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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Global Optimization of N-Maneuver, High-Thrust Trajectories Using Direct Multiple Shooting

The performance of impulsive, gravity-assist trajectories often improves with the inclusion of one or more maneuvers between flybys. However, grid-based scans over the entire design space can become computationally intractable for even one deep-space maneuver, and few global search routines are capable of an arbitrary number of maneuvers. To address this difficulty a trajectory transcription allowing for any number of maneuvers is developed within a multi-objective, global optimization framework for constrained, multiple gravity-assist trajectories. The formulation exploits a robust shooting scheme and analytic derivatives for computational efficiency. The approach is applied to several complex, interplanetary problems, achieving notable performance without a user-supplied initial guess.

optimization↗
DOE OSTI2020

Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders

We report the design/discovery of new materials is highly nontrivial owing to the near-infinite possibilities of material candidates and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to virtually screen material candidates with desired properties by learning a theoretical mapping from material-to-property space, referred to as the forward problem. However, this approach is inefficient and severely constrained by the candidates that the human imagination can conceive. Thus, in this work on polymers, we tackle the materials discovery challenge by solving the inverse problem: directly generating candidates that satisfy desired property/performance objectives. We utilize syntax-directed variational autoencoders (VAE) in tandem with Gaussian process regression (GPR) models to discover polymers expected to be robust under three extreme conditions: (1) high temperatures, (2) high electric field, and (3) high temperature and high electric field, useful for critical structural, electrical, and energy storage applications. This approach to learn from and augment) human ingenuity is general and can be extended to discover polymers with other targeted properties and performance measures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device

The utilization of machine learning techniques has become commonplace in the analysis of optical emission spectra. These methods are often limited to variants of principal components analysis (PCA), partial-least squares (PLS), and artificial neural networks (ANNs). A plethora of other techniques exist and are well established in the world of data science, yet are seldom investigated for their use in spectroscopic problems. In this study, machine learning techniques were used to analyze optical emission spectra of laser-induced plasma from ceria pellets doped with silicon in order to predict silicon content. Additionally, a boosted regression ensemble model was created, and its predictive accuracy was compared to that of traditional PCA, PLS, and ANN regression models. Boosted regression tree ensembles yielded fits with R-squared (R2) values as high as 0.964 and mean-squared errors of prediction (MSEPs) as low as 0.074, providing the most accurate predictive model. Neural networks performed with slightly lower R2 values and higher MSEPs compared to the ensemble methods, thus indicating susceptibility to overfitting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Abstract for CRADA between National Energy Technology Laboratory and Mattiq, Inc.

To decarbonize the chemicals and fuels industry, we require new and innovative technologies that can leverage renewable feedstocks including renewable electricity and renewable carbon sources, such as CO 2 . State-of-the-art (SOTA) CO 2 utilization technologies that can produce renewable chemicals and fuels, such as the electrochemical reduction of CO 2 , are still significantly lacking in efficiency, and are therefore not cost-competitive with existing infrastructure. The key bottleneck to cost-competitive chemicals and fuels sourced from CO 2 and renewable electricity is the lack of any efficient catalyst material. The National Energy Technology Laboratory (NETL) and Mattiq will collaborate in the development of an efficient catalyst material that can effectively convert CO 2 into products of interest. Specifically, NETL will utilize high-performance computing to greatly reduce the number of potential materials to be investigated by Mattiq ultrahigh-throughput experimental catalyst discovery framework. This work is poised to rapidly accelerate the development of novel and efficient CO 2 reduction electrocatalysts that can bring CO 2 utilization closer to commercial viability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Core-Shell Oxidative Aromatization Catalysts for Single Step Liquefaction of Distributed Shale Gas (Final Technical Report)

