Levison, W. H.↗
Analysis of response to wind-shears using the optimal control model of the human operator
The effects of wind-shears on the approach performance of a STOL aircraft are analyzed using the optimal-control model of the human operator. This analysis involves a time-varying situation that is more complex than is traditionally treated by human operator modelling techniques. The extensions to the time-varying case are discussed and results are presented that illustrate the effects of wind shears on category II window-performance and the effects on performance of pilot time-delay and of variations in pilot gain during approach.
Baron, S.↗
Studies in Software Cost Model Behavior: Do We Really Understand Cost Model Performance?
While there exists extensive literature on software cost estimation techniques, industry practice continues to rely upon standard regression-based algorithms. These software effort models are typically calibrated or tuned to local conditions using local data. This paper cautions that current approaches to model calibration often produce sub-optimal models because of the large variance problem inherent in cost data and by including far more effort multipliers than the data supports. Building optimal models requires that a wider range of models be considered while correctly calibrating these models requires rejection rules that prune variables and records and use multiple criteria for evaluating model performance. The main contribution of this paper is to document a standard method that integrates formal model identification, estimation, and validation. It also documents what we call the large variance problem that is a leading cause of cost model brittleness or instability.
data mining↗
Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study
The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.
Johannsen, G.↗
Using Agent Base Models to Optimize Large Scale Network for Large System Inventories
The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.
Shameldin, Ramez Ahmed↗
Enhancing Radiative Transfer Models for Optimized Assimilation of Microwave and Radar Observations
Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.
Isaac Moradi↗
Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements
The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.
risk assessment↗
Operations research investigations of satellite power stations
A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.
Cole, J. W.↗
Developing interpretable models with optimized set reduction for identifying high risk software components
Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.
Briand, Lionel C.↗
Analysis of a VTOL hover task with predictor displays using an optimal control model of the human operator
The influence of different types of predictor displays in a longitudinal VTOL hover task is analyzed in a theoretical study. It was assumed that pitch angle and position are presented to the pilot in separate displays namely the artificial horizon and position display. The predictive information is calculated by means of a Taylor series. From earlier experimental studies it is well known that predictor displays improve human and system performance and result in reducing human workload. In this study, an optimal control model is used to prove this effect theoretically. Several cases with differing amounts of predictive and rate information are compared.
Johannsen, G.↗
Geomagnetic field modeling by optimal recursive filtering
Five individual 5 year mini-batch geomagnetic models were generated and two computer programs were developed to process the models. The first program computes statistics (mean sigma, weighted sigma) on the changes in the first derivatives (linear terms) of the spherical harmonic coefficients between mini-batches. The program ran successfully. The statistics are intended for use in computing the state noise matrix required in the information filter. The second program is the information filter. Most subroutines used in the filter were tested, but the coefficient statistics must be analyzed before the filter is run.
Source record↗
Mathematical Model of a Regenerative Fuel Cell for System Optimization
This thesis developed a system-level optimization model of a regenerative fuel cell (RFC) system for long-duration, off-world energy storage applications. Prior RFC design studies have typically been limited to reduced parameter sets and simplified constraints due to computational limitations relative to the number of relevant degrees of freedom. As a result, important nonlinear interactions between subsystems have not been fully captured. This work began to address that gap by developing a higher-fidelity, nonlinear optimization framework that incorporates a broader set of design variables and coupled constraints, enabling a multidimensional model that captures the coupled behavior of RFC subsystems and demonstrates the feasibility of applying optimization to such systems. An expanded system-level optimization approach was established that captures interactions between electrochemical performance, structural requirements, and storage design. This enabled a more comprehensive evaluation of trade-offs than conventional formulations. The model integrates four coupled subsystems: a fuel cell, an electrolyzer, reactant gas, and high-pressure storage tanks, and was formulated to accommodate a wide range of mission parameters, including operational time and required output power. It incorporates constraints on available solar array power, reactant mass balance between production and consumption, and pressure-dependent storage requirements. To enable reliable convergence, the optimization problem was reformulated to reduce dimensionality and improve numerical stability, with subsystem models organized for efficient evaluation. Problem dimensionality was reduced by consolidating lower-level design variables into higher-level representative quantities, and subsystem behavior was evaluated within the optimization loop. A multi-start initialization strategy was employed to mitigate sensitivity to local minima and improve solution quality, while nonlinear relationships were solved using robust numerical methods. The results showed that convergence was achieved across a range of required output power values. Specific energy reached a maximum at a critical mission power level, where the electrolyzer power matched the available solar input and operated near its voltage and current density limits. Beyond this point, further increases in required power resulted in less mass-efficient operation, increasing total system mass and reducing overall performance. The developed model represents an advancement in RFC system-level optimization by enabling analysis of a broader and more tightly coupled design space than previous considerations. While convergence behavior and computational cost remain challenges, the methods introduced improve solvability and allow inclusion of additional design variables with minimal loss of physical fidelity. However, the numerical results should not be interpreted as definitive design recommendations, as the model includes simplifying assumptions and omits several higher-order effects. Future work should extend this framework by incorporating additional subsystems and loss mechanisms, such as thermal management, parasitic power consumption, and reactant losses, to improve fidelity and ensure more representative design conclusions.
