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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 433 records · Page 24

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement and Transition to MODIS

Study of the environment has historically been done with observations and measurements in relatively few local areas. While some of these have been done over long time spans, most have not. The NOAA/NASA Pathfinder project was initiated to complement these data sets with satellite data that can provide information over larger spatial areas and longer time spans. The AVHRR Polar Pathfinder (APR) program was part of this project. The APR was to supply data from the NOAA AVHRR instruments that was consistently generated in a format usable to a wide range of scientific investigators. A grant was obtained from the NASA Research Announcement 97-MTPE-03 to evaluate the APP products, to provide any enhancements, and to compare with products from the new MODIS instrument. There was about a two year overlap between the projects, and this validation effort had several impacts on the APP products. The APP products are derived from the instruments aboard 4 NOAA satellites, NOAA-7, 9, 11, and 14. Initial validation efforts compared the thermal calibrations of these instruments, and differences are found. Calibration has undergone many revisions and techniques have changed since the satellites were launched. The first calibration methods were optimized for global ocean temperatures, as this was one of the primary and important uses of the AVHRR instruments. As the APP program started, newer methods that provided more accurate temperature retrievals over a wider range of temperatures were being developed. The calibration of a wider range of temperatures were necessary because of the extremely low values in the polar regions. These methods were also designed so that calibrated data was also consistent between all the NOAA satellites. These newer calibration methods were then adopted primarily because of the initial finding of this validation effort.

Fowler, Charles↗

A Parametric Geometry Computational Fluid Dynamics (CFD) Study Utilizing Design of Experiments (DOE)

Design of Experiments (DOE) was applied to the LAS geometric parameter study to efficiently identify and rank primary contributors to integrated drag over the vehicles ascent trajectory in an order of magnitude fewer CFD configurations thereby reducing computational resources and solution time. SME s were able to gain a better understanding on the underlying flowphysics of different geometric parameter configurations through the identification of interaction effects. An interaction effect, which describes how the effect of one factor changes with respect to the levels of other factors, is often the key to product optimization. A DOE approach emphasizes a sequential approach to learning through successive experimentation to continuously build on previous knowledge. These studies represent a starting point for expanded experimental activities that will eventually cover the entire design space of the vehicle and flight trajectory.

Rhew, Ray D.↗

Mars Ascent Vehicle-First Stage Motor

This project is development effort of a first stage solid motor based on a two-stage solid motor Mars Ascent Vehicle (MAV) design for the robotic Mars Sample Return (MSR) mission (fig. 1). The MSR MAV has been studied for decades and multiple concepts have been shown to meet the mission objectives as posed.1 However, there remains significant uncertainty with the MAV requirements. The sample container and sample cache itself is immature. Additionally, MAV-specific requirements ranging from full three-axis controlled and strict communication requirements to minimal capability concepts are still under consideration. Given the maturity of the overall mission requirements, the MAV has been limited to a large number of parametric analyses and paper studies. Recently, a Jet Propulsion Laboratory study highlighted the flexibility of a two-stage solid motor concept. The MAV itself is driven by the constraints of the Entry, Decent, and Landing (EDL) system. Within the EDL constraints, there is a range of MAV options ranging in complexity from simple spun upper stage options to higher capability three-axis controlled solutions. There are also options to trade the ratio of mission (Delta)V between the first and second stage. Finally, sensitivity studies also indicated that solid motors with a high percentage of off-load flexability only had minor impact on the total system mass over a single point design optimized motor. This flexibility in the first stage motor has allowed NASA to mature the design of the motor beyond parametric analyses and start to address known design challenges of the motor.

