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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Design for steering accuracy in antenna arrays using shared optical phase shifters

Uniform linear phased arrays where many radiating elements share a relatively small number of phase shifters are investigated. Such architectures arise in arrays which derive the time delays in the signal paths from a small group of independent phase shifters. In particular, a true time-delay device which has been suggested recently for optically controlled arrays is used as the basic phase shifter. Different architectures, viz. alternative procedures of deriving the necessary time delay for each antenna in the face of phase-shifter inaccuracies, are examined. The variance of the steered beam's direction is used as the performance criterion. The direction-optimal architecture is obtained by means of quadratic programming, and is shown not to be unique. The nonuniqueness of the optimal architecture is exploited to improve other characteristics of the array's beam shape, and the optimal solution is shown to compare favorably with a suboptimal interleaved solution which is easier to implement.

Kam, Moshe↗
NASA NTRS1998

Evaluation and optimization of lidar temperature analysis algorithms using simulated data

The middle atmosphere (20 to 90 km altitude) ha received increasing interest from the scientific community during the last decades, especially since such problems as polar ozone depletion and climatic change have become so important. Temperature profiles have been obtained in this region using a variety of satellite-, rocket-, and balloon-borne instruments as well as some ground-based systems. One of the more promising of these instruments, especially for long-term high resolution measurements, is the lidar. Measurements of laser radiation Rayleigh backscattered, or Raman scattered, by atmospheric air molecules can be used to determine the relative air density profile and subsequently the temperature profile if it is assumed that the atmosphere is in hydrostatic equilibrium and follows the ideal gas law. The high vertical and spatial resolution make the lidar a well adapted instrument for the study of many middle atmospheric processes and phenomena as well as for the evaluation and validation of temperature measurements from satellites, such as the Upper Atmosphere Research Satellite (UARS). In the Network for Detection of Stratospheric Change (NDSC) lidar is the core instrument for measuring middle atmosphere temperature profiles. Using the best lidar analysis algorithm possible is therefore of crucial importance. In this work, the JPL and CNRS/SA lidar analysis software were evaluated. The results of this evaluation allowed the programs to be corrected and optimized and new production software versions were produced. First, a brief description of the lidar technique and the method used to simulate lidar raw-data profiles from a given temperature profile is presented. Evaluation and optimization of the JPL and CNRS/SA algorithms are then discussed.

Leblanc, Thierry↗
NASA NTRS1994

Thermal/Structural Tailoring of Engine Blades (T/STAEBL) User's manual

The Thermal/Structural Tailoring of Engine Blades (T/STAEBL) system is a computer code that is able to perform numerical optimizations of cooled jet engine turbine blades and vanes. These optimizations seek an airfoil design of minimum operating cost that satisfies realistic design constraints. This report documents the organization of the T/STAEBL computer program, its design and analysis procedure, its optimization procedure, and provides an overview of the input required to run the program, as well as the computer resources required for its effective use. Additionally, usage of the program is demonstrated through a validation test case.

Brown, K. W.↗
NASA NTRS1988

Structural Tailoring of Advanced Turboprops (STAT)

This interim report describes the progress achieved in the structural Tailoring of Advanced Turboprops (STAT) program which was developed to perform numerical optimizations on highly swept propfan blades. The optimization procedure seeks to minimize an objective function, defined as either direct operating cost or aeroelastic differences between a blade and its scaled model, by tuning internal and external geometry variables that must satisfy realistic blade design constraints. This report provides a detailed description of the input, optimization procedures, approximate analyses and refined analyses, as well as validation test cases for the STAT program. In addition, conclusions and recommendations are summarized.

Brown, Kenneth W.↗
NASA NTRS1975

Precision orbit raising trajectories

A precision trajectory program has been developed to serve as a test bed for geocentric orbit raising steering laws. The steering laws to be evaluated have been developed using optimization methods employing averaging techniques. This program provides the capability of testing the steering laws in a precision simulation. The principal system models incorporated in the program are described, including the radiation environment, the solar array model, the thrusters and power processors, the geopotential, and the solar system. Steering and array orientation constraints are discussed, and the impact of these constraints on program design is considered.

Flanagan, P. F.↗
NASA NTRS1989

Integrated aerodynamic/dynamic optimization of helicopter rotor blades

An integrated aerodynamic/dynamic optimization procedure is used to minimize blade weight and 4 per rev vertical hub shear for a rotor blade in forward flight. The coupling of aerodynamics and dynamics is accomplished through the inclusion of airloads which vary with the design variables during the optimization process. Both single and multiple objective functions are used in the optimization formulation. The Global Criteria Approach is used to formulate the multiple objective optimization and results are compared with those obtained by using single objective function formulations. Constraints are imposed on natural frequencies, autorotational inertia, and centrifugal stress. The program CAMRAD is used for the blade aerodynamic and dynamic analyses, and the program CONMIN is used for the optimization. Since the spanwise and the azimuthal variations of loading are responsible for most rotor vibration and noise, the vertical airload distributions on the blade, before and after optimization, are compared. The total power required by the rotor to produce the same amount of thrust for a given area is also calculated before and after optimization. Results indicate that integrated optimization can significantly reduce the blade weight, the hub shear and the amplitude of the vertical airload distributions on the blade and the total power required by the rotor.

Chattopadhyay, Aditi↗
DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Structural optimization via a design space hierarchy

Mathematical programming techniques provide a general approach to automated structural design. An iterative method is proposed in which design is treated as a hierarchy of subproblems, one being locally constrained and the other being locally unconstrained. It is assumed that the design space is locally convex in the case of good initial designs and that the objective and constraint functions are continuous, with continuous first derivatives. A general design algorithm is outlined for finding a move direction which will decrease the value of the objective function while maintaining a feasible design. The case of one-dimensional search in a two-variable design space is discussed. Possible applications are discussed. A major feature of the proposed algorithm is its application to problems which are inherently ill-conditioned, such as design of structures for optimum geometry.

