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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Wing design by numerical optimization

A study was conducted to assess the feasibility of performing computerized wing design by numerical optimization. The design program combined a full potential, inviscid aerodynamics code with a conjugate gradient optimization algorithm. Three design problems were selected to demonstrate the design technique. The first involved modifying the upper surface of the inboard 50% of a swept wing to reduce the shock drag subject to a constraint on wing volume. The second involved modifying the entire upper surface of the same swept wing (except the tip section) to increase the lift-drag ratio subject to constraints on wing volume and lift coefficient. The final problem involved modifying the inboard 50% of a low-speed wing to achieve good stall progression. Results from the three cases indicate that the technique is sufficiently accurate to permit substantial improvement in the design objectives.

Hicks, R. M.↗
NASA NTRS1988

Near-optimal output feedback regulation of ill-conditioned linear systems

A two-time scale approximation for the linear quadratic optimal output feedback regulator program is examined. Necessary conditions for optimality, as well as an algorithm for computing locally near-optimal gains are derived. If it is assumed that the slow and fast subsystem initial conditions are uniformly distributed, optimal gains for the two-time-scale problem provide a second-order approximation to optimal closed-loop performance in the unperturbed system. This is verified with a numerical example.

Moerder, Daniel D.↗
NASA NTRS1991

Structural evaluation of curved stiffened composite panels fabricated using a THERM-Xsm process

The use of composites in aircraft structures is often limited by material and manufacturing costs which, for some designs and applications, are prohibitively high. To increase the frequency of application of composites in primary airframe components alternative manufacturing processes are sought that reduce cost and/or enhance structural efficiency. One alternative process involves the use of THERM-Xsm as the pressure transfer medium during autoclave curing. THERM-Xsm, a silicon-based flow able polymer which behaves like a liquid under autoclave presssure, transmits quasi-hydrostatic pressure to all contacting surfaces of the part to be cured. Once the autoclave pressure is relieved, THERM-Xsm reverts back to the powdery solid state and can be reused many times. The THERM-Xsm process to be evaluated is depicted and consists of (1) enclosing the tool and part to be cured by a set of frames that create a box, (2) pouring THERM-Xsm powder onto the part and filling the box, and (3) placing a vacuum bag over the box assembly. In this program, a separating non-porous film (Teflon) was placed between the part to be cured and THERM-Xsm powder to avoid any contamination. The use of THERM-Xsm has two significant advantages over conventional manufacturing procedures. First, it eliminates complicated hard tooling since it guarantees uniform pressure transfer and thus, good compaction at complex structural details (such as frame-stiffener intersections and corners). Second, it greatly simplifies vacuum bagging, since once the part to be cured is covered by THERM-Xsm powder, the vacuum bag need only conform to a relatively flat shape reducing significantly the number of pleats required. A program is on-going at Sikorsky Aircraft to evaluate the structural performance of complex composite fuselage structures made with this THERM-Xsm process and to quantify the impact of THERM-Xsm on manufacturing labor hours and cost. The program involves fuselage panel optimization analysis, a building block test program where structural details representative of the full-scale article are analyzed and tested, and static and fatigue test/analysis of the full-scale test articles. The main results of this program are reported.

Kassapoglou, Christos↗
DOE OSTI2011

Analysis and selection of optimal function implementations in massively parallel computer

An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch

A significant difficulty associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DC optimal power flow problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique by simulating dispatch operations on a synthetic test system over the course of a week.

94 GMLC - Grid Modernization Laboratory Consortium↗
DOE OSTI2014

Scoping Study Using Randomized Controlled Trials to Optimize Small Buildings' and Small Portfolios' (SBSP) Energy Efficiency Programs

This report is an initial step in determining whether randomized controlled trials (RCTs) should be used by the U.S. Department of Energy (DOE), utilities, and others to optimize energy efficiency programs targeting the small buildings and small portfolios (SBSPs) community. This scoping study reviews the use of RCTs to evaluate consumer purchasing and decision-making behaviors and to inform energy-efficient decision making. The scoping study discusses the relevant work, gaps in existing work, and potential value in pursuing further RCTs as related to energy-efficiency decision making in the SBSPs community. Our findings show that the factors that drive consumer behavior toward the purchasing of green products or energy efficiency programs remain complex, requiring further study of the underlying behavior mechanisms leading to environmental concern and action. Although small- and medium-sized businesses may share some purchasing behaviors with individual consumers and large commercial portfolios, important differences should be considered. Factors that are relevant to businesses include firm size to determine economies of scale, regulation, age, and turnover of capital equipment. Marketing approaches to promote green services such as energy efficiency need to go beyond a conventional cost-benefit analysis to include the highlighting of the psychological benefits and delivery of practical benefits, such as energy efficiency.