Dankanich, John↗

Improved 140 Nd Production for the 140 Nd/ 140 Pr In Vivo Generator through Target Recycling and Radiochemical Optimization

Theranostic strategies that utilize f-block therapeutic radionuclides, including 161 Tb, 177 Lu, 225 Ac, and 227 Th, suffer from a shortage of positron emission tomography (PET) imaging counterparts in the same chemical space and often rely on 68 Ga as a surrogate. The 140 Nd/ 140 Pr in vivo PET generator, which belongs to the f-block, may address this issue and can be produced via the 141 Pr(p,2n) 140 Nd production route by using medium-energy cyclotrons. However, impurities in the target material, including stable Nd, and the inherent difficulty of adjacent lanthanide separations limit the achievable radionuclidic and chemical purity of 140 Nd. In this work, we address these challenges through the purification and recycling of praseodymium target material and optimization of Nd/Pr separation. The resulting purified 140Nd was evaluated using DOTA and Macropa chelators via radiolabeling and in vitro stability studies. A target material purification and recycling method was developed for the monoisotopic 141 Pr starting material to remove stable Nd impurities, yielding 90.3 ± 4.7% (n = 3) recovery. The purified 141 Pr was isolated as Pr 6 O 11 and irradiated with 24 MeV protons (20.07 MeV at the target surface) at 20 μA for 4 h, which produced 1417.0 ± 83.4 MBq (38.3 ± 2.2 mCi) of 140 Nd at the end of bombardment (EOB). The produced 140 Nd was purified through an optimized DGA normal method to recover 71.6 ± 6.3% pure 140 Nd. The amount of stable Nd reduced progressively in each target purification cycle from >340 ppm without purification to <250 ppb after three cycles, while other measured metallic impurities were below 30 ppb. This improvement in target purity was reflected in the direct increase of apparent molar activity (AMA), when purified 140 Nd was evaluated with DOTA and Macropa chelators. AMA of [ 140 Nd]Nd-DOTA and [ 140 Nd]Nd-Macropa increased from 70.3 MBq/μmol (1.9 mCi/μmol) and 74 MBq/μmol (2.0 mCi/μmol) to 8025.3 MBq/μmol (216.9 mCi/μmol) and 8473.0 MBq/μmol (229.0 mCi/μmol), respectively, after the third target purification cycle. Further evaluation of chelator-labeled 140 Nd showed that [ 140 Nd]Nd-DOTA was stable in phosphate-buffered saline (PBS), saline, human serum, and mouse serum, whereas [140Nd]Nd-Macropa was stable in all except human serum. This work established a practical methodological advance for the production of 140 Nd/ 140 Pr in vivo PET generators, combining optimized target recycling and radiochemical separation to enable scaled-up and high-molar activity 140 Nd suitable for preclinical imaging. These advances support broader development of 140 Nd/ 140 Pr as a robust PET analogue, especially for f-block therapeutics.

Irradiation↗

Additive manufacturing system and method having toolpath analysis

An additive manufacturing (AM) system is disclosed for constructing a three dimensional (3D) part with optimized orthotropy. The system combines an electronic processor which calculates an optimal set of physically achievable toolpaths to meet a given design objective, and a 3D printing direct ink write machine capable of printing inks with reinforcing particles that result in orthotropic materials. The electronic processor may combine a Domain of Interest subsystem that transforms a mathematical description of a desired part orthotropy to a plurality of guidepaths, a toolpath generate subsystem that develops a plurality of physically realizable toolpaths from those guidepaths with a minimum number of starts and stops, a finite element subsystem that computes spatially varying material orthotropy from those toolpaths and then solves a boundary value problem to determine a figure of merit for the design, and an optimization subsystem that uses that figure of merit to update the mathematical description of the part orthotropy to iteratively develop an improved part. The optimization subsystem also includes convergence criteria to indicate when toolpaths have been achieved that yield a sufficiently optimal part has been achieved. The toolpath generate can then output the final toolpaths, which are converted to suitable code that controls the motion of the 3D printer toolhead and allows the optimized 3D part to be manufactured.