The objective of this project was to design and demonstrate a core-shell structured multifunctional catalyst to convert the light (dry) components of shale gas into liquid aromatic compounds (primarily benzene and toluene) in a single step. Operated in a modular oxidative aromatization system (OAS) under a cyclic redox scheme, the novel catalyst and process can significantly improve the value and transportability of distributed shale gas. Since the project started, each quarter addressed a different set of tasks related to the completion of the milestone detailed in the project award. The yearly summaries of these tasks are summarized below: Q1-Q4: • Conducted project planning and literature search. • Investigated a number of SHC redox catalysts using thermogravimetric analysis and fixed-bed reactor experiments. • Initiated process modeling towards generating two process models for the methane DHA base case and OAS process. • Developed DHA catalysts capable of producing >500 g/kg-cat-hr aromatics at 80% or greater aromatics selectivity at 700°C. Q5-Q8: • Developed alternative approaches with sequential bed configurations to enhance the aromatic yields based on OCM+DHA • Improved the zeolite synthesis efficiency by using the microwave-assisted technique and investigated the synthesis conditions on the zeolite yield, crystalline structure and morphology • Constructed a set of Aspen Plus process models with significant energy savings for OAS as compared to the base case non-oxidative DHA. • Adapted conventional hydrothermal method to be applicable to the microwave synthesizer unit for more efficient catalyst synthesis. • Studied the structure of the OCM catalyst and the dispersion of the carbonate in the redox reactions and in methane flow with Raman Spectroscopy. Q9-Q12: • Scaled up the catalyst synthesis with the microwave synthesis method. Based on its performance, procedural characterizations and catalytic performance testing were further conducted for the new microwave synthesized catalysts with the newly-developed product analysis procedure. • Developed the reaction system setup for the C2-DHA or OCM+DHA reaction product and achieved a better product collection-analysis method for the aromatic products with an improved carbon balance. The product from the OCM reaction exhibited complicated effects on the DHA catalyst. • Conducted additional OCM catalyst characterization using Near Ambient Pressure X-ray Photoelectron Spectroscopy and in situ Raman characterization • Validated the significant energy savings for OAS as compared to the base case non-oxidative DHA. Successfully set up the simulation model for the OCM+DHA+SHC reaction system based on the updated experimental results from NCSU. Q13-End of project: • Synthesized new zeolite catalysts by the microwave method, conducted characterizations (XRD, SEM, and TEM) and catalytic behavior testing. • Explored the “wet” C 2 H 6 and C 2 H 4 DHA reactions with using steam co-feed. A subsequent reduction as the regeneration step can regenerate the DHA catalyst and recover 99% activity of the fresh performance. • Achieved a 15.3% single-pass aromatic yield from methane by rationally combining the OCM and DHA at different temperatures. • Conducted a 105-hour stability test with an improved regeneration procedure, with an average aromatic yield of 13.8%. • Developed new catalyst and achieved a record-high 23.2% yield.

03 NATURAL GAS↗
DOE OSTI2020

N-doped honeycomb-like porous carbon towards high-performance supercapacitor

Biomass-derived porous carbon with developed pore structure is critical to achieving high performance electrode materials. In this work, we report a grape-based honeycomb-like porous carbon (GHPC) prepared by KOH activation and carbonization, followed by N-doping (NGHPC). The obtained NGHPC exhibits a unique honeycomb-like structure with hierarchically interconnected micro/mesopores, and high specific surface area of 1268 m2/g. As a supercapacitor electrode, the NGPHC electrode exhibits a remarkable specific capacitance of 275 F/g at 0.5 A/g in a three-electrode cell. Moreover, the NGHPC//NGHPC symmetric supercapacitor displays a high energy density of 12.6 Wh/kg, and excellent cycling stability of approximately 95.2% capacitance retention after 5000 cycles at 5 A/g. The excellent electrochemical performance of NGHPC is ascribed to its high specific surface area, honeycomb-like structure and high-content of pyrodinic-N (36.29%). It is believed that grape-based carbon materials show great potential as advanced electrode materials for supercapacitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Agilent AgileBioFoundry CRADA (Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analytical Assessment of Impurities Found in Process Gases using the InfiTOF, a High Resolution, Low Mass, Variable Time-of-Flight Mass Spectrometer

The JEOL InfiToF is a high-resolution, low mass (HRLM) mass spectrometer (MS) with the application potential to meet analytical needs for tritium handling systems, such as those at the Savannah River Tritium Facilities (SRTE) and those used in fusion research. The Service Level Agreement (SLA) #144 line 27 “InfiTOF R&D” has concluded its first year of efforts under Tritium Recycle and Renewal. The project goals for FY22 were: (1) Production of a finalized modification list for tritium hardened components in the InfiTOF, (2) perform an assessment on impurity gases commonly found in process gases from Tritium Facilities and (3) begin developing a set of standardized work instructions that will be used as a basis for operations on the InfiTOF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1973

The starting transient of solid propellant rocket motors with high internal gas velocities

