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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 1,243 records · Page 69

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NASA NTRS1996

Aerodynamic Shape Optimization of Supersonic Aircraft Configurations via an Adjoint Formulation on Parallel Computers

This work describes the application of a control theory-based aerodynamic shape optimization method to the problem of supersonic aircraft design. The design process is greatly accelerated through the use of both control theory and a parallel implementation on distributed memory computers. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods (13, 12, 44, 38). The resulting problem is then implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) Standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on higher order computational fluid dynamics methods (CFD). In our earlier studies, the serial implementation of this design method (19, 20, 21, 23, 39, 25, 40, 41, 42, 43, 9) was shown to be effective for the optimization of airfoils, wings, wing-bodies, and complex aircraft configurations using both the potential equation and the Euler equations (39, 25). In our most recent paper, the Euler method was extended to treat complete aircraft configurations via a new multiblock implementation. Furthermore, during the same conference, we also presented preliminary results demonstrating that the basic methodology could be ported to distributed memory parallel computing architectures [241. In this paper, our concem will be to demonstrate that the combined power of these new technologies can be used routinely in an industrial design environment by applying it to the case study of the design of typical supersonic transport configurations. A particular difficulty of this test case is posed by the propulsion/airframe integration.

Reuther, James↗

NASA NTRS2004

Framework for Development of Object-Oriented Software

The Real-Time Control (RTC) Application Framework is a high-level software framework written in C++ that supports the rapid design and implementation of object-oriented application programs. This framework provides built-in functionality that solves common software development problems within distributed client-server, multi-threaded, and embedded programming environments. When using the RTC Framework to develop software for a specific domain, designers and implementers can focus entirely on the details of the domain-specific software rather than on creating custom solutions, utilities, and frameworks for the complexities of the programming environment. The RTC Framework was originally developed as part of a Space Shuttle Launch Processing System (LPS) replacement project called Checkout and Launch Control System (CLCS). As a result of the framework s development, CLCS software development time was reduced by 66 percent. The framework is generic enough for developing applications outside of the launch-processing system domain. Other applicable high-level domains include command and control systems and simulation/ training systems.

Perez-Poveda, Gus↗

NASA NTRSDate not supplied

A New Laser Transmitter for Methane and Water Vapor Measurements at 1.65 μm

Atmospheric methane trends over the last few years have been increasing at a rate of 7-12 parts per billion (ppb) per year after brief a pause in the first decade of this century. The reasons for the pause and subsequent increase remains unclear. Thus, there is a critical need for additional, precise and accurate methane observations to understand the natural and anthropogenic processes that drive the trends in atmospheric methane and to constrain its sources, and sinks. At NASA Goddard Space Flight Center (GSFC), in collaboration with Freedom Photonics Inc., we have been developing a lidar to measure atmospheric methane using Integrated Path Differential Absorption (IPDA) from an airborne platform as a precursor to a future space mission. In this paper we present the design of a laser transmitter operating at ~1651 nmbased on a newly developed Distributed Bragg Grating (DBR) seed laser and an Optical parametric oscillator (OPO). The DBR is rapidly step-tuned over the methane absorption at several discrete wavelengths. This multi-wavelength approach enables us to sample the entire methane lineshape and reduce systematic errors.

Atmospheric methane trends↗

DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Quasi-isochronous muon collection channels

Intense muon beams have many potential commercial and scientific applications, ranging from low-energy investigations of the basic properties of matter using spin resonance to large energy-frontier muon colliders. However, muons originate from a tertiary process that produces a diffuse swarm. To make useful beams, the swarm must be rapidly captured and cooled before the muons decay. In this STTR project a promising new concept for the collection and cooling of muon beams to increase their intensity and reduce their emittances was investigated, namely, the use of a nearly isochronous helical cooling channel (HCC) to facilitate capture of the muons into RF bunches. The muon beam can then be cooled quickly and coalesced efficiently to optimize the luminosity of a muon collider, or could provide compressed muon beams for other applications. Optimal ways to integrate such a subsystem into the rest of a muon collection and cooling system, for collider and other applications, were developed by analysis and simulation. The application of quasi-isochronous helical cooling channels (QIHCC) for RF capture of muon beams was developed. Innovative design concepts for a channel incorporating straight solenoids, a matching section, and an HCC, including RF and absorber, were developed, and its subsystems were simulated. Additionally, a procedure that uses an HCC to combine bunches for a muon collider was invented and simulated. Difficult design aspects such as matching sections between subsystems and intensity-dependent effects were addressed. The bunch recombination procedure was developed into a complete design with 3-D simulations. Bright muon beams are needed for many commercial and scientific reasons. Potential commercial applications include low-dose radiography, muon catalyzed fusion, and the use of muon beams to screen cargo containers for homeland security. Scientific uses include low energy beams for rare process searches, muon spin resonance applications, muon beams for neutrino factories, and muon colliders as Higgs factories or energy-frontier discovery machines.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

