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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 sources NASA NTRS DOE OSTI

NASA NTRS1991

UV-optical from space

The following subject areas are covered: (1) the science program (star formation and origins of planetary systems; structure and evolution of the interstellar medium; stellar population; the galactic and extragalactic distance scale; nature of galaxy nuclei, AGNs, and QSOs; formation and evolution of galaxies at high redshifts; and cosmology); (2) implementation of the science program; (3) the observatory-class missions (HST; LST - the 6m successor to HST; and next-generation 16m telescope); (4) moderate and small missions (Delta-class Explorers; imaging astrometric interferometer; small Explorers; optics development and demonstrations; and supporting ground-based capabilities); (5) prerequisites - the current science program (Lyman-FUSE; HTS optimization; the near-term science program; data analysis, modeling, and theory funding; and archives); (6) technologies for the next century; and (7) lunar-based telescopes and instruments.

Illingworth, Garth↗

NASA NTRS2003

Novel approaches and application of contemporary sensory evaluation practices in iron fortification programs

Iron deficiency is the leading nutritional deficiency in the U.S. and the rest of the world, with its highest prevalences in the developing world. Iron fortification of food has been proposed as a strategy to reduce the high prevalence of iron deficiency. Poor consumer acceptance, unacceptable taste, and discoloration of the iron-fortified foods have been frequently listed as causes of unsuccessful iron fortification programs. An excellent prospect for improving consumer acceptance of iron-fortified foods is the incorporation of a thorough, organized, and unified approach to sensory evaluation practices into iron fortification programs for product optimization. The information gained from systematic sensory evaluation allows for the manipulation of the sensory attributes, and thus improvement of the sensory properties of the fortified food. However, iron fortification programs have not systematically measured the effect of fortification on the sensory quality of the food. Because sensory evaluation is an important criterion in successful iron fortification, an integrated approach is necessary. Therefore, nutritionists and sensory scientists should work closely with each other to select the most suitable sensory tests and methods. The objectives of this article are to: (1) critically review and discuss some traditional and contemporary approaches and applications of sensory evaluation practices in iron fortification programs, and (2) demonstrate the importance of incorporating a multidisciplinary, systematic sensory evaluation approach in iron fortification programs.

Review, Tutorial↗

DOE OSTI2013

Materials and Modules for Low Cost, High Performance Fuel Cell Humidifiers

The objective of this program was to demonstrate a durable, high performance water transport membrane; and a compact, low-cost, membrane-based module utilizing that membrane for use in an automotive, stationary and/or portable fuel cell water transport exchangers. Over the past 20 years, great technical progress has been made in improving power density and durability of fuel cell stacks. Yet, operating durably at high performance levels under very dry conditions, e.g., < 20% RH at 80°C or above, remains beyond even the best fuel cell membrane electrode assemblies. Thus, today it is essential to humidify the gases supplied to the fuel cell inlets. In this work, we have produced a new, inexpensive, composite membrane capable of very high water vapor transport and low air cross-over. The composite structure consists of a very thin ionomer layer (e.g., < 5 μm) sandwiched between two microporous polymer layers. The thin ionomer layer facilitates the rapid water transport and provides an impermeable layer to prevent gas cross-over. Such an approach reduces cost, but maintains performance. The microporous layer protects the thin ionomer layer from mechanical damage during handling; confers strength to the thin layer allowing it to be more durable during use; and allows it to withstand higher automotive pressures and temperatures. The composite structure will therefore allow lower total cost while still meeting automotive humidifier water transport and durability targets. Because the transport rates of these new materials are so high, existing planar membrane humidifier module designs available at the start of the program were incapable of efficiently utilizing the high rates. Therefore, the assembled team designed, tested and demonstrated an innovative, low-cost humidifier module with customized channel geometries that can take advantage of the high the water transport rates. The objectives of the program have been fully met. The optimized membrane produced in the program has very high transport rates, nearly twice that of the closest competitive option, a homogeneous perfluorosulfonic acid (PFSA) membrane. Furthermore, the composite structure imparts significant durability advantages, allowing the membrane to remain gas impermeable during 20,000 relative humidity (RH) cycles, unlike the closest competitive options that fail very rapidly. It does suffer from a loss of performance with time at temperature because of inherent properties of the PFSA polymer, but this degradation is manageable through relatively simple system design changes. The final membrane of this program has been produced on manufacturing level equipment in a roll to roll form in the scale of hundreds of square meters. The process is readily scalable to automotive level volumes to allow production of a low-cost membrane required for this application. A full scale automotive air-to-air humidifier module has been designed, tested and built. The final module meets the design specifications required for automotive fuel cell use, and exceeds all the DOE 2017 targets for a cathode humidification module as determined in independent testing at Ford Motor Company. It has a small volume, less than 5 liters; a high water transfer rate, significantly greater than 5 g/s at the DOE specified conditions; acceptably low pressure drop; and is projected to maintain these properties over 5000 hours. Additionally, high volume cost projections suggest that the module can be produced for less than $\$$100 per unit in a scale of 500,000 units per year.