Guzowski, Leah↗
DOE OSTI2021

Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch

A significant difficulty associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DC optimal power flow problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique by simulating dispatch operations on a synthetic test system over the course of a week.

analog forecast↗
DOE OSTI2023

Impact of heating and cooling loads on battery energy storage system sizing in extreme cold climates

Efficient operation of battery energy storage systems requires that battery temperature remains within a specific range. Current techno-economic models neglect the parasitic loads heating and cooling operations have on these devices, assuming they operate at constant temperature. In this work, these effects are investigated considering the optimal sizing of battery energy storage systems when deployed in cold environments. Here, a peak shaving application is presented as a linear programming problem which is then formulated in the PYOMO optimization programming language. The building energy simulation software EnergyPlus is used to model the heating, ventilation, and air conditioning load of the battery energy storage system enclosure. Case studies are conducted for eight locations in the United States considering a nickel manganese cobalt oxide lithium ion battery type and whether the power conversion system is inside or outside the enclosure. The results show an increase of 42% to 300% in energy capacity size, 43% to 217% in power rating, and 43% to 296% increase in capital cost dependent on location. This analysis shows that the heating, ventilation, and air conditioning load can have a large impact on the optimal sizes and cost of a battery energy storage system and merit consideration in techno-economic studies.

25 ENERGY STORAGE↗
NASA NTRS1991

User's guide for NETS/PROSSS

Expensive analysis programs are often combined with optimization procedures to solve engineering problems. To obtain an optimal solution requires numerous iterations between the analysis program and the optimizer. This often becomes prohibitive due to the cost and amount of computer time needed to converge to an optimal solution. NETS/PROSSS was developed to address this problem. The purpose of this paper is to serve as a user's guide for NETS/PROSSS. The key features include the neural network, determining the training pairs for the neural network, and the approximated analysis/optimization process. A small problem is given to serve as an example of how to apply the system.

Rogers, James L.↗
NASA NTRS1983

Large-scale structural optimization

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1967

Automatic control

Numerical solution of optimal control and programming problems

FEEDBACK CONTROL SYSTEM↗
DOE OSTI2019

Route-Optimized Energy Management of Connected and Automated Multi-Mode Plug-In Hybrid Electric Vehicle Using Dynamic Programming

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route. The objective of the optimizer is to enable future Connected and Automated Vehicles (CAVs) to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile information from Intelligent Transportation Systems (ITS), Internet of Things (IoT), High-definition Mapping, and onboard sensing technologies. Emphasis is placed on runtime minimization to quickly react and plan an optimal mode scheme in highly dynamic road conditions with minimal computational resources. On-road performance of the optimizer paired with automated CD and CS mode selection is evaluated on a fleet of four instrumented Chevrolet Volts in a variety of driving scenarios. Here, the results indicate variable energy savings depending on the drive route and initial battery SOC with potential ranging between 2 to 12% and less than 7 seconds initial optimization for a 24-mile drive cycle.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1982

Combining analysis with optimization at Langley Research Center. An evolutionary process

The evolutionary process of combining analysis and optimization codes was traced with a view toward providing insight into the long term goal of developing the methodology for an integrated, multidisciplinary software system for the concurrent analysis and optimization of aerospace structures. It was traced along the lines of strength sizing, concurrent strength and flutter sizing, and general optimization to define a near-term goal for combining analysis and optimization codes. Development of a modular software system combining general-purpose, state-of-the-art, production-level analysis computer programs for structures, aerodynamics, and aeroelasticity with a state-of-the-art optimization program is required. Incorporation of a modular and flexible structural optimization software system into a state-of-the-art finite element analysis computer program will facilitate this effort. This effort results in the software system used that is controlled with a special-purpose language, communicates with a data management system, and is easily modified for adding new programs and capabilities. A 337 degree-of-freedom finite element model is used in verifying the accuracy of this system.

Rogers, J. L., Jr.↗
DOE OSTI2018

Concepts and Meta-Programming Library

CAMP provides a portable optimized implementation of template meta-programming primitives. All capabilities found within are available in other open source projects, including metal and mpl among others, but no other library we know of supports all compilers required by LLNL codes. CAMP serves as an efficient facility for writing portable compile-time operations in C++ codes. It was developed as part of the RAJA project to facilitate more complex compile-time introspection and better error message delivery to users, but has since proven useful in Umpire, CHAI and other pre-release LLNL software projects and is thus being re-factored to stand alone. The CAMP library uses portable C++ template mechanisms almost exclusively, with the exception of intrinsics provided for performance by some compilers such as clang and gee. There are no private or protected interfaces and no proprietary information included in the source. Any and all future versions will limit themselves to implementing commonly available and well known primitives for compile-time manipulation of types. A new public github repository will be created to host the code independent of its current location in the raja repository, likely at github.com/llnl/camp.

Kunen, AdamJ.↗