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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Completion design improvement using a deep convolutional network

Maximizing stimulated natural and hydraulic fracture network is one of the primary hydraulic fracturing concerns for economic production from a horizontal shale gas well. Geomechanical facies and preexisting fractures in each stage are identified based on similarities in formation characteristics to optimize the locations of perforation clusters. This often requires analyzing large volumes of drilling, Logging While Drilling (LWD) and Measurement While Drilling (MWD) data. In this paper, we develop a methodology that calculates the mechanical specific energy (MSE) using real-time drill string acceleration signals directly from its definition. High resolution vibration signals have been collected using a tri-axial accerlometer, which was an auxiliary tool included in acoustic borehole imager. This technique provides a cost-efficient solution for engineered completion design. Furthermore, we adopt deep Convolutional Neural Network (CNN) with signal processing to build a data pipeline that effectively extracts patterns from dynamic acceleration signals for rock lateral MSE classification. First, we apply discrete wavelet transform and Short-Time Fourier Transform (STFT) for signal denoising and pattern recognition. Then we construct an image dataset using multi-scale image fusion at pixel level from 3 sensor channels, including axial, lateral acceleration spectrograms and zero-padded revolutions per minute (RPM). The resulted RGB image dataset includes 4,000 images of 5 MSE ranges with various rock strength conditions. Our results demonstrate that the proposed deep learning model can achieve more than 90% classification accuracy. The deep learning results, as a reference source, were applied in selected Marcellus Shale Energy and Environmental Lab (MSEEL) wells engineered completion located in the Marcellus shale gas site.

03 NATURAL GAS↗
DOE OSTI2024

Colossal magnetoresistance from spin-polarized polarons in an Ising system

Recent experiments suggest a new paradigm toward novel colossal magnetoresistance (CMR) in a family of materials EuM 2 X 2 (M = Cd, In, Zn; X = P, As), distinct from the traditional avenues involving Kondo–Ruderman–Kittel–Kasuya–Yosida crossovers, magnetic phase transitions with structural distortions, or topological phase transitions. Here, we use angle-resolved photoemission spectroscopy and density functional theory calculations to explore their origin, particularly focusing on EuCd 2 P 2 . While the low-energy spectral weight royally tracks that of the resistivity anomaly near the temperature with maximum magnetoresistance ( T MR ) as expected from transport-spectroscopy correspondence, the spectra are completely incoherent and strongly suppressed with no hint of a Landau quasiparticle. Using systematic material and temperature dependence investigation complemented by theory, we attribute this nonquasiparticle caricature to the strong presence of entangled magnetic and lattice interactions, a characteristic enabled by the p - f mixing. Given the known presence of ferromagnetic clusters, this naturally points to the origin of CMR being the scattering of spin-polarized polarons at the boundaries of ferromagnetic clusters. These results are not only illuminating to investigate the strong correlations and topology in EuCd 2 X 2 family, but, in a broader view, exemplify how multiple cooperative interactions can give rise to extraordinary behaviors in condensed matter systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

GPU acceleration of all-electron electronic structure theory using localized numeric atom-centered basis functions

We present an implementation of all-electron density-functional theory for massively parallel GPU-based platforms, using localized atom-centered basis functions and real-space integration grids. Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the update of the electron density, the integration of the real-space Hamiltonian matrix, and calculation of Pulay forces. To assess the performance of our GPU implementation, we performed benchmarks on three different architectures using a 103-material test set. We find that operations which rely on dense serial linear algebra show dramatic speedups from GPU acceleration: in particular, SCF iterations including force and stress calculations exhibit speedups ranging from 4.5 to 6.6. For the architectures and problem types investigated here, this translates to an expected overall speedup between 3–4 for the entire calculation (including non-GPU accelerated parts), for problems featuring several tens to hundreds of atoms. Additional calculations for a 375-atom Bi2Se3 bilayer show that the present GPU strategy scales for large-scale distributed-parallel simulations.

42 ENGINEERING↗
NASA NTRS1976

System for imposing directional stability on a rocket-propelled vehicle

An improved system for use in imposing directional stability on a rocket-propelled vehicle is described. The system includes a pivotally supported engine-mounting platform, a gimbal ring mounted on the platform and adapted to pivotally support a rocket engine and an hydraulic actuator connected to the platform for imparting selected pivotal motion. An accelerometer and a signal comparator circuit for providing error intelligence indicative of aberration in vehicle acceleration is included along with an actuator control circuit connected with the actuator and responsive to error intelligence for imparting pivotal motion to the platform. Relocation of the engine's thrust vector is thus achieved for imparting directional stability to the vehicle.

Perkins, H.↗
DOE OSTI2022

Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data

AI and simulation workloads consume and generate large amounts of data that need to be searched, transformed and merged with other data. With the goal of treating data as a first-class citizen inside a traditionally compute-centric HPC environment, we explore how the use of accelerators and high-speed interconnects can speed up tasks which otherwise constitute bottlenecks in computational discovery workflows. BlazingSQL is SQL engine that runs natively on NVIDIA GPUs and supports internode communication for fast analytics on terabyte-scale tabular data sets. We show how a fast interconnect improves query performance if leveraged through the Unified Communication X (UCX) middleware. We envision that future computing platforms will integrate accelerated database query capabilities for immediate and interactive analysis of large simulation data.