08 HYDROGEN↗

DOE OSTI2013

Materials and Modules for Low Cost, High Performance Fuel Cell Humidifiers (Final Report)

Over the past 20 years, great technical progress has been made in improving power density and durability of fuel cell stacks. Yet, operating durably at high performance levels under very dry conditions, e.g., < 20% RH at 80 °C or above, remains beyond even the best fuel cell membrane electrode assemblies. Thus, today it is essential to humidify the gases supplied to the fuel cell inlets. In this work, we have produced a new, inexpensive, composite membrane capable of very high water vapor transport and low air cross-over. The composite structure consists of a very thin ionomer layer (e.g., < 5 μm) sandwiched between two microporous polymer layers. The thin ionomer layer facilitates the rapid water transport and provides an impermeable layer to prevent gas cross-over. Such an approach reduces cost, but maintains performance. The microporous layer protects the thin ionomer layer from mechanical damage during handling; confers strength to the thin layer allowing it to be more durable during use; and allows it to withstand higher automotive pressures and temperatures. The composite structure will therefore allow lower total cost while still meeting automotive humidifier water transport and durability targets. Because the transport rates of these new materials are so high, existing planar membrane humidifier module designs available at the start of the program were incapable of efficiently utilizing the high rates. Therefore, the assembled team designed, tested and demonstrated an innovative, low-cost humidifier module with customized channel geometries that can take advantage of the high the water transport rates. Program Results: The objectives of the program have been fully met. The optimized membrane produced in the program has very high transport rates, nearly twice that of the closest competitive option, a homogeneous perfluorosulfonic acid (PFSA) membrane. Furthermore, the composite structure imparts significant durability advantages, allowing the membrane to remain gas impermeable during 20,000 relative humidity (RH) cycles, unlike the closest competitive options that fail very rapidly. It does suffer from a loss of performance with time at temperature because of inherent properties of the PFSA polymer, but this degradation is manageable through relatively simple system design changes. The final membrane of this program has been produced on manufacturing level equipment in a roll to roll form in the scale of hundreds of square meters. The process is readily scalable to automotive level volumes to allow production of a low-cost membrane required for this application. A full scale automotive air-to-air humidifier module has been designed, tested and built. The final module meets the design specifications required for automotive fuel cell use, and exceeds all the DOE 2017 targets for a cathode humidification module as determined in independent testing at Ford Motor Company. It has a small volume, less than 5 liters; a high water transfer rate, significantly greater than 5 g/s at the DOE specified conditions; acceptably low pressure drop; and is projected to maintain these properties over 5000 hours. Additionally, high volume cost projections suggest that the module can be produced for less than $100 per unit in a scale of 500,000 units per year.

08 HYDROGEN↗

DOE OSTI2015

HEMS: Home Energy Management System [SWR-15-12] - Stochastic Optimal Scheduling of Residential Appliances with Renewable Energy Sources

The HEMS algorithm schedules residential appliance operation to minimize the weighted sum of occupant discomfort, total energy cost, peak electricity consumption and carbon footprint, weighted according to occupant preferences. A centralized mixed integer linear programming (MILP) based optimization approach is taken, with the HEMS managing all appliances directly, following a Model Predictive Control (MPC) methodology which determines the optimal schedule over the user-specified scheduling horizon and repeats the optimization at configurable time intervals. The HEMS is developed on the General Algebraic Modeling System (GAMS) using the MILP solver. This system is able to effectively deal with the stochasticity in the distributed system by utilizing Monte Carlo simulation where uncertainties in future electricity price, outdoor temperature, water usage, solar and wind generation can be accounted for. The HEMS controls the operation of the heating, ventilation and air conditioning (HVAC) system, water heater, refrigerator, residential batteries, electric vehicles, standalone micro combined heat and power (CHP) generator, dishwasher, washer/dryer, pool pumps, and lighting.

