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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Improved Nystrom Integrators

New formulation for Nystrom integrators offers increased precision and speed of computation. Formulation takes advantage of capabilities of modern electronic computers. Independent and dependent variables and various partial and total derivatives expressed via compact tensor notation. In this approach, typical set of constraint equations derived in about 1 day. Solution of constraint equations speeded by SEARCH computer program. Is general-purpose optimization program, which maximizes or minimizes cost function defined by user. Used successfully, to make least-squares fit of about 4,000 equations in 12 unknowns.

Lear, William M.↗
DOE OSTI2016

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Wang, Bin↗
NASA NTRS1968

Computer program for parameter optimization

Flexible, large scale digital computer program was designed for the solution of a wide range of multivariable parameter optimization problems. The program has the ability to solve constrained optimization problems involving up to one hundred parameters.

Glatt, C. R.↗
DOE OSTI2013

Michigan: Michigan's Clean Energy Resources and Economy [Brochure]

By harnessing its abundant supply of conventional hydroelectric power, biomass, and wind, Michigan is well on its way to meeting its goal, set by the 2008 Clean Renewable and Efficient Energy Act, of generating 10% of retail electricity from renewable sources by 2015. Renewable biomass accounted for 39% of renewable energy credits certified in Michigan between 2009 and 2011, thanks in part to Michigan’s 19 million acres of forest land. Small hydroelectric plants, landfill gas, and municipal solid waste are all important sources of renewable electricity in Michigan—together accounting for 34% of renewable energy credits during the same time period. Michigan also has significant undeveloped wind energy potential. Michigan also requires electric providers to develop and fund “energy optimization” programs aimed at reducing electricity consumption. Michigan is one of the few states to count efficiency as an eligible clean energy resource, awarding “energy optimization credits” for successfully reducing energy consumption. Energy optimization credits can be substituted for renewable energy credits. As of December 2009, all utility customers in Michigan are eligible to participate in at least one energy-efficiency program offered through a local utility, and aggregate statewide funding for energy optimization programs has more than tripled from $\$$67 million in 2009 to $\$$208 million in 2011. Michigan is becoming a center for the domestic advanced battery industry. Companies all along the battery supply chain cluster in the state and draw from a talented pool of scientists, engineers, and other skilled workers with decades of experience in the auto industry. Michigan’s geographic position makes the state an attractive site for wind industry manufacturing; 2010 counted 31 wind technology manufacturing facilities in the state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

SPAROW: Stochastic Programming and Related Optimization Workflows

SAND2026-16703O SPAROW: Stochastic Programming and Related Optimization Workflows is a Python library tool that facilitates the development and solution of stochastic programming problems. It provides a user-friendly class structure for defining stochastic programs through scenario-based representations of uncertainties. SPAROW incorporates multiple optimization strategies, including integer programming with all scenarios, progressive hedging, Benders decomposition, and Snoglode, a novel technique developed by Carnegie Mellon University. It also features interfaces to external solvers and functions that are commonly used in analysis workflows, making it applicable to a wide range of scientific and engineering design challenges, particularly in power grid planning. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-NM), Albu↗
NASA NTRS1992

Optimal control computer programs

The solution of the optimal control problem, even with low order dynamical systems, can usually strain the analytical ability of most engineers. The understanding of this subject matter, therefore, would be greatly enhanced if a software package existed that could simulate simple generic problems. Surprisingly, despite a great abundance of commercially available control software, few, if any, address the part of optimal control in its most generic form. The purpose of this paper is, therefore, to present a simple computer program that will perform simulations of optimal control problems that arise from the first necessary condition and the Pontryagin's maximum principle.

Kuo, F.↗
NASA NTRS1972

Performance Analysis and Design Synthesis (PADS) computer program. Volume 3: User manual

The two-fold purpose of the Performance Analysis and Design Synthesis (PADS) computer program is discussed. The program can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general purpose branched trajectory optimization program. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent. The second module uses the method of quasi-linearization, which requires a starting solution from the first trajectory module.