Vanderplaats, G. N.↗
NASA NTRS1987

Optimization methods applied to the aerodynamic design of helicopter rotor blades

Described is a formal optimization procedure for helicopter rotor blade design which minimizes hover horsepower while assuring satisfactory forward flight performance. The approach is to couple hover and forward flight analysis programs with a general-purpose optimization procedure. The resulting optimization system provides a systematic evaluation of the rotor blade design variables and their interaction, thus reducing the time and cost of designing advanced rotor blades. The paper discusses the basis for and details of the overall procedure, describes the generation of advanced blade designs for representative Army helicopters, and compares design and design effort with those from the conventional approach which is based on parametric studies and extensive cross-plots.

Walsh, Joanne L.↗
NASA NTRS1976

Fire resistant resilient foams

Primary program objectives were the formulation, screening, optimization and characterization of open-cell, fire resistant, low-smoke emitting, thermally stable, resilient polyimide foams suitable for seat cushions in commercial aircraft and spacecraft. Secondary program objectives were to obtain maximum improvement of the tension, elongation and tear characteristics of the foams, while maintaining the resiliency, thermal stability, low smoke emission and other desirable attributes of these materials.

Gagliani, J.↗
NASA NTRS1980

Structural sizing considerations for large space platforms

Structural optimization studies are made using mathematical programming techniques to examine minimum mass structural proportions of deployable and erectable tetrahedral truss platforms subject to the integrated effects of practical design requirements. Considerations integrated into the optimization process are: 1) lowest natural frequencies of the platform and individual platform components (struts); 2) packaging constraints imposed by the Shuttle cargo bay capacity; 3) initial curvature of the struts; 4) column buckling of the struts due to gravity gradient, orbital transfer, strut length tolerance, or design loads; and 5) practical lower limits for strut diameter and wall thickness. Ultra-low mass designs are shown to be possible with strut proportions much more slender than those conventionally used for earthbound application.

Heard, W. L., Jr.↗
NASA NTRS1971

Computer-aided linear-circuit design.

Usually computer-aided design (CAD) refers to programs that analyze circuits conceived by the circuit designer. Among the services such programs should perform are direct network synthesis, analysis, optimization of network parameters, formatting, storage of miscellaneous data, and related calculations. The program should be embedded in a general-purpose conversational language such as BASIC, JOSS, or APL. Such a program is MARTHA, a general-purpose linear-circuit analyzer embedded in APL.

Penfield, P.↗
DOE OSTI2024

Metric Learning to Accelerate Convergence of Operator Splitting Methods

Recent developments in machine learning have led to promising advances in accelerating the solution of constrained optimization problems. Increasing demand for real-time decision-making capabilities in applications such as artificial intelligence and optimal control has led to a variety of proposed strategies for learning to produce fast solutions to optimization problems. For example, recent works have shown that it is possible to accelerate the convergence of optimization algorithms by learning to select their parameters, such as gradient descent stepsizes. This work proposes a new approach, in which the underlying metric spaces of proximal operator splitting algorithms are learned to maximize convergence rate. While prior works in optimization theory have derived optimal metrics in simple cases, no such result exists for many practical problem forms including general Quadratic Programming (QP). This paper shows how differentiable optimization can enable the end-to-end learning of proximal metrics, enhancing the convergence of proximal algorithms for QP problems beyond what is possible based on known theory. Additionally, the results illustrate a strong connection between the learned proximal metrics and active constraints at the optima, leading to an interpretation in which the predicted proximal metrics can be viewed as a form of active set prediction.

King, Ethan [BATTELLE (PACIFIC NW LAB)]↗
NASA NTRS2014

Property Differencing for Incremental Checking

This paper introduces iProperty, a novel approach that facilitates incremental checking of programs based on a property di erencing technique. Speci cally, iProperty aims to reduce the cost of checking properties as they are initially developed and as they co-evolve with the program. The key novelty of iProperty is to compute the di erences between the new and old versions of expected properties to reduce the number and size of the properties that need to be checked during the initial development of the properties. Furthermore, property di erencing is used in synergy with program behavior di erencing techniques to optimize common regression scenarios, such as detecting regression errors or checking feature additions for conformance to new expected properties. Experimental results in the context of symbolic execution of Java programs annotated with properties written as assertions show the e ectiveness of iProperty in utilizing change information to enable more ecient checking.

Yang, Guowei↗
DOE OSTI2024

Transforming Science Through Software: Improving While Delivering 100×

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Solar, Wind, and Load Forecasting Dataset for MISO, NYISO, and SPP Balancing Areas

The Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program is an initiative intended to foster "a fundamental shift in grid management rooted in an understanding of asset risk and system risk" (ARPA-E 2020). Launched by the Advanced Research Projects Agency-Energy (ARPA-E), the program supports efforts to incorporate uncertainty in electric power decision making. In support of PERFORM, the National Renewable Energy Laboratory (NREL) has produced a set of time-coincident forecasts of solar, wind, and load profiles. As part of Phase I of the PERFORM effort, NREL created a dataset that consists of one year of time-coincident load, wind, and solar actuals and probabilistic forecasts based on data from the Electric Reliability Council of Texas (ERCOT) (Bryce et al. 2023). In Phase II, NREL developed similar datasets for three other U.S. Independent System Operators (ISO): the Midcontinent Independent System Operator (MISO), the New York Independent System Operator (NYISO), and the Southwest Power Pool (SPP).

24 POWER TRANSMISSION AND DISTRIBUTION↗