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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range

We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler flow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.

Li, Wu↗
NASA NTRS2007

ESAS-Derived Earth Departure Stage Design for Human Mars Exploration

The Vision for Space Exploration has set the nation on a course to have humans on Mars as early as 2030. To reduce the cost and risk associated with human Mars exploration, NASA is planning for the Mars architecture to leverage the lunar architecture as fully as possible. This study takes the defined launch vehicles and system capabilities from ESAS and extends their application to DRM 3.0 to design an Earth Departure Stage suitable for the cargo and crew missions to Mars. The impact of a propellant depot in LEO was assessed and sLzed for use with the EDS. To quantitatively assess and compare the effectiveness of alternative designs, an initial baseline architecture was defined using the ESAS launch vehicles and DRM 3.0. The baseline architecture uses three NTR engines, LH2 propellant, no propellant depot in LEO, and launches on the Ares I and Ares V. The Mars transfer and surface elements from DRM 3.0 were considered to be fixed payloads in the design of the EDS. Feasible architecture alternatives were identified from previous architecture studies and anticipated capabilities and compiled in a morphological matrix. ESAS FOMs were used to determine the most critical design attributes for the effectiveness of the EDS. The ESAS-derived FOMs used in this study to assess alternative designs are effectiveness and performance, affordability, reliability, and risk. The individual FOMs were prioritized using the AHP, a method for pairwise comparison. All trades performed were evaluated with respect to the weighted FOMs, creating a Pareto frontier of equivalently ideal solutions. Additionally, each design on the frontier was evaluated based on its fulfillment of the weighted FOMs using TOPSIS, a quantitative method for ordinal ranking of the alternatives. The designs were assessed in an integrated environment using physics-based models for subsystem analysis where possible. However, for certain attributes such as engine type, historical, performance-based mass estimating relations were more easily employed. The elements from the design process were integrated into a single loop, allowing for rapid iteration of subsystem analyses and compilation of resulting designs.

Flaherty, Kevin↗
DOE OSTI2024

Artificial Intelligence for Conjugated Polymers

Conjugated polymers have garnered significant attention due to their diverse applications in electronics, photonics, and energy storage. However, realizing their full potential poses a formidable challenge, as their design has historically relied on iterative adjustments and continuous inspiration from researchers. Traditional methods often struggle to efficiently navigate their vast chemical landscape. In this work, the application of artificial intelligence (AI), specifically machine learning (ML), needs to be discussed in the realm of conjugated polymers. Our paper emphasizes the importance of understanding the structure–property relationships of these polymers and how ML can facilitate property prediction and inverse-design. We delve into various chemical fingerprints, structural descriptors, and ML algorithms, showcasing their utility across a spectrum of applications, including simulations, glass transition temperature determination, photovoltaics, reorganization energy for charge transport, photocatalysts, and sensors. Finally, we give some outlooks in this filed and propose unexplored areas within the field that hold the potential to benefit from ML techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Preliminary Thermal-Hydraulic Analysis of the UTA–2 Subcritical Linear Accelerator–Driven System

The National Nuclear Security Administration’s mission includes establishing a reliable supply of 99 Mo without highly enriched uranium. Oak Ridge National Laboratory (ORNL) supports this objective through collaborative research and development with industrial partners. Niowave Inc., a current partner, is currently designing a subcritical linear accelerator-driven system (ADS) and preparing for the US Nuclear Regulatory Commission’s licensing process. Niowave’s system has the potential to efficiently supply medical radioisotopes. The technology includes a superconducting electron accelerator and a pile of both natural and low-enriched uranium (LEU) targets. The process fissions uranium and many valuable isotopes can then be extracted from the targets. Niowave is currently iterating through conceptual and detailed design processes for several system sizes. This report discusses UTA–2, which is at the demonstration stage. UTA–2 will validate numerical modeling results with experimental measurements before progressing to the detailed design of UTA–3, the commercial-sized ADS. The thermal-hydraulic behavior of the UTA–2 core design was numerically investigated using STAR-CCM+, as described in this report. STAR-CCM+, a state-of-the-art computational fluid dynamics (CFD) software that was commercially developed by Siemens, has an extensive user base and a set of validation studies. It is also compliant with the American Society of Mechanical Engineers’ Nuclear Quality Assurance 1 standard. Three cases are investigated in this report. Case 1 quantified the temperature field within the UTA–2 assembly and water tank using only conduction as the method of thermal energy transport. This simplified approach was overly conservative and yielded wetted cladding temperatures above the coolant saturation temperature. In this case, the maximum temperature of the wetted cladding surface of the highest power rod exceeded the saturation temperature of water by 63.8°C. Because of the overly conservative approach taken in Case 1 and its negative subcooled margin, buoyancy-driven natural circulation flow physics were implemented in Case 2. Adding coolant motion significantly distributed the thermal energy of the system through convective heat transfer. This relatively small amount of convective heat transfer significantly reduced system temperatures and increased the subcooled margin from –63.8 to 61.3°C. This margin confirmed that no boiling was expected during normal operation of UTA–2 at 230 W. Case 3 had no additional physics models but considered an overpower event during which the power of each LEU and natural uranium rod was at its respective peak values. This resulted in a study with the total assembly power equal to 176% of the nominal power of 230 W considered in Cases 1 and 2. The resulting natural circulation flows were slightly enhanced. The subcooled margin decreased slightly to 46.3°C, which is still a significant margin to local boiling of the water within the tank. This margin confirmed that no boiling was expected during an abnormal operation of UTA–2 at 406 W.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2006