A comprehensive analytical model which considers time and space development of the flow field in solid propellant rocket motors with high volumetric loading density is described. The gas dynamics in the motor chamber is governed by a set of hyperbolic partial differential equations, that are coupled with the ignition and flame spreading events, and with the axial variation of mass addition. The flame spreading rate is calculated by successive heating-to-ignition along the propellant surface. Experimental diagnostic studies have been performed with a rectangular window motor (50 cm grain length, 5 cm burning perimeter and 1 cm hydraulic port diameter), using a controllable head-end gaseous igniter. Tests were conducted with AP composite propellant at port-to-throat area ratios of 2.0, 1.5, 1.2, and 1.06, and head-end pressures from 35 to 70 atm. Calculated pressure transients and flame spreading rates are in very good agreement with those measured in the experimental system.

Peretz, A.↗
NASA NTRS1977

Tilt-proprotor perspective

The general tilt-proprotor concept is discussed, and a more detailed look at the XV-15 aircraft is taken. The special features of the two-engine system, engine control system, and flight control system are mentioned. The main objectives of the XV-15 program are to (1) verify rotor/pylon/wing/dynamic stability and aircraft performance over a representative operational envelope, (2) assess the handling qualities and establish a safe operating envelope, and (3) investigate gust sensitivity, effects of downwash, and hover operation. With regard to rotor/pylon stability, one challenge is to be able to predict a parameter's value and then build hardware to match. The analytical program has gained some respect through aeroelastic and full-scale XV-3 demonstrations. Special concern centers around the thrust and power management system when flying at high speed when very small changes in rotor collective pitch represent large changes in thrust and power. Demonstration of the system awaits wind-tunnel and flight testing.

Few, D. D.↗
NASA NTRS1994

An application of miniscale experiments on Earth to refine microgravity analysis of adiabatic multiphase flow in space

Adiabatic two-phase flow is of interest to the design of multiphase fluid and thermal management systems for spacecraft. This paper presents original data and unifies existing data for capillary tubes as a step toward assessing existing multiphase flow analysis and engineering software. Comparisons of theory with these data once again confirm the broad accuracy of the theory. Due to the simplicity and low cost of the capillary tube experiments, which were performed on earth, we were able to closely examine for the first time a flow situation that had not previously been examined appreciably by aircraft tests. This is the situation of a slug flow at high quality, near transition to annular flow. Our comparison of software calculations with these data revealed overprediction of pipeline pressure drop by up to a factor of three. In turn, this finding motivated a reexamination of the existing theory, and then development of a new analytical and is in far better agreement with the data. This sequence of discovery illustrates the role of inexpensive miniscale modeling on earth to anticipate microgravity behavior in space and to complete and help define needs for aircraft tests.

Rothe, Paul H.↗
NASA NTRS1997

Cure Chemistry of Phenylethynyl Terminated Oligomers

The ability to process high performance polymers into quality, void-free composites has been significantly advanced using oligomers terminated with reactive groups which cure or crosslink at elevated temperature without the evolution of volatile byproducts. Several matrix resin systems of considerable interest to the aerospace community utilize phenylethynyl-terminated imide (PETI) technology to achieve this advantage. The present paper addresses the cure chemistry of PETI oligomers. The thermal cure of a low molecular weight model compound was studied using a variety of analytical techniques including differential scanning calorimetry, Fourier transform infrared spectroscopy, and liquid chromatography-mass spectroscopy. The studies indicate an extremely complex cure process. Many stable products were isolated and this paper reports current work on identification of those products. The intent of this research is to provide fundamental insight into the molecular structure of the cured PETI engineering materials so that performance and durability can be more fully assessed.

Wood, Karen H.↗
NASA NTRS2018

Development of the Multi Purpose Transportation System for the Space Launch System (SLS) Core Stage (CS) Flight Article

NASA’s Multi Purpose Transportation System (MPTS) is designed to transport the Space Launch System vehicle segments by waterway and roadway. It is tasked with transporting the vehicle from where it is manufactured to its intermediate test location and final launch destination. Its design incorporates mechanisms that release degrees of freedom to prevent excessive loading during transit and ensure a successful delivery of the vehicle to its intended destination. In addition to the CS (Core Stage) flight article, the system will also move three structural test articles and a simulated CS Pathfinder (weight, center of gravity, outer mold line dimensions, and overall length) over road terrain on four NASA centers and on the Pegasus barge. The MPTS independently supports the article at both ends while communicating as a combined unit through automated monitoring of its released degree of freedom and corrective responses. This allows the system to constrain its payload in a statically determinate manner while traversing across highly variable terrain. Multi-body simulation of the transportation route is useful to predict free-body motion within the specified travel ranges. The MPTS has completed its design and analysis developmental cycles. This unpublished paper will describe the design challenges encountered in developing this system of large scale structure which incorporates complex mechanisms. The unique techniques and methodologies developed for analytical assessment of the hardware will be also be discussed. Key results from analytical evaluations as well as ongoing performance testing will be presented.

