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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Rapid Preliminary Design of Interplanetary Trajectories Using the Evolutionary Mission Trajectory Generator

This set of tutorial slides is an introduction to the Evolutionary Mission Trajectory Generator (EMTG), NASA Goddard Space Flight Center's autonomous tool for preliminary design of interplanetary missions. This slide set covers the basics of creating and post-processing simple interplanetary missions in EMTG using both high-thrust chemical and low-thrust electric propulsion along with a variety of operational constraints.

optimization↗
NASA NTRS2026

Uranus Orbiter and Probe: Mission Challenges and Concept Updates Since the Origins, Worlds, and Life Decadal Survey

Origins, Worlds, and Life: Planetary Science and Astrobiology in the Next Decade identified a Uranus Orbiter and Probe as the highest-priority strategic mission for the decade 2023–2032, as it enables broad cross-disciplinary science in the largely unexplored Uranian system. The mission architecture evaluated by the Decadal Survey was a singular proof of concept demonstrating that a moderately instrumented mission could deliver Decadal-priority science with a reduced cost and risk posture by leveraging existing technologies to the maximum extent possible. With revised assumptions since the Decadal, we have explored a large trade space including launch vehicles, propulsion options, cruise trajectories, available power sources, viable concept of operations, and science data return for later launch dates without a Jupiter gravity assist. The most repeatable trajectory solutions employ either a commercially derived solar electric propulsion (SEP) transfer stage or the availability of a more capable launch vehicle under development, such as the SpaceX Starship. Orbit insertion has been moved farther from Uranus to acknowledge the remaining uncertainty in Uranian ring structure. A streamlined, SEP-adaptable, orbiter design was developed using two Next Gen Radioisotope Thermoelectric Generators, and the probe design was matured, reducing the entry gravitational acceleration, and assuming the largest Decadal-recommended payload to provide margin for future instrument selections. With this updated design, we also constructed a detailed concept of operations for three representative science cases, returning 13–15 Gbit of science data and spacecraft telemetry per ∼34 day orbit.

Amy A Simon↗
DOE OSTI2020

Randomization of dangling nodes in a digital circuit design to mitigate hardware trojans

Described herein are various technologies pertaining to randomizing logic associated with dangling nodes in a digital circuit design. A dangling node is an input to or output from a logic gate in the digital circuit design that is identified as not impacting a desired output of the digital circuit design. Randomizing the logic associated with a dangling node can include deleting a logic gate, adding a logic gate, replacing a logic gate with another logic gate, etc. Randomizing the logic associated with the dangling node prevents hardware trojans that may have been inserted into the circuit design from being implemented in a circuit that is generated based upon the design.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

A Water Vapor Differential Absorption LIDAR Design for Unpiloted Aerial Vehicles

This system study proposes the deployment of a water vapor Differential Absorption LIDAR (DIAL) system on an Altair unmanned aerial vehicle (UAV) platform. The Altair offers improved payload weight and volume performance, and longer total flight time as compared to other commercial UAV's. This study has generated a preliminary design for an Altair based water vapor DIAL system. The design includes a proposed DIAL schematic, a review of mechanical challenges such as temperature and humidity stresses on UAV deployed DIAL systems, an assessment of the available capacity for additional instrumentation (based on the proposed design), and an overview of possible weight and volume improvements associated with the use of customized electronic and computer hardware, and through the integration of advanced fiber-optic and laser products. The results of the study show that less than 17% of the available weight, less than 19% of the volume capacity, and approximately 11% of the electrical capacity is utilized by the proposed water vapor DIAL system on the Altair UAV.

DeYoung, Russell J.↗
NASA NTRS1977

Development of a character, line and point display system

A compact graphics terminal for use as the input to a computerized medical records system is described. The principal mode of communication between the terminal and the records system is by checklists and menu selection. However, the terminal accepts short, handwritten messages as well as conventional alphanumeric input. The terminal consists of an electronic tablet, a display, a microcomputer controller, a character generator, and a refresh memory for the display. An Intel SBC 80/10 microcomputer controls the flow of information and a 16 kilobyte memory stores the point-by-point array of information to be displayed. A specially designed interface continuously generates the raster display without the intervention of the microcomputer.

