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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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A mathematical programing model is presented to optimize the selection of Orbital Replacement Unit on-orbit spares for the Space Station. The model maximizes system availability under the constraints of logistics resupply-cargo weight and volume allocations.
Equivalent plate modeling techniques based on Ritz analysis with simple polynomials prove to be efficient tools for structural modeling of wings in the preliminary design stage. Accuracy problems are encountered, however, when these models are used to obtain finite difference behavior sensitivities with respect to planform shape. The accuracy problems are associated with the poor numerical conditioning of static and eigenvalue equations. As higher-order polynomials are being used to Improve the analysis itself, the more sensitive is the finite difference derivative to the step size used. This article describes a formulation of wing equivalent plate modeling in which it is simple to obtain analytic, explicit expressions for stiffness and mass matrix elements without the need to perform numerical integration. This formulation leads naturally to analytic expressions for the derivatives of displacements, stresses, and natural frequencies with respect to shape design variables. This article examines the accuracy of finite difference derivatives compared with the analytic derivatives, and shows that In some cases it is impossible to obtain any information of value by finite differences. Analytic sensitivities, in this case, are still sufficiently accurate for design optimization.
A hierarchical structured control model was used to describe pilot performance in a multivariable control problem. The model is based on the assumption that a well trained operator optimized a quadratic optimization criterion. The model considers some special characteristics of the human operator as time delay, neuromuscular time lag, observation and motor noise and the ability to extract the first derivative of a displaced value. Numerical results of a simple human engineering example using the BBN model demonstrate the influence of the variation of different parameters on covariance matrices of the state and observation vectors.
Meteorological reanalyses provide multi-year gridded datasets that describe the evolution of the atmosphere. Such products use a data assimilation system, comprising of an atmospheric model, a broad suite of observations, and an analysis system that optimally combines the model forecast with the observations, using an algorithm that includes information about model and data accuracy. The mixture of observations is of central importance to the quality of the assimilated datasets. The Modern-era Retrospective Analysis for Research and Applications (MERRA) included constraints on the thermal structure of the middle atmosphere from nadir sounders on the NOAA polar-orbiting platforms (Stratospheric Sounding Units and Advanced Microwave Sounding Units). These instruments have peak sensitivities that occur well below the stratopause. As such, the radiance measurements do not provide strong constraints on stratopause temperature. The new MERRA-2 reanalysis is using EOS-MLS temperature retrievals after they are available: it will be demonstrated that these data lead to a more realistic stratopause structure in MERRA-2 than in MERRA. Similarly, the work demonstrates the improvements in lower stratospheric ozone in MERRA-2 than in MERRA, for the period when EOS-MLS ozone data are assimilated. This improvement occurs because of the ozone profile information offered by MLS in the low stratosphere, in contrast to the SBUV/2 data used for the rest of MERRA-2. The impacts of choosing to use the EOS-MLS datasets are discussed in context of the continuity of the data record in MERRA- 2.
The approach and techniques described herein define an optimization and evaluation approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system. The method uses Monte Carlo simulations, genetic algorithm solvers, a propulsion thermo-chemical code, power series regression curves for historical data, and statistical models in order to optimize a vehicle system. The system, including parameters for engine chamber pressure, area ratio, and oxidizer/fuel ratio, was modeled and optimized to determine the best design for seven separate design weight and cost cases by varying design and technology parameters. Significant model results show that a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Other key findings show the sensitivity of propulsion parameters, technology factors, and cost factors and how these parameters differ when cost and weight are optimized separately. Each of the three key propulsion parameters; chamber pressure, area ratio, and oxidizer/fuel ratio, are optimized in the seven design cases and results are plotted to show impacts to engine mass and overall vehicle mass.