King, Michael J.↗

PSTN-055: Survey Cadence Optimization Committee's Phase 2 Recommendations

This document describes the recommendations formulated by the Survey Cadence Optimization Committee (SCOC) of Vera C. Rubin Observatory for the observing strategy of the Legacy Survey of Space and Time (LSST). These "Phase 2" recommendations follow the initial "Phase 1" recommendations released in December 2021 as PSTN-053, and convey the current recommendations for the initial implementation of the LSST. These recommendations are based on the SCOC analysis of LSST simulations generated according to PSTN-053 and the feedback received from the scientific community on those simulations. These recommendations should be considered as the current guidance for implementing the LSST observing survey at the start of the survey, a strategy to be reviewed regularly over the survey lifetime, and are accompanied by a simulation, baseline_v3.0, which represents a specific implementation of these recommendations. While these recommendations dramatically narrow the possible LSST observing parameter choices, we emphasize that at this stage they do not yet represent a final or complete set of recommendations for the survey strategy, and several details are still to be refined. Furthermore, the strategy should be considered "living" and subject to evolution throughout the survey. The SCOC continues to engage with the community to finalize its recommendations. At the time of the release of this document, the final phases of construction of Rubin Observatory are ongoing with an expected first light in mid-2024. We expect the SCOC recommendations to be revised as needed, as knowledge of the system as built and the outcome of commissioning and Science Verification mature. This document describes the Phase 2 SCOC recommendations —highlighting elements that can be considered final and elements that remain to be finalized—, the process through which the SCOC has converged on these recommendations, and the working plan for the SCOC starting in January 2023 through the start of the survey to finalize the initial implementation of the Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗

The surface chemistry of the atomic layer deposition of metal thin films

Abstract In this perspective we discuss the progress made in the mechanistic studies of the surface chemistry associated with the atomic layer deposition (ALD) of metal films and the usefulness of that knowledge for the optimization of existing film growth processes and for the design of new ones. Our focus is on the deposition of late transition metals. We start by introducing some of the main surface-sensitive techniques and approaches used in this research. We comment on the general nature of the metallorganic complexes used as precursors for these depositions, and the uniqueness that solid surfaces and the absence of liquid solvents bring to the ALD chemistry and differentiate it from what is known from metalorganic chemistry in solution. We then delve into the adsorption and thermal chemistry of those precursors, highlighting the complex and stepwise nature of the decomposition of the organic ligands that usually ensued upon their thermal activation. We discuss the criteria relevant for the selection of co-reactants to be used on the second half of the ALD cycle, with emphasis on the redox chemistry often associated with the growth of metallic films starting from complexes with metal cations. Additional considerations include the nature of the substrate and the final structural and chemical properties of the growing films, which we indicate rarely retain the homogeneous 2D structure often aimed for. We end with some general conclusions and personal thoughts about the future of this field.

Materials Science↗

RISE: robust iterative surface extension for sub-nanometer X-ray mirror fabrication

Precision optics have been widely required in many advanced technological applications. X-ray mirrors, as an example, serve as the key optical components at synchrotron radiation and free electron laser facilities. They are rectangular silicon or glass substrates where a rectangular Clear Aperture (CA) needs to be polished to sub-nanometer Root Mean Squared (RMS) to keep the imaging capability of the incoming X-ray wavefront at the diffraction limit. The convolutional polishing model requires a CA to be extended with extra data, from which the dwell time is calculated via deconvolution. However, since deconvolution is very sensitive to boundary errors and noise, the existing surface extension methods can hardly fulfill the sub-nanometer requirement. On one hand, the figure errors in a CA were improperly modeled during the extension, leading to continuity issues along the boundary. On the other hand, uncorrectable high-frequency errors and noise were also extended. In this study, we propose a novel Robust Iterative Surface Extension (RISE) method that resolves these problems with a data fitting strategy. RISE models the figure errors in a CA with orthogonal polynomials and ensures that only correctable errors are fit and extended. Combined with boundary conditions, an iterative refinement of dwell time is then proposed to compensate the errors brought by the extension and deconvolution, which drastically reduces the estimated figure error residuals in a CA while the increase of total dwell time is negligible. To our best knowledge, RISE is the first data fitting-based surface extension method and is the first to optimize dwell time based on iterative extension. An experimental verification of RISE is given by fabricating two elliptic cylinders (10 mm × 80 mm CAs) starting from a sphere with a radius of curvature around 173 m using ion beam figuring. The figure errors in the two CAs greatly improved from 204.96 nm RMS and 190.28 nm RMS to 0.62 nm RMS and 0.71 nm RMS, respectively, which proves that RISE is an effective method for sub-nanometer level X-ray mirror fabrication.