Owen, E. W.↗
NASA NTRS1972

Engineering study for the functional design of a multiprocessor system

The results are presented of a study to generate a functional system design of a multiprocessing computer system capable of satisfying the computational requirements of a space station. These data management system requirements were specified to include: (1) real time control, (2) data processing and storage, (3) data retrieval, and (4) remote terminal servicing.

Miller, J. S.↗
NASA NTRS1975

Development of a solar-powered residential air conditioner: Screening analysis

Screening analysis aimed at the definition of an optimum configuration of a Rankine cycle solar-powered air conditioner designed for residential application were conducted. Initial studies revealed that system performance and cost were extremely sensitive to condensing temperature and to the type of condenser used in the system. Consequently, the screening analyses were concerned with the generation of parametric design data for different condenser approaches; i. e., (1) an ambient air condenser, (2) a humidified ambient air condenser (3) an evaporative condenser, and (4) a water condenser (with a cooling tower). All systems feature a high performance turbocompressor and a single refrigerant (R-11) for the power and refrigeration loops. Data were obtained by computerized methods developed to permit system characterization over a broad range of operating and design conditions. The criteria used for comparison of the candidate system approaches were (1) overall system COP (refrigeration effect/solar heat input), (2) auxiliary electric power for fans and pumps, and (3) system installed cost or cost to the user.

Source record↗
NASA NTRS2012

Resource Management and Contingencies in Aerospace Concurrent Engineering

significant concern in designing complex systems implementing new technologies is that while knowledge about the system is acquired incrementally, substantial financial commitments, even make-or-break decisions, must be made upfront, essentially in the unknown. One practice that helps in dealing with this dichotomy is the smart embedding of contingencies and margins in the design to serve as buffers against surprises. This issue presents itself in full force in the aerospace industry, where unprecedented systems are formulated and committed to as a matter of routine. As more and more aerospace mission concepts are generated by concurrent design laboratories, it is imperative that such laboratories apply well thought-out contingency and margin structures to their designs. The first part of this publication provides an overview of resource management techniques and standards used in the aerospace industry. That is followed by a thought provoking treatise on margin policies. The expose presents the actual flight telemetry data recorded by the thermal discipline during several recent NASA Goddard Space Flight Center missions. The margins actually achieved in flight are compared against pre-flight predictions, and the appropriateness and the ramifications of having designed with rigid margins to bounding stacked worst case conditions are assessed. The second half of the paper examines the particular issues associated with the application of contingencies and margins in the concurrent engineering environment. In closure, a discipline-by-discipline disclosure of the contingency and margin policies in use at the Integrated Design Center at NASA s Goddard Space Flight Center is made.

Karpati, Gabe↗
NASA NTRS2013

Issues and Strategies in Solving Multidisciplinary Optimization Problems

Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions can be produced by all the three methods. The variation in the weight calculated by the methods was found to be modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Patnaik, Surya↗
NASA NTRS2012

Multi-Objective Optimization of a Turbofan for an Advanced, Single-Aisle Transport

Considerable interest surrounds the design of the next generation of single-aisle commercial transports in the Boeing 737 and Airbus A320 class. Aircraft designers will depend on advanced, next-generation turbofan engines to power these airplanes. The focus of this study is to apply single- and multi-objective optimization algorithms to the conceptual design of ultrahigh bypass turbofan engines for this class of aircraft, using NASA s Subsonic Fixed Wing Project metrics as multidisciplinary objectives for optimization. The independent design variables investigated include three continuous variables: sea level static thrust, wing reference area, and aerodynamic design point fan pressure ratio, and four discrete variables: overall pressure ratio, fan drive system architecture (i.e., direct- or gear-driven), bypass nozzle architecture (i.e., fixed- or variable geometry), and the high- and low-pressure compressor work split. Ramp weight, fuel burn, noise, and emissions are the parameters treated as dependent objective functions. These optimized solutions provide insight to the ultrahigh bypass engine design process and provide information to NASA program management to help guide its technology development efforts.

