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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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At least 397 records · Page 22

Turbulence control on an airborne laser platform

An active flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time and then release all of the flow instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. A flat plate towed in a water channel is used as a test bed. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, it is shown that the cyclic jet will produce periodic structures that are similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall of the plate. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗

Turbulence control on airborne laser platform

An avctive flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A flat plate towed in a water channel is used as a test bed. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time during its 'on' period. When the jet is turned 'off', all of the turbulent fluid is released instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, the cyclic jet produces periodic structures that are qualitatively similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗

PDEMOD: Software for control/structures optimization

Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.

Taylor, Lawrence W., Jr.↗

Antenna pattern control using impedence surfaces

During this research period, September 16, 1990 to March 15, 1991, a design method for selecting a low-loss impedance material coating for a horn antenna pattern control has been developed. This method and the stepped waveguide technique can be employed to accurately compute the electromagnetic wave phenomenon inside the transition region of the horn antenna, with or without the impedance surfaces, from the feed to the radiating aperture. For moment method solutions of the electric and magnetic current distributions on the radiating aperture and the outer surface of the horn antenna, triangular surface-patch modes are introduced to replace the sinusoidal surface-patch modes as expansion and testing functions to provide a more physical expansion of the current distributions. In the synthesis problem, a numerical optimization process is formulated to minimize the error function between the desired waveguide modes and the modes provided by the horn transition with impedance surfaces. Since the modes generated by the horn transition with impedance surface are computed by analytical techniques, the computational error involved in the synthesis of the antenna pattern is minimum. Therefore, the instability problem can be avoided. A preliminary implementation of the techniques has demonstrated that the developed theory of the horn antenna pattern control using the impedance surfaces is realizable.

Balanis, Constantine A.↗

NEP systems model

A new nuclear electric propulsion (NEP) systems analysis code is discussed. The new code is modular and consists of a driver code and various subsystem models. The code models five different subsystems: (1) reactor/shield; (2) power conversion; (3) heat rejection; (4) power management and distribution (PMAD); and (5) thrusters. The code optimizes for the following design criteria: minimum mass; minimum radiator area; and low mass/low area. The code also optimizes the following parameters: separation distance; temperature ratio; pressure ratio; and transmission frequency. The discussion is presented in vugraph form.

George, Jeffrey A.↗

PROFILE: Airfoil Geometry Manipulation and Display

This report provides user information for program PROFILE, an aerodynamics design utility for plotting, tabulating, and manipulating airfoil profiles. A dozen main functions are available. The theory and implementation details for two of the more complex options are also presented. These are the REFINE option, for smoothing curvature in selected regions while retaining or seeking some specified thickness ratio, and the OPTIMIZE option, which seeks a specified curvature distribution. Use of programs QPLOT and BPLOT is also described, since all of the plots provided by PROFILE (airfoil coordinates, curvature distributions, pressure distributions)) are achieved via the general-purpose QPLOT utility. BPLOT illustrates (again, via QPLOT) the shape functions used by two of PROFILE's options. These three utilities should be distributed as one package. They were designed and implemented for the Applied Aerodynamics Branch at NASA Ames Research Center, Moffett Field, California. They are all written in FORTRAN 77 and run on DEC and SGI systems under OpenVMS and IRIX.

Collins, Leslie↗

Enhancement of Nucleate Boiling Heat Flux on Macro/Micro-Structured Surfaces Cooled by Multiple Impinging Jets

An experimental investigation of nucleate boiling heat transfer from modified surfaces cooled by multiple in-line impinging circular jets is reported and found to agree with single jet results. A copper block is heated from the back by two electrical arcs, and cooled on the opposite side by three identical liquid jets of distilled water at subcoolings of 25 C 50 C and 77 C and Freon 113 at 24 C subcooling. Liquid flow rates are held constant at 5, 10, and 15 GPH for each of the three jets with jet velocities ranging from 1.4 m/s to 1 1.2 m/s and jet diameters from 0.95 mm to 2.2 mm. To increase the maximum heat flux (CHF) and heat removal rate, the boiling surface was modified by both macro and micro enhancements. Macro modification consists of machined radial grooves in the boiling surface arranged in an optimally designed pattern to allow better liquid distribution along the surface. These grooves also reduce splashing of liquid droplets, and provide 'channels' to sweep away bubbles. Micro modification was achieved by flame spraying metal powder on the boiling surface, creating a porous, sintered surface. With the addition of both micro and macro structured enhancements, maximum heat flux and nucleate boiling can be enhanced by more than 200%. Examination of each surface modification separately and together indicates that at lower superheats, the micro structure provides the enhanced heat transfer by providing more nucleation sites, while for higher superheats the macro structure allows better liquid distribution and bubble removal. A correlation is presented to account for liquid subcoolings and surface enhancements, in addition to the geometrical and fluid properties previously reported in the literature.