Although existing CORBA specifications, such as Real-time CORBA and CORBA Messaging, address many end-to-end quality-of service (QoS) properties, they do not define strategies for configuring these properties into applications flexibly, transparently, and adaptively. Therefore, application developers must make these configuration decisions manually and explicitly, which is tedious, error-prone, and open sub-optimal. Although the recently adopted CORBA Component Model (CCM) does define a standard configuration framework for packaging and deploying software components, conventional CCM implementations focus on functionality rather than adaptive quality-of-service, which makes them unsuitable for next-generation applications with demanding QoS requirements. This paper presents three contributions to the study of middleware for QoS-enabled component-based applications. It outlines rejective middleware techniques designed to adaptively (1) select optimal communication mechanisms, (2) manage QoS properties of CORBA components in their contain- ers, and (3) (re)con$gure selected component executors dynamically. Based on our ongoing research on CORBA and the CCM, we believe the application of rejective techniques to component middleware will provide a dynamically adaptive and (re)configurable framework for COTS software that is well-suited for the QoS demands of next-generation applications.
Although existing CORBA specifications, such as Real-time CORBA and CORBA Messaging, address many end-to-end quality-of-service (QoS) properties, they do not define strategies for configuring these properties into applications flexibly, transparently, and adaptively. Therefore, application developers must make these configuration decisions manually and explicitly, which is tedious, error-prone, and often sub-optimal. Although the recently adopted CORBA Component Model (CCM) does define a standard configuration frame-work for packaging and deploying software components, conventional CCM implementations focus on functionality rather than adaptive quality-of service, which makes them unsuitable for next-generation applications with demanding QoS requirements. This paper presents three contributions to the study of middleware for QoS-enabled component-based applications. It outlines reflective middleware techniques designed to adaptively: (1) select optimal communication mechanisms, (2) man- age QoS properties of CORBA components in their containers, and (3) (re)configure selected component executors dynamically. Based on our ongoing research on CORBA and the CCM, we believe the application of reflective techniques to component middleware will provide a dynamically adaptive and (re)configurable framework for COTS software that is well-suited for the QoS demands of next-generation applications.
The well-known stabilizing property of linear quadratic state feedback design is utilized to evaluate the robustness of a linear quadratic feedback design in the presence of modeling errors. Two general conditions are obtained for allowable modeling errors such that the resulting closed-loop system remains stable. One of these conditions is applied to obtain two more particular conditions which are readily applicable to practical situations where a designer has information on the bounds of modeling errors. Relations are established between the allowable parameter uncertainty and the weighting matrices of the quadratic performance index, thereby enabling the designer to select appropriate weighting matrices to attain a robust feedback design.
The Space Transportation System (STS) test program is unique in that it combines flight testing with operational flights using the first operational orbital vehicle (OV-102). The Space Shuttle Orbiter was instrumented to obtain various types of flight data. The instrumentation, designated Development Flight Instrumentation (DFI) includes pressure transducers, thermocouples, calorimeters, and accelerometers. A comparison is conducted between orbiter DFI forward fuselage flight pressure data obtained from OV-102 during the STS-1 reentry, and ground facility data obtained utilizing a 0.04 scale Orbiter forebody model. The comparisons are used to validate the existing experimental data base, optimize the pressure modeling technique, and make possible the refinement of error analysis relative to both. The obtained results indicate, in general, good agreement between flight and ground-based data.
A method for inverting gravitational data is the basis for the present models of Saturn, Jupiter, and Uranus, which have been computed to the third-order in rotational disturbance to the total potential and yield exact matches for recent, highly-accurate determinations of gravitational harmonics for these planets. These results indicate that a major He depletion has either not occurred in the outer layers of Jupiter or of Saturn, or that such a depletion's effect on the density profile has been masked by the presence of denser components. Considerable uncertainty characterizes Uranian models; the one presently preferred has substantial heavy-element enhancement at depth and little ice-rock separation.
Multidisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO.
