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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

ADS: A FORTRAN program for automated design synthesis, version 1.00

A new general-purpose optimization program for engineering design is described. ADS-1 (Automated Design Synthesis - Version 1) is a FORTRAN program for solution of nonlinear constrained optimization problems. The program is segmented into three levels, being strategy, optimizer, and one-dimensional search. At each level, several options are available so that a total of over 100 possible combinations can be created. Examples of available strategies are sequential unconstrained minimization, the Augmented Lagrange Multiplier method, and Sequential Linear Programming. Available optimizers include variable metric methods and the Method of Feasible Directions as examples and one-dimensional search options include polynomial interpolation and the Golden Section method as examples. Emphasis is placed on ease of use of the program. All information is transferred via a single parameter list. Default values are provided for all internal program parameters such as convergence criteria, and the user is given a simple means to over-ride these, if desired. The program is demonstrated with a simple structural design example.

Vanderplaats, G. N.↗
NASA NTRS1990

An averaging approach to optimal adaptive control of large space structures

Averaging methods are applied to analyzing the transient response associated with adaptive control of large space structures. Using a dominant mode approximation to the plant, an analytical bound is found on the envelope of the adaptive response, characterizing many of the features of the response useful for control design (e.g., peak values, quadratic costs, settling times, etc.). An optimal adaptive design problem is formulated based on minimizing the product of the settling time and peak torque requirement. The resulting nonlinear constrained optimization problem is solved in closed form, and several properties of the optimal adaptive design are discussed.

Bayard, D. S.↗
NASA NTRS1972

Optimal filter design subject to output delobe constraints

The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and Duality Theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures. A convergent algorithm is presented for computational solution of the dual problem.

Fortmann, T. E.↗
NASA NTRS1974

Optimal filter design subject to output sidelobe constraints - Theoretical considerations

The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and duality theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures.

Fortmann, T. E.↗
DOE OSTI2025

Valued peaks: Sustainable water allocation for small hydropower plants in an era of explicit ecological needs

Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.

13 HYDRO ENERGY↗
NASA NTRS1987

Alternative methods for calculating sensitivity of optimized designs to problem parameters

Optimum sensitivity is defined as the derivative of the optimum design with respect to some problem parameter, P. The problem parameter is usually fixed during optimization, but may be changed later. Thus, optimum sensitivity is used to estimate the effect of changes in loads, materials or constraint bounds on the design without expensive re-optimization. Here, the general topic of optimum sensitivity is discussed, available methods identified, examples given, and the difficulties encountered in calculating this information in nonlinear constrained optimization are identified.

Vanderplaats, G. N.↗
NASA NTRS1991

Trajectory optimization and guidance for a hypersonic vehicle

The optimal ascent problem for a hypersonic vehicle is formulated as an inverse dynamic problem. This formulation is essential in solving the trajectory optimization problem via the nonlinear programming approach. Both minimum-fuel and minimax type of performance indices are considered. The results reveal important features of the optimal trajectory and controls, and they are subsequently used to construct a nonlinear feedback midcourse control law. This control law not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suitable for onboard implementation. Finally, off-nominal trajectory guidance is addressed using combination of feedback compensation and onboard generation of control through the inverse dynamics approach.

Lu, Ping↗
NASA NTRS1985

A method to stabilize linear systems using eigenvalue gradient information

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

Wieseman, C. D.↗
NASA NTRS1989

CONSOLE: A CAD tandem for optimization-based design interacting with user-supplied simulators

CONSOLE employs a recently developed design methodology (International Journal of Control 43:1693-1721) which provides the designer with a congenial environment to express his problem as a multiple ojective constrained optimization problem and allows him to refine his characterization of optimality when a suboptimal design is approached. To this end, in CONSOLE, the designed formulates the design problem using a high-level language and performs design task and explores tradeoff through a few short and clearly defined commands. The range of problems that can be solved efficiently using a CAD tools depends very much on the ability of this tool to be interfaced with user-supplied simulators. For instance, when designing a control system one makes use of the characteristics of the plant, and therefore, a model of the plant under study has to be made available to the CAD tool. CONSOLE allows for an easy interfacing of almost any simulator the user has available. To date CONSOLE has already been used successfully in many applications, including the design of controllers for a flexible arm and for a robotic manipulator and the solution of a parameter selection problem for a neural network.