Protograph LDPC Codes Over Burst Erasure Channels

In this paper we design high rate protograph based LDPC codes suitable for binary erasure channels. To simplify the encoder and decoder implementation for high data rate transmission, the structure of codes are based on protographs and circulants. These LDPC codes can improve data link and network layer protocols in support of communication networks. Two classes of codes were designed. One class is designed for large block sizes with an iterative decoding threshold that approaches capacity of binary erasure channels. The other class is designed for short block sizes based on maximizing minimum stopping set size. For high code rates and short blocks the second class outperforms the first class.

protgraph based codes↗
NASA NTRS1989

Applications of a transonic wing design method

A method for designing wings and airfoils at transonic speeds using a predictor/corrector approach was developed. The procedure iterates between an aerodynamic code, which predicts the flow about a given geometry, and the design module, which compares the calculated and target pressure distributions and modifies the geometry using an algorithm that relates differences in pressure to a change in surface curvature. The modular nature of the design method makes it relatively simple to couple it to any analysis method. The iterative approach allows the design process and aerodynamic analysis to converge in parallel, significantly reducing the time required to reach a final design. Viscous and static aeroelastic effects can also be accounted for during the design or as a post-design correction. Results from several pilot design codes indicated that the method accurately reproduced pressure distributions as well as the coordinates of a given airfoil or wing by modifying an initial contour. The codes were applied to supercritical as well as conventional airfoils, forward- and aft-swept transport wings, and moderate-to-highly swept fighter wings. The design method was found to be robust and efficient, even for cases having fairly strong shocks.

Campbell, Richard L.↗
NASA NTRS1994

Multidisciplinary design optimization using genetic algorithms

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Unal, Resit↗
NASA NTRS1979

The design of supercritical wings by the use of three-dimensional transonic theory

A procedure was developed for the design of transonic wings by the iterative use of three dimensional, inviscid, transonic analysis methods. The procedure was based on simple principles of supersonic flow and provided the designer with a set of guidelines for the systematic alteration of wing profile shapes to achieve some desired pressure distribution. The method was generally applicable to wing design at conditions involving a large region of supercriterical flow. To illustrate the method, it was applied to the design of a wing for a supercritical maneuvering fighter that operates at high lift and transonic Mach number. The wing profiles were altered to produce a large region of supercritical flow which was terminated by a weak shock wave. The spanwise variation of drag of this wing and some principles for selecting the streamwise pressure distribution are also discussed.

Mann, M. J.↗
NASA NTRS1990

An improved fully stressed design algorithm for plate/shell structures

The stress-ratio algorithm associated with fully stressed design philosophy has been used as a convenient tool to achieve minimum weight design of strength-limited structures. The algorithm is effective and converges quickly for many cases. However, it presents extremely slow oscillatory iteration histories for plate-thickness design problems that involve transverse bending loads. Modification of the basic algorithm presented in this paper provides an effective remedy to this problem when both membrane and bending loads are present. The modified resizing algorithm requires numerical solutions of a fourth-order algebraic equation. No additional data, beyond the ordinary static analysis results, are required.