36 MATERIALS SCIENCE↗

Primer for OTERR Core Reloading Optimization

OTERR (Optimization of Test Reactor Reloading) is a software tool which assists in finding optimal fuel assembly reloading patterns for nuclear reactors. It was created specifically to support the Versatile Test Reactor (VTR) program, but its functionality is general enough to be applied to most fast spectrum reactors which use hexagonal prismatic fuel elements. This document is meant to be a primer for new users of OTERR to walk through example workflows for core reloading optimization cases. Simple cases are followed step-by-step to discuss what needs to be done to complete a reloading optimization sequence. Note that the intent of this document is to provide practical examples for users to follow along with so they can quickly start using OTERR and then make changes to fit their own modeling needs. Detail is limited in terms of addressing additional features not used in these examples and especially lacking in discussion of theory used in the code. To better address these points, users are highly encouraged to refer to the OTERR User Manual and the OTERR Theory Manual.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

High-Temperature Gas-Cooled Reactor Research Survey and Overview: Preliminary Data Platform Construction for the Nuclear Energy University Program

Since the U.S. Department of Energy Office of Nuclear Energy initiated the Nuclear Energy University Program (NEUP) in 2009, there are 29 NEUP projects focusing on high-temperature gas-cooled reactor (HTGR) research up to July 2022. The resultant research product, either experimental or computational, were published as final NEUP reports, journal articles and conference proceedings. However, these federally funded products have been scattered and sometimes cannot be easily accessed. To improve access to this valuable HTGR validation data and optimize the return on the significant investment made by the Department of Energy, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects to develop a public-access database specific for HTGRs applications that can be used to retrieve computational fluid dynamics and system code validation data. This effort will help guide future NEUP-funded research, define new state of the ART Phenomena Identification and Ranking Table (PIRT), and promote the usage of this data in the codes validation matrices. This report provides an overview of the NEUP-funded HTGR-related research projects from Fiscal Year (FY) 2009–2021 and identifies validation knowledge gaps still existing in HTGR thermal-fluid research. A preliminary data platform has been developed for the 29 NEUP projects investigating HTGR thermal hydraulics, including their final reports as well as the available scientific publications. As an ultimate goal for this work, the ART-GCR program will create a central database at Idaho National Laboratory to identify, organize, and store these datasets generated by experimental investigations or computational models, experimental facility descriptions, and publicly-available academic products from the HTGR-related NEUP projects and provide future guidance for the storage and transmission of important project documentations for later NEUP projects as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Inert gas thrusters

Inert gases are of interest as possible alternatives to the usual electric thruster propellants of mercury and cesium. The multipole discharge chamber investigated was shown capable of low discharge chamber losses and flat ion beam profiles with a minimum of optimization. Minimum discharge losses were 200 to 250 eV/ion for xenon and 300 to 350 eV/ion for argon, while flatness parameters in the plane of the accelerator grid were 0.85 to 0.95. The design used employs low magnetic field strengths, which permits the use of sheet-metal parts. The corner problem of the discharge chamber was resolved with recessed corner anodes, which approximately equalized both the magnetic field above the anodes and the electron currents to these anodes. Argon hollow cathodes were investigated at currents up to about 5 amperes using internal thermionic emitters. Cathode chamber diameter optimized in the 1.0 to 2.5 cm range, while orifices diameter optimized in the 0.5 to 5 mm range. The use of a bias voltage for the internal emitter extended the operating range and facilitated starting. The masses of 15 and 30 cm flight type thrusters were estimated at about 4.2 and 10.8 kg.