Pratt, Annabelle↗

NASA NTRS2020

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗

DOE OSTI2024

Measure this, not that: Optimizing the cost and model-based information content of measurements

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. Here, this work extends popular MBDoE workflows by proposing a convex mixed integer (non)linear programming (MINLP) to optimize the selection of measurements. The solver MindtPy is modified to support calculating the D-optimality objective and its gradient via an external package, scipy, using the grey-box module in Pyomo. The new approach is demonstrated in two case studies: estimating highly correlated kinetics from a batch reactor and estimating transport parameters in a large-scale rotary packed bed for CO 2 capture. Both case studies show how examining the Pareto optimal trade-offs between information content measured by A- and D-optimality versus measurement budget offers practical guidance for selecting measurements for scientific experiments.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1989

Optimal Placement Of Multiple Antennas

Computer program based on pair of algorithms selects approximately optimal locations of antennas and approximately optimal number of elements in each antenna of multiple-antenna communication system. Obscuration in field of view at given antenna location taken into account in choice of number of antenna elements mounted there. Directional coverages of combinations of up to four antenna elements computed in search for combination to cover clear portion of field of view. Developed to aid design of antenna system of conceptual space station. Applied to system aboard ship or aircraft, on building in city, or in any location where transmission and reception blocked in some directions from each potential antenna-mounting point.

Shelton, Kyle W.↗

NASA NTRS1975

Applications of a quadratic extended interior penalty function for structural optimization

A quadratic extended interior penalty function formulation especially well suited for second-order unconstrained optimization procedures is presented. Analytical derivatives of constraints and an approximate analysis technique are used. Minimum-mass design results are presented which indicate that the combination of these procedures can help make mathematical programming a useful optimization tool for large-order structural design problems with a large number of design variables and multiple constraints. Examples include statically loaded high- and low-aspect-ratio wings simultaneously subjected to stress, displacement, minimum gage and, in some cases, maximum strain constraints.

Haftka, R. T.↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS1973

A summary report on system effectiveness and optimization study

Report treats optimization and effectiveness separately. Report illustrates example of dynamic programming solution to system optimization. Computer algorithm has been developed to solve effectiveness problem and is included in report.

Williamson, O. L.↗

NASA NTRS2003

Formation Tetrahedron Design for Phase I of the Magnetospheric Multiscale Mission

The Magnetospheric Multiscale Mission (MMS) is a NASA mission intended to make fundamental advancements in our understanding of the Earth's Magnetosphere. There are three processes that MMS will study including magnetic reconnection, charged particle acceleration, and turbulence. There are four phases in the nominal mission and this work addresses some of the outstanding issues in phase I. The nominal phase I orbit is 1.2 x 12 R(sub e) highly elliptic orbit with four spacecraft nominally forming a regular tetrahedron. In this paper we investigate the relative dynamics of the four MMS spacecraft about an assumed reference orbit. There are several tetrahedron dimensions required in Phase I of the mission and in this work we design optimal tetrahedrons for the 10 km baseline. The performance metric used in the optimization process is directly related to the science return, and is based on an extension of previous work performed by Glassmeier. The optimizer we use is a commercially available Sequential Quadratic Programming (SQP) routine. Multiple optimal solutions are found, and we characterize how the performance of the formation varies between different regions of the reference orbit.

Hughes, Steven P.↗

NASA NTRS1998

Minimum Climb to Cruise Noise Trajectories Modeled for the High Speed Civil Transport