Sandridge, Sarah↗
NASA NTRS2023

Reduction in Computational Cost of Progressive Failure Analysis of Composite Structures

Designing aircraft structures requires efficient modeling approaches to iterate on multiple structural configurations to achieve an optimal design. Typically, damage tolerance is not considered at the design stage because of the high computational cost in its implementation within a finite element modeling approach. Therefore, analytical or empirical approaches are often used to size critical damage-tolerant structures once an optimal design is determined. In this study, the Progressive Release eXplicit Virtual Crack-Closure Technique (PRX-VCCT) is assessed for its capability to cost-effectively evaluate skin stringer separation of a blade-stiffened panel that is subjected to seven point bend loads. An initial verification study was performed to evaluate PRX VCCT to accurately simulate skin-stringer separation with respect to existing cohesive element approaches. Furthermore, the influence of element size, ranging from 0.10 in. to 0.40 in., on the total computational time using the PRX-VCCT is investigated. The results indicate that the PRX-VCCT can be used to accurately simulate skin stringer separation using large element lengths (0.40 in.). Additionally, a significant reduction in the computational time to simulate skin stringer separation is observed using the PRX-VCCT. Large-scale progressive damage analysis using PRX-VCCT can be implemented early in the design cycle of composite structures without requiring a global-to-local modeling approach.

Composites↗
NASA NTRSDate not supplied

The Genesis Non-flight Implant Sample Archive

Introduction: For the past 20 years the Genesis science community has been analyzing solar wind captured in sample collectors now curated at Johnson Space Center (JSC). Non-flown flight like collector materials (non-flight) considered reference material was always allocated by the JSC Genesis team for testing experimental procedures. However, to expedite Genesis science, distribution of non-flown reference materials were also provided by, D. S. Burnett (Genesis PI, Caltech) and A. J. G. Jurewicz (ASU) who were funded to aid all Genesis PIs by providing engineering test materials archived at Caltech pre-flight as well as ion implants into these materials [1]. Implanted materials (non-flight reference, flight-like semiconductor materials, and NIST SRM glass) received from the Caltech collection during a pilot project are being used to develop an accession procedure for the purpose of making these materials available to researchers in the future. These implant samples are important because they can be utilized as measurement standards [2]. This is a work in progress and this work reports progress in documentation and imaging. The pilot program received 63 implanted reference materials with known implanted ions. Genesis Non-Flight Database: The existing non-flight material database was modified to allow for the description of implant sessions and to allow correlation of the implant information to individual specimens. An implant session has three main components: a known ion, a known dose (ion/cm2), and a known energy (keV). Procedure: Laboratory Procedure. Upon receiving non-flight analytical standards (independently calibrated implants), or implant samples (nominally calibrated implants), they will be imaged in their current containers to capture any information written before being brought into the Genesis Sample Laboratory. Documentation is provided by the donor and used for correlating the data between the implant sessions and implant samples. This information is not verified by Genesis Curation. The microscope used to image samples in the laboratory has an automated stage with a stainless-steel plate to hold samples and a camera that utilizes the software Surveyor to take photomosaic images of the implant samples. The camera attached to the microscope is a QICAM High Performance IEEE 1394 FireWire Digital CCD Camera. This setup, shown in Fig. 1, allows for photomosaics of small-scale samples with a 10x objective or 25x objective. Examples of images taken with this microscope setup are shown in Fig.2 and Fig. 3. After imaging, samples get stored in a clean fluoroware container or polypropylene vial depending on sample size for long term storage. Database Procedure. The Genesis Non-Flight Database currently allows for the addition of implant sessions. The required fields for adding an implant session are the implant session ion, the implant session dose, and the implant session energy. There are also fields for the date and vendor of the sessions as well as a field for if the session was calibrated or not. Once an implant session has been inserted into the database, additional documentation from the session can be attached. The database will automatically assign an Implant Session Number. After inserting an implant session, the implanted samples can be inserted. The fields required for an implant sample are the material of the sample and the size of the sample. The Generic name for the implant sample with be automatically generated by the database once it has been inserted. Implant sample numbers begin with 3X to distinguish from flown Genesis sample numbers. There are also fields for processors to add the location (room, cabinet, tray) and container type (fluoroware, polypropylene vial). Once an implant session and an associated sample(s) have been inserted into the database the sample can be then tied to all associated implant sessions. An implant sample can be tied to multiple implant sessions. Future work: For curation, future work consists of creating an online catalogue for implant samples as well as updating the database with more samples as we receive them. For the scientific community these implant samples have many potential uses. For Genesis research, they are directly applicable for testing and, in some cases, as analytical standards. For non-Genesis research, implants (especially calibrated implants) could be used for calibrating other, unique planetary materials [1].