The NASA Langley Aluminum Testbed Cylinder (ATC) was designed to serve as a universal structure for evaluating structural acoustic codes, modeling techniques and optimization methods used in the prediction of aircraft interior noise. Finite element models were developed for the components of the ATC based on the geometric, structural and material properties of the physical test structure. Numerically predicted modal frequencies for the longitudinal stringer, ring frame and dome component models, and six assembled ATC configurations were compared with experimental modal survey data. The finite element models were updated and refined, using physical parameters, to increase correlation with the measured modal data. Excellent agreement, within an average 1.5% to 2.9%, was obtained between the predicted and measured modal frequencies of the stringer, frame and dome components. The predictions for the modal frequencies of the assembled component Configurations I through V were within an average 2.9% and 9.1%. Finite element modal analyses were performed for comparison with 3 psi and 6 psi internal pressurization conditions in Configuration VI. The modal frequencies were predicted by applying differential stiffness to the elements with pressure loading and creating reduced matrices for beam elements with offsets inside external superelements. The average disagreement between the measured and predicted differences for the 0 psi and 6 psi internal pressure conditions was less than 0.5%. Comparably good agreement was obtained for the differences between the 0 psi and 3 psi measured and predicted internal pressure conditions.
The NASA Langley Aluminum Testbed Cylinder (ATC) was designed to serve as a universal structure for evaluating structural acoustic codes, modeling techniques and optimization methods used in the prediction of aircraft interior noise. Finite element models were developed for the components of the ATC based on the geometric, structural and material properties of the physical test structure. Numerically predicted modal frequencies for the longitudinal stringer, ring frame and dome component models, and six assembled ATC arrangements were in good agreement with experimental modal survey data. Finite element modal analyses were performed for 3 psi and 6 psi internal pressurization conditions. Acoustic cylinder modes for the interior of the ATC were calculated with an acoustic finite element model. Frequency transfer functions between a unit force on the structure and the acoustic response inside the ATC cylinder were measured and were compared with predictions based on a boundary element model. Comparisons between predicted and experimental results are presented and discussed.
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A long-standing problem in NASA is how to allocate scarce technology development resources across advanced technologies in order to best support a large set of future potential missions. Within NASA, two orthogonal paradigms have received attention in recent years: the real-options approach and the broad mission model approach. This paper focuses on the latter.
The concept for Highly Reliable Reusable Launch Systems (HRRLS) under the NASA Hypersonics project is a two-stage-to-orbit, horizontal-take-off / horizontal-landing, (HTHL) architecture with an air-breathing first stage. The first stage vehicle is a slender body with an air-breathing propulsion system that is highly integrated with the airframe. The light weight slender body will deflect significantly during flight. This global deflection affects the flow over the vehicle and into the engine and thus the loads and moments on the vehicle. High-fidelity multi-disciplinary analyses that accounts for these fluid-structures-thermal interactions are required to accurately predict the vehicle loads and resultant response. These predictions of vehicle response to multi physics loads, calculated with fluid-structural-thermal interaction, are required in order to optimize the vehicle design over its full operating range. This contract with ResearchSouth addresses one of the primary objectives of the Vehicle Technology Integration (VTI) discipline: the development of high-fidelity multi-disciplinary analysis and optimization methods and tools for HRRLS vehicles. The primary goal of this effort is the development of an integrated software system that can be used for full-vehicle optimization. This goal was accomplished by: 1) integrating the master code, FEMAP, into the multidiscipline software network to direct the coupling to assure accurate fluid-structure-thermal interaction solutions; 2) loosely-coupling the Euler flow solver FEFLO to the available and proven aeroelasticity and large deformation (FEAP) code; 3) providing a coupled Euler-boundary layer capability for rapid viscous flow simulation; 4) developing and implementing improved Euler/RANS algorithms into the FEFLO CFD code to provide accurate shock capturing, skin friction, and heat-transfer predictions for HRRLS vehicles in hypersonic flow, 5) performing a Reynolds-averaged Navier-Stokes computation on an HRRLS configuration; 6) integrating the RANS solver with the FEAP code for coupled fluid-structure-thermal capability; and 7) integrating the existing NASA SRGULL propulsion flow path prediction software with the FEFLO software for quasi-3D propulsion flow path predictions, 8) improving and integrating into the network, an existing adjoint-based design optimization code.
The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.