Source record↗
NASA NTRS2005

Minimum impulse transfers to rotate the line of apsides

While an optimal scenario for the general two-impulse transfer between coplanar orbits is not known, there are optimal scenarios for various special cases. We consider in-plane rotations of the line of apsides. Numerical comparisons with a trajectory optimization program support the claim that the optimal deltaV required by two impulses is about half that required by a single impulse, regardless of semi-major axes. We observe that this estimate becomes more conservative with larger angles of rotation and eccentricities, and thus also present a more accurate two-impulse rotation deltaV estimator.

orbit rotation↗
DOE OSTI2014

SU-E-T-409: Intensity Modulated Robotic Radiotherapy

Purpose: As compared with the IRIS-based models, the MLC-based CyberKnife system allows more efficient treatment delivery due to its improved coverage of large lesions and intensity modulation. The treatment delivery efficiency is mainly determined by the number of selected nodes. This study aimed to demonstrate that relatively small sets of optimally selected nodes could produce high-quality plans. Methods: The full body path of the CyberKnife system consists of 110 nodes, from which we selected various sets for 4 prostate cancer cases using our in-house beamselection software. With the selected nodes we generated IMRT plans using our in-house beamlet-based inverse-planning optimization program. We also produced IMRT plans using the MultiPlan treatment planning system (version 5.0) for the same cases. Furthermore, the nodes selected by MultiPlan were used to produce plans with our own optimization software so that we could compare the quality of the selected sets of nodes. Results: Our beam-selection program selected one node-set for each case, with the number of nodes ranging from 23 to 34. The IMRT plans based on the selected nodes and our in-house optimization program showed adequate target coverage, with favorable critical structure sparing for the cases investigated. Compared with the plans using the nodes selected by MultiPlan, the plans generated with our selected beams provided superior rectum/bladder sparing for 75% of the cases. The plans produced by MultiPlan with various numbers of nodes also suggested that the plan quality was not compromised significantly when the number of nodes was reduced. Conclusion: Our preliminary results showed that with beamletbased planning optimization, one could produce high-quality plans with an optimal set of nodes for MLC-based robotic radiotherapy. Furthermore, our beam-selection strategy could help further improve critical structure sparing.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Optimization guide for programs compiled under IBM FORTRAN H (OPT=2)

Guidelines are given to provide the programmer with various techniques for optimizing programs when the FORTRAN IV H compiler is used with OPT=2. Subroutines and programs are described in the appendices along with a timing summary of all the examples given in the manual.

Smith, D. M.↗
NASA NTRS1988

Gear optimization

The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future.

Vanderplaats, G. N.↗
NASA NTRS1980

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 2: Appendices

The computer programs and derivations generated in support of the modeling and design optimization program are presented. Programs for the buck regulator, boost regulator, and buck-boost regulator are described. The computer program for the design optimization calculations is presented. Constraints for the boost and buck-boost converter were derived. Derivations of state-space equations and transfer functions are presented. Computer lists for the converters are presented, and the input parameters justified.

Lee, F. C.↗
NASA NTRS1989

Optimizing for minimum weight when two different finite element models and analyses are required

The Finite Element Structural Optimization Program's (FESOP) ability to perform minimum weight optimization using two different finite element analyses and models is discussed. FESOP uses the ADS optimizer developed by Dr. Garret Vanderplaats to solve the nonlinear constrained optimization problem. The design optimization problem requires a response spectrum analysis and model to evaluate the stress and displacement constraints. However, the problem needs a frequency analysis and model to calculate the natural frequencies used to evaluate the frequency range constraints. The results of both the successful and unsuccessful approaches used to solve this difficult weight minimization problem are summarized. The results show that no one ADS optimization algorithm worked in all cases. However, the Sequential Convex Programming and Modified Method of Feasible Directions algorithms were the most successful.

Hall, Jeffrey C.↗