Kaufman, H. R.↗

The Epic Chronicle of Designing Cassini's Titan Flyby Altitudes

The selection and optimization of Titan flyby altitudes for NASA's Cassini mission at Saturn has traveled a long, fascinating, and often torturous sixteen-year path - starting in 2001, when pre-arrival trajectory design decisions had to be made, through April of 2017 when Cassini's last, and arguably most critical, low flyby takes place. The chronicle of designing and updating the Titan flyby altitudes have twists and turns enough to satisfy a full-length novel or feature film, including: critical design decision-making before arrival with multiple atmospheric models, high uncertainties, and limited data; early flybys that seemed to show trends that weren't there; use and misuse of statistical analysis; unexpected surprises with limited reaction time; navigation of a scientific, engineering, and management community with a wide array of inherent biases; and consideration of a variety of project risk postures in a high-scrutiny, high-impact, high-reward environment.

Bittner, Molly↗

On the energy landscape of symmetric quantum signal processing

Symmetric quantum signal processing provides a parameterized representation of a real polynomial, which can be translated into an efficient quantum circuit for performing a wide range of computational tasks on quantum computers. For a given polynomial f , the parameters (called phase factors) can be obtained by solving an optimization problem. However, the cost function is non-convex, and has a very complex energy landscape with numerous global and local minima. It is therefore surprising that the solution can be robustly obtained in practice, starting from a fixed initial guess &#x03A6; 0 that contains no information of the input polynomial. To investigate this phenomenon, we first explicitly characterize all the global minima of the cost function. We then prove that one particular global minimum (called the maximal solution) belongs to a neighborhood of &#x03A6; 0 , on which the cost function is strongly convex under the condition &#x2016; f &#x2016; &#x221E; = O ( d &#x2212; 1 ) with d = d e g ( f ) . Our result provides a partial explanation of the aforementioned success of optimization algorithms.

Wang, Jiasu↗

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗

Designing optimal core–shell MOFs for direct air capture

Metal–organic frameworks (MOFs), along with other novel adsorbents, are frequently proposed as candidate materials to selectively adsorb CO 2 for carbon capture processes. However, adsorbents designed to strongly bind CO 2 nearly always bind H 2 O strongly (sometimes even more so). Given that water is present in significant quantities in the inlet streams of most carbon capture processes, a method that avoids H 2 O competition for the CO 2 binding sites would be technologically valuable. Here, in this paper, we consider a novel core–shell MOF design strategy, where a high-CO 2 -capacity MOF “core” is protected from competitive H 2 O-binding via a MOF “shell” that has very slow water diffusion. We consider a high-frequency adsorption/desorption cycle that regenerates the adsorbents before water can pass through the shell and enter the core. To identify optimal core–shell MOF pairs, we use a combination of experimental measurements, computational modeling, and multiphysics modeling. Our library of MOFs is created from two starting MOFs-UiO-66 and UiO-67-augmented with 30 possible functional group variations, yielding 1740 possible core–shell MOF pairs. After defining a performance score to rank these pairs, we identified 10 core–shell MOF candidates that significantly outperform any of the MOFs functioning alone.

42 ENGINEERING↗

A DSN optimal spacecraft scheduling model

A computer model is described which uses mixed-integer linear programming to provide optimal DSN spacecraft schedules given a mission set and specified scheduling requirements. A solution technique is proposed which uses Bender's Method and a heuristic starting algorithm.

Webb, W. A.↗

An optimal spacecraft scheduling model for the NASA deep space network

A computer model is described which uses mixed-integer linear programming to provide optimal DSN spacecraft schedules given a mission set and specified scheduling requirements. A solution technique is proposed which uses Bender's method and a heuristic starting algorithm.

Webb, W. A.↗