Miura, H.↗
NASA NTRS1998

Aerothermodynamic Flight Simulation Capabilities for Aerospace Vehicles

Aerothermodynamics, encompassing aerodynamics, aeroheating, and fluid dynamics and physical processes, is the genesis for the design and development of advanced space transportation vehicles and provides crucial information to other disciplines such as structures, materials, propulsion, avionics, and guidance, navigation and control. Sources of aerothermodynamic information are ground-based facilities, Computational Fluid Dynamic (CFD) and engineering computer codes, and flight experiments. Utilization of this aerothermodynamic triad provides the optimum aerothermodynamic design to safely satisfy mission requirements while reducing design conservatism, risk and cost. The iterative aerothermodynamic process for initial screening/assessment of aerospace vehicle concepts, optimization of aerolines to achieve/exceed mission requirements, and benchmark studies for final design and establishment of the flight data book are reviewed. Aerothermodynamic methodology centered on synergism between ground-based testing and CFD predictions is discussed for various flow regimes encountered by a vehicle entering the Earth s atmosphere from low Earth orbit. An overview of the resources/infrastructure required to provide accurate/creditable aerothermodynamic information in a timely manner is presented. Impacts on Langley s aerothermodynamic capabilities due to recent programmatic changes such as Center reorganization, downsizing, outsourcing, industry (as opposed to NASA) led programs, and so forth are discussed. Sample applications of these capabilities to high Agency priority, fast-paced programs such as Reusable Launch Vehicle (RLV)/X-33 Phases I and 11, X-34, Hyper-X and X-38 are presented and lessons learned discussed. Lastly, enhancements in ground-based testing/CFD capabilities necessary to partially/fully satisfy future requirements are addressed.

Miller, Charles G.↗
DOE OSTI2025

DESIGN ISSUES AND QUALIFICATION OF HYDROFORMED DOUBLE WALLED EXPANSION JOINTS IN VACUUM SERVICE

The Vacuum Auxiliary System for ITER is devoted to pumping out, venting, and purging the vacuum volumes of the tokamak. Over 5000 clients including the cryostat and vacuum vessel, at 8500 m3 and 1400 m3 respectively, are serviced by approximately 150 pumping stations through 6 km of pipework. The piping and functions provided to the clients include component operation, routing of potentially tritiated gases, and timely leak localization. Expansion joints are used to reduce loadings on pumps and piping stresses but also to qualify in-line components having low allowable design loads. The ITER project utilizes vacuum valves that are not designed to withstand typical piping system loadings and require detailed design and evaluation. Loading scenarios prescribed by governing system specifications must be considered. To maintain allowable design loads for components and to keep piping stresses below code requirements, double walled hydroformed expansion joints have been employed in the design. These are not standard items and require custom fabrication. Installation space constraints and adjacent pipe support attachment location availability at ITER limit standard expansion joint installation guidelines provided by the Expasion Joint Manufacturers Association (EJMA). Careful consideration must be given to the analysis model to ensure proper function and life expectancy of the component. These considerations include accurate accounting of thrust forces, thermal movements, seismic accelerations, equipment and building differential displacements. In addition to displacements, the process internal, external, and interspace pressures affect the qualification and selection of the double walled expansion joints. The calculation results shall confirm that deflections, forces, and moments are reasonable for the size and type required for the system’s demands as evaluated against the manufacturer’s design.

Clark, Forrest [ORNL] (ORCID:0009000678106843)↗
NASA NTRSDate not supplied

Designing the Design Process for Early Problem Discovery for a Complex Aeronautics Systems Challenge

The earliest stage in the innovation lifecycle, problem formulation, is crucial for setting direction in an innovation effort. When faced with an interesting problem, engineers commonly assume the approximate solution area and focus on ideating innovative solutions. However, in this project, NASA and their contracted partner, Accenture, collaboratively conducted problem discovery to ensure that solutioning efforts were focused on the right problems, for the right users, and addressing the most critical needs—in this case, exploring weather tolerant operations (WTO) to further urban air mobility (UAM) – known as UAM WTO. The project team leveraged generative, qualitative methods to understand the ecosystem, players, and where challenges in the industry are inhibiting development. The complexity of the problem area required that the team constantly observe and iterate on problem discovery, effectively “designing the design process.” This report discusses the approach, methodologies, and selected results, including insights on the application of early-stage design methodologies to a complex, system-level problem.