Kugler, Scott Lee↗

In-Space Radiator Shape Optimization using Genetic Algorithms

Future space exploration missions will require the development of more advanced in-space radiators. These radiators should be highly efficient and lightweight, deployable heat rejection systems. Typical radiators for in-space heat mitigation commonly comprise a substantial portion of the total vehicle mass. A small mass savings of even 5-10% can greatly improve vehicle performance. The objective of this paper is to present the development of detailed tools for the analysis and design of in-space radiators using evolutionary computation techniques. The optimality criterion is defined as a two-dimensional radiator with a shape demonstrating the smallest mass for the greatest overall heat transfer, thus the end result is a set of highly functional radiator designs. This cross-disciplinary work combines topology optimization and thermal analysis design by means of a genetic algorithm The proposed design tool consists of the following steps; design parameterization based on the exterior boundary of the radiator, objective function definition (mass minimization and heat loss maximization), objective function evaluation via finite element analysis (thermal radiation analysis) and optimization based on evolutionary algorithms. The radiator design problem is defined as follows: the input force is a driving temperature and the output reaction is heat loss. Appropriate modeling of the space environment is added to capture its effect on the radiator. The design parameters chosen for this radiator shape optimization problem fall into two classes, variable height along the width of the radiator and a spline curve defining the -material boundary of the radiator. The implementation of multiple design parameter schemes allows the user to have more confidence in the radiator optimization tool upon demonstration of convergence between the two design parameter schemes. This tool easily allows the user to manipulate the driving temperature regions thus permitting detailed design of in-space radiators for unique situations. Preliminary results indicate an optimized shape following that of the temperature distribution regions in the "cooler" portions of the radiator. The results closely follow the expected radiator shape.

Hull, Patrick V.↗

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design

UQ↗

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design.

UQ↗

Air data system optimization using a genetic algorithm

An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.

Deshpande, Samir M.↗

Deconflicting Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace

North Atlantic oceanic airspace accommodates more than 1000 flights daily, and is subjected to very strong winds. Flying wind-optimal trajectories yields time and fuel savings for each individual flight. However, when taken together, these trajectories induce a large amount of potential en-route conflicts. This paper analyses the detected conflicts, figuring out conflict distribution in time and space. It further describes an optimization algorithm aimed at reducing the number of conflicts for a daily set of flights on strategic level. Several trajectory modification strategies are discussed, followed with simulation results. Finally, an algorithm improvement is presented aiming at better preserving the trajectory optimality.

wind-optimal trajectories↗

Chance-Constrained Guidance With Non-Convex Constraints

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of failure) is below a user-specified bound known as the risk bound. An example problem is to drive a car to a destination as fast as possible while limiting the probability of an accident to 10(exp -7). This framework allows users to trade conservatism against performance by choosing the risk bound. The more risk the user accepts, the better performance they can expect.

FROM↗

SURE (Science User Resource Expert): A science planning and scheduling assistant for a resource based environment

SURE (Science User Resource Expert) is one of three components that compose the SURPASS (Science User Resource Planning and Scheduling System). This system is a planning and scheduling tool which supports distributed planning and scheduling, based on resource allocation and optimization. Currently SURE is being used within the SURPASS by the UARS (Upper Atmospheric Research Satellite) SOLSTICE instrument to build a daily science plan and activity schedule and in a prototyping effort with NASA GSFC to demonstrate distributed planning and scheduling for the SOLSTICE II instrument on the EOS platform. For the SOLSTICE application the SURE utilizes a rule-based system. Development of a rule-based program using Ada CLIPS as opposed to using conventional programming, allows for capture of the science planning and scheduling heuristics in rules and provides flexibility in inserting or removing rules as the scientific objectives and mission constraints change. The SURE system's role as a component in the SURPASS, the purpose of the SURE planning and scheduling tool, the SURE knowledge base, and the software architecture of the SURE component are described.

Thalman, Nancy E.↗

Masked Proportional Routing

Masked proportional routing is an improved procedure for choosing links between adjacent nodes of a network for the purpose of transporting an entity from a source node ("A") to a destination node ("B"). The entity could be, for example, a physical object to be shipped, in which case the nodes would represent waypoints and the links would represent roads or other paths between waypoints. For another example, the entity could be a message or packet of data to be transmitted from A to B, in which case the nodes could be computer-controlled switching stations and the links could be communication channels between the stations. In yet another example, an entity could represent a workpiece while links and nodes could represent, respectively, manufacturing processes and stages in the progress of the workpiece towards a finished product. More generally, the nodes could represent states of an entity and the links could represent allowed transitions of the entity. The purpose of masked proportional routing and of related prior routing procedures is to schedule transitions of entities from their initial states ("A") to their final states ("B") in such a manner as to minimize a cost or to attain some other measure of optimality or efficiency. Masked proportional routing follows a distributed (in the sense of decentralized) approach to probabilistically or deterministically choosing the links. It was developed to satisfy a need for a routing procedure that 1. Does not always choose the same link(s), even for two instances characterized by identical estimated values of associated cost functions; 2. Enables a graceful transition from one set of links to another set of links as the circumstances of operation of the network change over time; 3. Is preferably amenable to separate optimization of different portions of the network; 4. Is preferably usable in a network in which some of the routing decisions are made by one or more other procedure(s); 5. Preferably does not cause an entity to visit the same node twice; and 6. Preferably can be modified so that separate entities moving from A to B do not arrive out of order.

Wolpert, David↗

Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems; Workshop Report

The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.

Braverman, Amy↗

Use of the Collaborative Optimization Architecture for Launch Vehicle Design

Collaborative optimization is a new design architecture specifically created for large-scale distributed-analysis applications. In this approach, problem is decomposed into a user-defined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a system-level coordination process. This decentralized design strategy allows domain-specific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a single-stage-to-orbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 5 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influence which an priori ascent-abort criterion has on development cost. Similarly, objective-function selection is discussed, demonstrating the difference between minimum weight and minimum cost concepts. The operational advantages of the collaborative optimization

Braun, R. D.↗

Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

Reuther, James↗