High-Z Sensitized Plastic Scintillators: A Review

The need for affordable and reliable radiation detectors has prompted significant investment in new radiation detector materials, due to concerns about national security and nuclear nonproliferation. Plastic scintillators provide an affordable approach to large volume detectors, yet their performance for high-energy gamma radiation is severely limited by the small radiation stopping power inherent to their low atomic number. Although some sensitization attempts with organometallics were made in the 1950s to 1960s, the concomitant decrease in light yield has limited the usefulness of these sensitized detectors. Recently, with new knowledge gained during the rapid development of organic optoelectronics and nanotechnology, there has been a revived interest in the field of heavy element sensitized plastic scintillators. In this paper, the recent efforts on sensitized plastic scintillators are summarized. Basic scintillator physics is first reviewed. The discussion then focuses on two major thrusts in the field: sensitization with: (1) organometallics and (2) oxide and fluoride nanoparticles. The design rationales and major results are examined in detail, with existing limitations and possible future pathways discussed. Lastly, special attention is paid to the underlying energy deposition and transfer processes, as these determine the key performance metrics such as light yield and radioluminescence decay lifetime.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams

Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Research Update: Atmospheric pressure spatial atomic layer deposition of ZnO thin films: Reactors, doping, and devices

Atmospheric pressure spatial atomic layer deposition (AP-SALD) has recently emerged as an appealing technique for rapidly producing high quality oxides. Here, we focus on the use of AP-SALD to deposit functional ZnO thin films, particularly on the reactors used, the film properties, and the dopants that have been studied. We highlight how these films are advantageous for the performance of solar cells, organometal halide perovskite light emitting diodes, and thin-film transistors. Future AP-SALD technology will enable the commercial processing of thin films over large areas on a sheet-to-sheet and roll-to-roll basis, with new reactor designs emerging for flexible plastic and paper electronics.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Simulator for an Accelerator-Driven Subcritical Fissile Solution System

LANL has developed a process to generate a progressive family of system models for a fissile solution system. This family includes a dynamic system simulation comprised of coupled nonlinear differential equations describing the time evolution of the system. Neutron kinetics, radiolytic gas generation and transport, and core thermal hydraulics are included in the DSS. Extensions to explicit operation of cooling loops and radiolytic gas handling are embedded in these systems as is a stability model. The DSS may then be converted to an implementation in Visual Studio to provide a design team the ability to rapidly estimate system performance impacts from a variety of design decisions. This provides a method to assist in optimization of the system design. Once design has been generated in some detail the C++ version of the system model may then be implemented in a LabVIEW user interface to evaluate operator controls and instrumentation and operator recognition and response to off-normal events. Taken as a set of system models the DSS, Visual Studio, and LabVIEW progression provides a comprehensive set of design support tools.

42 ENGINEERING↗

NASA NTRS1978

Mean gravity anomalies and sea surface heights derived from GEOS-3 altimeter data

Approximately 2000 GEOS-3 altimeter arcs were analyzed to improve knowledge of the geoid and gravity field. An adjustment procedure was used to fit the sea surface heights (geoid undulations) in an adjustment process that incorporated cross-over constraints. The error model used for the fit was a one or two parameter model which was designed to remove altimeter bias and orbit error. The undulations on the adjusted arcs were used to produce geoid maps in 20 regions. The adjusted data was used to derive 301 5 degree equal area anomalies and 9995 1 x 1 degree anomalies in areas where the altimeter data was most dense, using least squares collocation techniques. Also emphasized was the ability of the altimeter data to imply rapid anomaly changes of up to 240 mgals in adjacent 1 x 1 degree blocks.

Rapp, R. H.↗

NASA NTRS1991

Asteroid exploration and utilization: The Hawking explorer

The Earth is nearing depletion of its natural resources at a time when human beings are rapidly expanding the frontiers of space. The resources which may exist on asteroids could have enormous potential for aiding and enhancing human space exploration as well as life on Earth. With the possibly limitless opportunities that exist, it is clear that asteroids are the next step for human existence in space. This report comprises the efforts of NEW WORLDS, Inc. to develop a comprehensive design for an asteroid exploration/sample return mission. This mission is a precursor to proof-of-concept missions that will investigate the validity of mining and materials processing on an asteroid. Project STONER (Systematic Transfer of Near Earth Resources) is based on two utilization scenarios: (1) moving an asteroid to an advantageous location for use by Earth; and (2) mining an asteroids and transporting raw materials back to Earth. The asteroid explorer/sample return mission is designed in the context of both scenarios and is the first phase of a long range plane for humans to utilize asteroid resources. The report concentrates specifically on the selection of the most promising asteroids for exploration and the development of an exploration scenario. Future utilization as well as subsystem requirements of an asteroid sample return probe are also addressed.