Electrochemistry↗
An aircraft noise pollution model for trajectory optimization
A mathematical model describing the generation of aircraft noise is developed with the ultimate purpose of reducing noise (noise-optimizing landing trajectories) in terminal areas. While the model is for a specific aircraft (Boeing 737), the methodology would be applicable to a wide variety of aircraft. The model is used to obtain a footprint on the ground inside of which the noise level is at or above 70 dB.
Barkana, A.↗
Solution of nonlinear finite difference ocean models by optimization methods with sensitivity and observational strategy analysis
The paper studies with finite difference nonlinear circulation models the uncertainties in interesting flow properties, such as western boundary current transport, potential and kinetic energy, owing to the uncertainty in the driving surface boundary condition. The procedure is based upon nonlinear optimization methods. The same calculations permit quantitative study of the importance of new information as a function of type, region of measurement and accuracy, providing a method to study various observing strategies. Uncertainty in a model parameter, the bottom friction coefficient, is studied in conjunction with uncertain measurements. The model is free to adjust the bottom friction coefficient such that an objective function is minimized while fitting a set of data to within prescribed bounds. The relative importance of the accuracy of the knowledge about the friction coefficient with respect to various kinds of observations is then quantified, and the possible range of the friction coefficients is calculated.
Schroeter, Jens↗
Effects of noise variance model on optimal feedback design and actuator placement
In optimal placement of actuators for stochastic systems, it is commonly assumed that the actuator noise variances are not related to the feedback matrix and the actuator locations. In this paper, we will discuss the limitation of that assumption and develop a more practical noise variance model. Various properties associated with optimal actuator placement under the assumption of this noise variance model are discovered through the analytical study of a second order system.
Ruan, Mifang↗
On the modeling and optimization of Schottky varactor frequency multipliers at submillimeter wavelengths
Schottky varactor frequency multipliers are used to generate local oscillator power at millimeter and submillimeter wavelengths. The equivalent circuit of the Schottky varactor contains a junction capacitance, a junction conductance, a series resistance and a model for electron velocity saturation. A millimeter wavelengths the equivalent circuits is affected by the edge effects, which are due to the small-area circular anode. The correction factors due to the edge effect for the junction capacitance and for the series resistance are available in the literature. In this work the electron velocity saturation is modeled by limiting the velocity of the transition front between the depleted and undepleted layer. By using this model the maximum current of the diode is given by the actual area of the transition front between depleted and undepleted layers, and is therefore related to the capacitance correction factor. The new model has been tested by analyzing a two diode balanced doubler for 160 GHz presented earlier in the literature. The agreement between the theoretical results and the measurements is excellent. The new diode model is useful in optimization of varactors for high millimeter and submillimeter wave frequencies.
TRT-THEORETICAL↗
The Development and Use of a Flight Optimization System Model of a C-130E Transport Aircraft
The Systems Analysis Branch at NASA Langley Research Center conducts a variety of aircraft design and analyses studies. These studies include the prediction of characteristics of a particular conceptual design, analyses of designs that already exist, and assessments of the impact of technology on current and future aircraft. The FLight OPtimization System (FLOPS) is a tool used for aircraft systems analysis and design. A baseline input model of a Lockheed C-130E was generated for the Flight Optimization System. This FLOPS model can be used to conduct design-trade studies and technology impact assessments. The input model was generated using standard input data such as basic geometries and mission specifications. All of the other data needed to determine the airplane performance is computed internally by FLOPS. The model was then calibrated to reproduce the actual airplane performance from flight test data. This allows a systems analyzer to change a specific item of geometry or mission definition in the FLOPS input file and evaluate the resulting change in performance from the output file. The baseline model of the C-130E was used to analyze the effects of implementing upper wing surface blowing on the airplane. This involved removing the turboprop engines that were on the C-130E and replacing them with turbofan engines. An investigation of the improvements in airplane performance with the new engines could be conducted within the Flight Optimization System. Although a thorough analysis was not completed, the impact of this change on basic mission performance was investigated.
Desch, Jeremy D.↗