C D Calva↗
DOE OSTI2020

Pilgrim : A thermal rate constant calculator and a chemical kinetics simulator

Pilgrim is a program written in Python and designed to use direct dynamics in the calculation of thermal rate constants of chemical reactions by the variational transition state theory (VTST), based on electronic structure calculations for the potential energy surface. Pilgrim can also simulate reaction mechanisms using kinetic Monte Carlo (KMC). For reaction processes with many elementary steps, the rate constant of each of these steps can be calculated by means of conventional transition state theory (TST) or by using VTST. In the current version, Pilgrim can evaluate thermal rates using the canonical version of reaction-path VTST, which requires the calculation of the minimum energy path (MEP) associated with each elementary step or transition structure. Multi-dimensional quantum effects can be incorporated through the small-curvature tunneling (SCT) approximation. These methodologies are available both for reactions involving a single structure of the reactants and the transition state and also for reactions involving flexible molecules with multiple conformations of the reactant and/or of the transition state. For systems with many conformers, the program can evaluate each of the elementary reaction rate constants by multipath canonical VTST or multi-structural VTST. Moreover, the reactant can be unimolecular or bimolecular. Torsional anharmonicity can be incorporated through either the MSTor or the Q2DTor programs. Dual-level calculations are also available in Pilgrim: automatic high-level single-point energies can be used to correct the energy of reactants, transition states, products, and MEP points using the interpolated single-point energies (ISPE) algorithm. When the rate constants of all the chemical processes of interest are known, by means of their calculation using Pilgrim or alternatively through analytical fits to the rate constants as functions of temperature, it is possible to simulate a multistep mechanism under specified laboratory conditions using KMC. Finally, this algorithm allows performing a kinetic simulation to monitor the evolution of each chemical species with time and obtain the product yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Machine learning prediction of glass transition temperature of conjugated polymers from chemical structure

Predicting the glass transition temperature (T g ) is of critical importance as it governs the thermomechanical performance of conjugated polymers (CPs). Here, we report a predictive modeling framework to predict T g of CPs through the integration of machine learning (ML), molecular dynamics (MD) simulations, and experiments. With 154 T g data collected, an ML model is developed by taking simplified “geometry” of six chemical building blocks as molecular features, where side-chain fraction, isolated rings, fused rings, and bridged rings features are identified as the dominant ones for T g . MD simulations further unravel the fundamental roles of those chemical building blocks in dynamical heterogeneity and local mobility of CPs at a molecular level. The developed ML model is demonstrated for its capability of predicting T g of several new high-performance solar cell materials to a good approximation. The established predictive framework facilitates the design and prediction of T g of complex CPs, paving the way for addressing device stability issues that have hampered the field from developing stable organic electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ground State Energy Functional with Hartree–Fock Efficiency and Chemical Accuracy

We introduce the deep post Hartree–Fock (DeePHF) method, a machine learning-based scheme for constructing accurate and transferable models for the ground-state energy of electronic structure problems. DeePHF predicts the energy difference between results of highly accurate models such as the coupled cluster method and low accuracy models such as the Hartree–Fock (HF) method, using the ground-state electronic orbitals as the input. It preserves all the symmetries of the original high accuracy model. The added computational cost is less than that of the reference HF or DFT and scales linearly with respect to system size. We examine the performance of DeePHF on organic molecular systems using publicly available data sets and obtain the state-of-art performance, particularly on large data sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