The proposed U.S. High Speed Civil Transport (HSCT) will revolutionize commercial air travel by providing economical supersonic passenger service to destinations worldwide. Unlike the high-bypass turbofan engines that propel today's subsonic airliners, HSCT engines will have much higher jet exhaust speeds. Jet noise, caused by the turbulent mixing of high-speed exhaust with the surrounding air, poses a significant challenge for HSCT engine designers. To resolve this challenge, engineers have designed advanced mixer rejector nozzles that reduce HSCT jet noise to airport noise certification levels by entraining and mixing large quantities of ambient air with the engines' jet streams. Although this works well during the first several minutes of flight, far away from the airport, as the HSCT gains speed and climbs, poor ejector inlet recovery and ejector ram drag contribute to poor thrust, making it advantageous to turn off the ejector. Doing so prematurely, however, can cause unacceptable noise levels to propagate to the ground, even when the aircraft is many miles from the airport. This situation lends itself ideally to optimization, where the aircraft trajectory, throttle setting, and ejector setting can be varied (subject to practical aircraft constraints) to minimize the noise propagated to the ground. A method was developed at the NASA Lewis Research Center that employs a variation of the classic energy state approximation: a trajectory analysis technique historically used to minimize climb time or fuel burned in many aircraft problems. To minimize the noise on the ground at any given throttle setting, high aircraft altitudes are desirable; but the HSCT may either climb quickly to high altitudes using a high, noisy throttle setting or climb more slowly at a lower, quieter throttle setting. An optimizer has been programmed into NASA's existing aircraft and noise analysis codes to balance these options by dynamically choosing the best altitude-velocity path and throttle setting history. The noise level standard, or metric, used in the optimizer should be one that accurately reflects the subjective annoyance levels of ground-based observers under the flight path. A variety of noise metrics are available, many of which are practical for airport-vicinity noise certification. Unlike airport noise, however, the HSCT's climb noise will be characterized by relatively low noise levels, long durations, and low-frequency spectra. The noise metrics used in these calculations are based on the recommendations of researchers at the NASA Langley Research Center, who have correlated the flyover noise annoyance levels of actual laboratory subjects with a variety of measurements. Analysis of data from this optimizer has shown that significant reductions in noise may be obtained with trajectory optimization. And since throttling operations are performed in the subsonic portion of the climb path (where thrust is plentiful), only small penalties in HSCT range or fuel performance occur.

Berton, Jeffrey J.↗

DOE OSTI2024

Inventory of Clean Energy Education and Workforce Programs in Connecticut's I-91 Corridor

This document reports on the findings of an inventory of the educational and workforce development resources in a four-county area on the I-91 corridor in Connecticut. The overarching goal of this exercise is to help the local workforce leaders in Bridgeport, Connecticut to optimize their training programs to support the county's clean energy transition. The inventory generally finds that Fairfield County, where Bridgeport is located, lacks adequate education and training programs compared to other surrounding counties with similar populations. More than half of Fairfield County's programs occur through high school or career technical education programs, suggesting that there are minimal opportunities for workers who are not currently high school students. Much of the existing focus within Fairfield County is on general construction or plumbing and electrical skills. There is room to expand by offering more programs focusing on energy efficiency and renewable energy skills. The document outlines some potential next steps and questions for consideration for the local workforce leaders in Bridgeport. Bridgeport is a city located within Fairfield County in southwestern Connecticut. It is the largest city in Connecticut with an estimated population of 150,000. Through the Department of Energy-funded Communities LEAP program, NREL conducted an analysis of existing education and workforce development (EWD) programs located in Fairfield County that align with (or could support) the worker pipeline for occupations related to building energy efficiency (EE), renewable energy (RE), and clean energy manufacturing. The analysis also looked at EWD offerings in other counties in Connecticut as a point of comparison.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Optimization of battery swapping infrastructure for e-commerce drone delivery

Drone delivery is widely-researched to alter the current e-commerce delivery convention for providing short delivery lead times. Yet, flight range of drones, constrained by the available battery technology, sets a milestone toward realizing the sole-drone delivery. To tackle with the flight range limitation, locating automated battery swapping machines (ABSM) have been proposed and a few studies modeled the problem. Using the ABSMs, drones can be loaded with fully-charged batteries along the route to a demand location. Here, we introduce a mixed-integer nonlinear program to model the problem. The objective of the program is to optimally select ABSM locations, determine the delivery-mode choices (drone-only, truck-only, and mixed delivery) of demand locations, find drone delivery routes, and approximate the baseline requirements for the number of drones and batteries needed. The program minimizes the overall delivery system costs including: ABSM, delivery, drone ownership, battery inventory, and service congestion. A cutting-plane method is developed to find exact solutions in finite iterations. Computational experiments showed that the method quickly yields the optimal solution to instances with less than 60 ABSM candidates and 20 demand locations. A case study shows that the optimal drone delivery infrastructure can save almost 20% cost compared to the conventional truck-only delivery. Sensitivity analyses were conducted to reveal the impact of key parameters in the decision-making and found that a decrease in the ABSM and drone costs highly affect the system cost.

25 ENERGY STORAGE↗

NASA NTRS1975

Control optimization, stabilization and computer algorithms for aircraft applications

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

Source record↗

DOE OSTI2020

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

A significant difficultly 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 DCOPF 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 on simulated dispatch operations of the RTS-GMLC over a week.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1976

Operations research investigations of satellite power stations

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

Cole, J. W.↗