Berton, Jeffrey J.↗
NASA NTRS2010

From Paper to Production: An Update on NASA's Upper Stage Engine for Exploration

The NASA/industry team responsible for developing the J-2X Upper Stage Engine for the Constellation Program's Ares I and Ares V launch vehicles has made significant progress toward moving the design from paper to production during the past year. The J-2X exemplifies the Constellation goal of using proven technology and experience from more than 50 years of United States spaceflight experience and seeking where possible to employ common hardware in the Ares I crew launch vehicle and the Ares V cargo launch vehicle. The J-2X will power the Ares I upper stage to place the Orion crew vehicle in orbit. For the Ares V, the J-2X will place the Earth departure stage (EDS) and lunar lander in orbit and later re-start to send the Orion and lander to the Moon. Pratt & Whitney Rocketdyne (PWR) is under contract to develop and produce the engine, leveraging its flight-proven LH2/LOX, gas generator cycle J-2 and RS-68 engine capabilities, recent experience with the X-33 aerospike XRS-2200 engine, and development knowledge of the J-2S tap-off cycle engine. The J-2X employs a gas generator operating cycle designed to produce 294,000 pounds of thrust in primary operating mode for the Ares I and Ares V ascent phases. It also has a secondary mode, during which it operates at 80 percent thrust by altering its mixture ratio to perform the TLI burn for the Ares V lunar sortie and lunar cargo missions. The J-2X development philosophy is based on proven hardware, an aggressive development schedule, and early risk reduction. NASA Marshall Space Flight Center (MSFC) and PWR began development of the J-2X in June 2006. The government/industry team of more than 600 people within NASA and PWR successfully completed the Critical Design Review (CDR) in November 2008, following extensive risk mitigation testing. The team is working toward a first flight of the J-2X on the Orion 1 mission in 2014. This paper will discuss the J-2X development background and provide top-level information on design and testing to date. Details will be provided on overcoming challenges such as gas generator instability, turbine blade life, and nozzle extension selection and materials.

Kynard, Mike↗
NASA NTRS2008

Cassini's Maneuver Automation Software (MAS) Process: How to Successfully Command 200 Navigation Maneuvers

To keep Cassini on its complex trajectory, more than 200 orbit trim maneuvers (OTMs) have been planned from July 2004 to July 2010. With only a few days between many of these OTMs, the operations process of planning and executing the necessary commands had to be automated. The resulting Maneuver Automation Software (MAS) process minimizes the workforce required for, and maximizes the efficiency of, the maneuver design and uplink activities. The MAS process is a well-organized and logically constructed interface between Cassini's Navigation (NAV), Spacecraft Operations (SCO), and Ground Software teams. Upon delivery of an orbit determination (OD) from NAV, the MAS process can generate a maneuver design and all related uplink and verification products within 30 minutes. To date, all 112 OTMs executed by the Cassini spacecraft have been successful. MAS was even used to successfully design and execute a maneuver while the spacecraft was in safe mode.

Yang, Genevie Velarde↗
DOE OSTI2022

Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model

Abstract The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Developing the Next Generation of High-Performance Solid-State Batteries

The project team conducted cutting-edge battery research on electrode materials, electrolyte formulations, and cell designs for next-generation rechargeable lithium metal batteries designed for high energy density and safety. The research has focused on two separate but related technologies: 1) a high-temperature lithium metal battery designed for extreme environments, and 2) a high-energy lithium metal battery designed for more general applications (including aerospace, defense, transportation, electronics, etc.). We took these projects from the conceptual stage (an idea on paper) all the way to high performing lab prototypes and early commercial-format pouch and cylindrical cell prototypes. Both chemistries were improved substantially in terms of materials compatibility, lithium metal cyclability, high-voltage stability, high-temperature stability, and scalability.

25 ENERGY STORAGE↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