Fan, Michael K. H.↗
NASA NTRS1991

Exact and explicit optimal solutions for trajectory planning and control of single-link flexible-joint manipulators

An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.

Chen, Guanrong↗
NASA NTRS1991

Sensitivity of Space Station Alpha Joint robust controller to structural modal parameter variations

The baseline design of the photovoltaic-array sun-tracking control system is presented with special attention given to the optimization of design variables related to stability and performance. The procedures utilized to attenuate control/structure interaction are described, and controller sensitivity to variations in structural modal parameters is examined. Constrained optimization techniques determine the stability margin and tracking capability, which are then tested for sensitivity to variations in natural frequency, mode-shape amplitudes, and modal-damping ratios. The effect of variations in the modal parameters of the dominant modes on performance indicators is also examined to optimize tracking-performance responsiveness and satisfy the design requirements. It is concluded that accurate on-orbit modal data are necessary to make the reoptimization procedure effective in improving the performance of the control system.

Kumar, Renjith R.↗
NASA NTRS2017

Reconfigurable Cellular Composite Structures for Lighter than Air Vehicles with Scalable Size and Endurance

Engineered non-stochastic cellular materials show promising characteristics on the laboratory scale,with nearly ideal specific stiffness and strength scaling at ultralight mass density. These propertiessuggest performance benefits in any application with combined stiffness and mass constraints, suchas air vehicles. We investigate here the application of re-configurable cellular composite materialsand structures to lighter than air vehicles. We describe the properties and applicability of these materials,provide an example analysis of governing loading conditions associated with airships, showan example optimization method for navigating the design space, and describe how recent advancesin cellular material manufacturing and reconfiguration enable system performance benefits includingnew concepts of operation. Lastly, we propose lighter than air vehicles that are assembled andmaintained in-flight, eliminating structural compromises associated with transitional flight modesand ground handling.Engineered non-stochastic cellular material properties suggest performance benefits in lighter than air vehicles due tostiffness and mass constraints that are intrinsic to the airship design problem. Recent advances in cellular materialmanufacturing and reconfiguration enable system performance benefits including new concepts of operation, such aslighter than air vehicles that are assembled and maintained in-flight, eliminating structural compromises associatedwith transitional flight modes and ground handling. Existing engineered cellular materials display properties allowinglarge large scale airships design as monocoque cellular solids. Inevitable improvements in cellular material propertiesand manufacturing will improve feasibility even further. Given the suggestion that the two most significant technologygaps exist across all current airship projects are manufacturing and assembly processes and ground handling [7],a strategy that encompasses construction and maintenance in flight could provide critical rephrasing of the systemdesign problem through these new concepts of operation. Refactoring of traditional manufacturing, operation, andservice process constraints could extend to other domains in aerospace systems and manufacturing in general.In future work, the complexity of the design task would benefit from a form of optimization in order to find themost suitable geometry for a chosen application. For example, the Sequential Least SQuares Programming (SLSQP)function from within the SciPy Minimize library is a multiobjective constrained optimization method that has beenapplied to fixed wing aircraft design. [17] In this situation it would allow for several objective functions such as drag,bending stiffness, buoyancy and cost of transport to be incorporated into a composite objective function.