Carlson, Alan↗

NASA NTRS2016

Design and Development Comparison of Rapid Cycle Amine 1.0, 2.0, and 3.0

The development of the Rapid Cycle Amine (RCA) swing-bed technology for carbon dioxide (CO2) removal has been in progress since favorable results were published in 1996. Shortly thereafter, a prototype was designed, developed, and tested successfully and delivered to Johnson Space Center in 1999. An improved prototype (RCA 1.0) was delivered to NASA in 2006 and sized for the extravehicular activity (EVA). The RCA swing-bed technology is a regenerative system which employs two alternating solid-amine sorbent beds to remove CO2 and water. The two-bed design employs a chemisorption process whereby the beds alternate between adsorption and desorption. This process provides for an efficient RCA operation that enables one bed to be in adsorb (uptake) mode, while the other is in the desorb (regeneration) mode. The RCA has progressed through several iterations of technology readiness levels. Test articles have now been designed, developed, and tested for the advanced space suit portable life support system (PLSS) including RCA 1.0, RCA 2.0, and RCA 3.0. The RCA 3.0 was the most recent RCA fabrication and was delivered to NASA-JSC in June 2015. The RCA 1.0 test article was designed with a pneumatically actuated linear motion spool valve. The RCA 2.0 and 3.0 test articles were designed with a valve assembly which allows for switching between uptake and regeneration modes while minimizing gas volume losses to the vacuum source. RCA 2.0 and 3.0 also include an embedded controller design to control RCA operation and provide the capability of interfacing with various sensors and other ventilation loop components. The RCA technology is low power, small, and has fulfilled all test requirements levied upon the technology during development testing thus far. This paper will provide an overview of the design and development of RCA 1.0, 2.0 and 3.0 including detail differences between the design specifications of each. Nomenclature.

Chullen, Cinda↗

DOE OSTI2019

Control of Physical and Chemical Processes with Nonlocal Metal–Dielectric Environments

In this report, we make the case that (meta) material platforms that were originally designed to control the propagation of light can affect scores of physical and chemical phenomena, which are often thought to lie outside of the traditional electrodynamics domain. We show that nonlocal metal-dielectric environments, which can be as simple as metal–dielectric interfaces, can control spontaneous and stimulated emission, Förster energy transfer, wetting contact angle, and rates of chemical reactions. The affected phenomena can occur in both strong and weak coupling regimes and the large coupling strength seems to enhance the effects of nonlocal environments. This intriguing field of study has experienced a rapid growth over the past decade and many exciting discoveries and applications are expected in the years to come.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗

DOE OSTI2021

Thermal Evolution of Internal Strain in Doped PbTe

Recent improvements in the efficiency of heat-to-electricity energy conversion in lead chalcogenide thermoelectrics involve reducing the thermal conductivity by incorporating large amounts of internal strain. The extent to which typical lead chalcogenide processing techniques (such as doping, ball milling, and densification) increase internal strain and dislocation density must be quantified to improve materials design. In this study, neutron powder diffraction is leveraged to evaluate the internal strain introduced by ball milling in doped and undoped powders. Doping with Na and/or Eu increases internal strain beyond ball milling alone, with the greatest increase from combining the two dopants. Strain recovery occurs in each powder above 400 K but can be suppressed by co-doping, indicating a strong dopant–dislocation interaction in this system. Therefore, high-temperature processing of PbTe powders should be avoided if high internal strain is desired. Low-temperature densification and/or rapid pressing techniques may be key to maintaining internal strain in the final pressed pellet. The diffraction peak asymmetry and correlated elastic softening measured in pressed PbTe pellets in past studies were not observed in the precursor powders measured here, suggesting that measurements of the Debye temperature on final pressed pellets are required to examine the influence of defect-induced elastic softening on thermal conductivity. This work provides key guidance for defect engineering to maximize internal strain and thermoelectric performance in PbTe thermoelectrics.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Targeted materials discovery using Bayesian algorithm execution

Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of the design space which meet more complex or specialized goals. We present a framework that captures experimental goals through straightforward user-defined filtering algorithms. These algorithms are automatically translated into one of three intelligent, parameter-free, sequential data collection strategies (SwitchBAX, InfoBAX, and MeanBAX), bypassing the time-consuming and difficult process of task-specific acquisition function design. Our framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision making. We demonstrate this approach on datasets for TiO 2 nanoparticle synthesis and magnetic materials characterization, and show that our methods are significantly more efficient than state-of-the-art approaches. Overall, our framework provides a practical solution for navigating the complexities of materials design, and helps lay groundwork for the accelerated development of advanced materials.

42 ENGINEERING↗

DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