Problem formulation↗
NASA NTRS2018

Do You See What I See? Interactive Visualization of Mission Design and Navigation

Mission Design and Navigation (MDNav) is an intensive process requiring advanced computational resources, expert human intuition, and many successive human-in-the-loop iterations to converge on acceptable trajectory designs or navigation solutions. The current bottleneck in MDNav is not the underlying computational algorithms but the human cognitive capacity to prune through a multitude of simulated results to select high-value candidates. One approach to alleviate this burden is through the judicious application of visualizations that allow humans to interactively filter data in multiple dimensions to reveal salient patterns and highlight divergences. When designed efficiently, such interactive visualizations should aid human operators to get familiar with data faster, visually observe correlations, and communicate findings more effortlessly. In this work, we present three visualization case studies that have the potential to increase human operator efficiency in MDNav. While identifying the most critical “pain points” that operators face, and also working on potential solutions, we followed a human-centered design approach. We started with a series of interviews with potential users, and then rapidly created prototypes for alternative solutions, validated outcomes with feedback from users through out development of these proof of concept visualizations. With this survey of our current efforts, we demonstrate the transformative capability of interactive data visualizations for improving mission development and operations, enabling operators to grow intuition, and communicating key concepts across diverse mission teams.

Arora, Nitin↗
NASA NTRS2010

Packing Optimization of an Intentionally Stratified Sorbent Bed Containing Dissimilar Media Types

The Fire Cartridge is a packed bed air filter with two different and separate layers of media designed to provide respiratory protection from combustion products after a fire event on the International Space Station (ISS). The first layer of media is a carbon monoxide catalyst made from gold nanoparticles dispersed on iron oxide. The second layer of media is universal carbon, commonly used in commercial respirator filters. Each layer must be optimally packed to effectively remove contaminants from the air. Optimal packing is achieved by vibratory agitations. However, if post-packing movement of the media within the cartridge occurs, mixing of the bed layers, air voids, and channeling could cause preferential air flow and allow contaminants to pass. Several iterations of prototype fire cartridges were developed to reduce post-packing movement of the media within each layer (settling), and to prevent mixing of the two media types. Both types of movement of the media contribute to decreased fire cartridge performance. Each iteration of the fire cartridge design was tested to demonstrate mechanical loads required to cause detrimental movement within the bed, and resulting level of functionality of the media beds after movement was detected. In order to optimally pack each layer, vertical, horizontal, and orbital agitations were tested and a final packed bulk density was calculated for each method. Packed bulk density must be calculated for each lot of catalyst to accommodate variations in particle size, shape, and density. In addition, a physical divider sheet between each type of media was added within the fire cartridge design to further inhibit intermixing of the bed layers.

Kidd, Jessica↗
DOE OSTI2020

Constrained Bayesian optimization of criticality experiments

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. Furthermore, we demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments at LLNL [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for critical ity safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2021

Candidate Core Designs for the Transformational Challenge Reactor

Early cycle activities under the Transformational Challenge Reactor (TCR) program focused on analyzing and maturing four reactor core design concepts: two fast-spectrum systems and two thermal-spectrum systems. A rapid, iterative approach has been implemented through which designs can be modified and analyzed and subcomponents can be manufactured in parallel over time frames of weeks rather than months or years. To meet key program initiatives (e.g., timeline, material use), several constraints—including fissile material availability (less than 250 kg of HALEU), component availabilities, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small (less than one cubic meter in volume) cores with near-term viability. The fast-spectrum designs did not meet the fissile material constraint, so the thermal-spectrum systems became the primary design focus. Since significant progress has been made on advanced moderator materials (YH x ) under the TCR program, gas-cooled thermal-spectrum systems using less than 250 kg of HALEU that occupy less than 1 m 3 are now feasible. The designs for two of these systems have been evolved and matured. In both thermal-spectrum design concepts, bidirectional coolant flow is used. Coolant flows down through YH x moderator elements and is reversed in a bottom manifold and core support structure, and then flows up though or around the fuel elements. The main difference between the two thermal-spectrum design concepts is the fuel elements—one uses traditional UO 2 ceramic fuel, and the other uses UN-bearing TRISO fuel particles embedded inside a SiC matrix. Finally, core neutronics and thermal performance for these systems are assessed and summarized herein.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