Copplestone, Grace↗
NASA NTRS2002

A Method for Optimizing Non-Axisymmetric Liners for Multimodal Sound Sources

Central processor unit times and memory requirements for a commonly used solver are compared to that of a state-of-the-art, parallel, sparse solver. The sparse solver is then used in conjunction with three constrained optimization methodologies to assess the relative merits of non-axisymmetric versus axisymmetric liner concepts for improving liner acoustic suppression. This assessment is performed with a multimodal noise source (with equal mode amplitudes and phases) in a finite-length rectangular duct without flow. The sparse solver is found to reduce memory requirements by a factor of five and central processing time by a factor of eleven when compared with the commonly used solver. Results show that the optimum impedance of the uniform liner is dominated by the least attenuated mode, whose attenuation is maximized by the Cremer optimum impedance. An optimized, four-segmented liner with impedance segments in a checkerboard arrangement is found to be inferior to an optimized spanwise segmented liner. This optimized spanwise segmented liner is shown to attenuate substantially more sound than the optimized uniform liner and tends to be more effective at the higher frequencies. The most important result of this study is the discovery that when optimized, a spanwise segmented liner with two segments gives attenuations equal to or substantially greater than an optimized axially segmented liner with the same number of segments.

Watson, W. R.↗
NASA NTRS1985

The Construction of Curves and Surfaces Using Numerical Optimization Techniques

Numerical optimization techniques are playing an increasing role in curve and surface construction. Often difficult problems in curve and surface construction, especially when some aspect of shape control is involved, can be phrased as a constrained optimization problem. Four such classes of problems are explored: parametric curve fitting with non-linear shape constraints; explicit surface fitting with linear shape constraints; surface fitting to scattered data giving rise to ill-posed problems; finally, variable knot problems. In each of these problems there is a nonlinear aspect: either the shape of the curve or surface is important for manufacturing or engineering reasons or the shape affects the convergence of numerical algorithms which use the curve or surface or the placement of knots affects the accuracy of the fits. In all cases the class of functions used is that of parametric spline curves and tensor or direct product spline surfaces. The reason for choosing this class is that splines provide flexible models that are easily evaluated and stored. Furthermore, the B-spline representation of splines leads to convenient expressions for shape control over regions.

Ferguson, D. R.↗
NASA NTRS1992

Optimization by nonhierarchical asynchronous decomposition

Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. The algorithm is carefully analyzed for quadratic programs, and a number of modifications are suggested to improve its robustness.

Shankar, Jayashree↗
NASA NTRS2013

Real-Time Optimization for use in a Control Allocation System to Recover from Pilot Induced Oscillations

Integration of the Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) System into the control system of a Short Takeoff and Landing Mobility Concept Vehicle simulation presents a challenge because the CAPIO formulation requires that constrained optimization problems be solved at the controller operating frequency. We present a solution that utilizes a modified version of the well-known L-BFGS-B solver. Despite the iterative nature of the solver, the method is seen to converge in real time with sufficient reliability to support three weeks of piloted runs at the NASA Ames Vertical Motion Simulator (VMS) facility. The results of the optimization are seen to be excellent in the vast majority of real-time frames. Deficiencies in the quality of the results in some frames are shown to be improvable with simple termination criteria adjustments, though more real-time optimization iterations would be required.

optimal control↗
NASA NTRS1991

Least squares restoration of multichannel images

Multichannel restoration using both within- and between-channel deterministic information is considered. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images yield suboptimal results when applied to multichannel images, since between-channel information is not utilized. Multichannel least squares restoration filters are developed using the set theoretic and the constrained optimization approaches. A geometric interpretation of the estimates of both filters is given. Color images (three-channel imagery with red, green, and blue components) are considered. Constraints that capture the within- and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. A spatially adaptive, multichannel least squares filter that utilizes local within- and between-channel image properties is proposed. Experiments using color images are described.

Galatsanos, Nikolas P.↗
NASA NTRS2000

Analytical and Computational Aspects of Collaborative Optimization

Bilevel problem formulations have received considerable attention as an approach to multidisciplinary optimization in engineering. We examine the analytical and computational properties of one such approach, collaborative optimization. The resulting system-level optimization problems suffer from inherent computational difficulties due to the bilevel nature of the method. Most notably, it is impossible to characterize and hence identify solutions of the system-level problems because the standard first-order conditions for solutions of constrained optimization problems do not hold. The analytical features of the system-level problem make it difficult to apply conventional nonlinear programming algorithms. Simple examples illustrate the analysis and the algorithmic consequences for optimization methods. We conclude with additional observations on the practical implications of the analytical and computational properties of collaborative optimization.

Alexandrov, Natalia M.↗