Glaser, Jens↗
DOE OSTI2023

Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning

High-fidelity modeling is an essential design tool for many engineering applications. However, for complex systems, computational cost can be a limiting factor. Analyzing parameter sensitivity, uncertainty quantification, and design optimization require many model evaluations. Surrogate models are often used to develop the relationship between model parameters and quantities of interest. However, in the case of complex systems, surrogate models require several degrees of freedom and, thus, a large number of data points to determine the correct dependencies. For many applications, this may be prohibitively expensive. The reduction of computational requirements can be achieved by leveraging low-fidelity models. Low-fidelity models represent the system at a coarser resolution with the advantage of computational efficiency. Therefore, a bi-fidelity modeling paradigm, which augments the accuracy of a low-fidelity model in a computationally efficient manner by invoking limited runs of a high-fidelity model, can be leveraged to sufficiently balance the accuracy and computational requirements. In this work, a bi-fidelity weighted transfer learning method using neural networks was applied to a computational fluid dynamics heat transfer modeling problem. The transfer learning advantage was investigated as a function of hyperparameters. Our main finding is that the use of a bi-fidelity modeling paradigm achieves accuracy close to that of a high-fidelity Gaussian process model while significantly reducing computational cost. The bi-fidelity model achieves comparable performance with 90 high-fidelity samples-that is, 60% less than the samples needed to achieve similar accuracy without the use of bi-fidelity modeling,

Borowiec, Katarzyna↗
DOE OSTI2021

NRIC Asset Suite Engineering and Operations Data Integration Plan

The National Reactor Innovation Center (NRIC), established by the U.S. Department of Energy (DOE) in August 2019, accelerates the demonstration and deployment of advanced nuclear energy through its mission to inspire stakeholders and the public, empower innovators, and deliver successful outcomes through efficient coordination of partners and resources. NRIC is a national program led by Idaho National Laboratory (INL), enabling collaborators to harness the world-class capabilities of the U.S. National Laboratory System. Committed to demonstrating advanced reactors by the end of 2025, NRIC is designed to bridge the gap between research, development, and the marketplace to help convert some of the Nation’s most promising advanced nuclear reactors into commercial applications by 2030. To meet these needs, NRIC is developing two reactor demonstration test beds at Idaho National Laboratory (INL), the Laboratory for Operation and Testing in the United States (LOTUS) and the Demonstration and Operation of Microreactor Experiments (DOME) test bed. Each test bed involves the modification of existing facilities at INL’s Materials and Fuels Complex (MFC). Retrofitting these facilities to accommodate novel reactors, as well as subsequent but similar NRIC projects, is a non-trivial engineering task and is expected to generate a significant amount of new and revised documentation. Leveraging digital engineering practices, this documentation will be managed in a purpose-built data management tool to facilitate origination, review, and approval while coordinating with the design contractor. The subsequent upload and review of documentation to INL’s existing document control system comprises a long and unnecessarily manual task. An opportunity exists to automate this upload process and save job-hours while continuing to adhere to INL/MFC document management procedures.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2006

System Would Detect Foreign-Object Damage in Turbofan Engine

A proposed data-fusion system, to be implemented mostly in software, would further process the digitized and preprocessed outputs of sensors in a turbofan engine to detect foreign-object damage (FOD) [more precisely, damage caused by impingement of such foreign objects as birds, pieces of ice, and runway debris]. The proposed system could help a flight crew to decide what, if any, response is necessary to complete a flight safely, and could aid mechanics in deciding what post-flight maintenance action might be needed. The sensory information to be utilized by the proposed system would consist of (1) the output of an accelerometer in an engine-vibration-monitoring subsystem and (2) features extracted from a gas path analysis. ["Gas path analysis" (GPA) is a term of art that denotes comprehensive analysis of engine performance derived from readings of fuel-flow meters, shaft-speed sensors, temperature sensors, and the like.] The acceleration signal would first be processed by a wavelet-transform-based algorithm, using a wavelet created for the specific purpose of finding abrupt FOD-induced changes in noisy accelerometer signals. Two additional features extracted would be the amplitude of vibration (determined via a single- frequency Fourier transform calculated at the rotational speed of the engine), and the rate of change in amplitude due to an FOD-induced rotor imbalance. This system would utilize two GPA features: the fan efficiency and the rate of change of fan efficiency with time. The selected GPA and vibrational features would be assessed by two fuzzy-logic inference engines, denoted the "Gas Path Expert" and the "Vibration Expert," respectively (see Figure 1). Each of these inference engines would generate a "possibility" distribution for occurrence of an FOD event: Each inference engine would assign, to its input information, degrees of membership, which would subsequently be transformed into basic probability assignments for the gas path and vibration components. The outputs of the inference engines would be fused by use of Dempster s combination algorithm (more precisely, an algorithm, based on the Dempster-Shafer-Yager theory of evidence, for fusing uncertain or imprecise information) to provide a reduced body of information to a human or computer decision maker. Figure 2 depicts some outputs generated in response to simulated accelerometer and GPA signals

Torso, James A.↗
NASA NTRS2005

Results of a 2000 hour wear test of the NEXIS ion engine

The Nuclear Electric Xenon Ion System (NEXIS) ion thruster was developed for potential outer planet robotic missions under NASA's Prometheus program. This engine was designed to operate at power levels ranging from 16 to over 20 kWe at specific impulses of 6000 to 7500 s for burn times of up to 10 years, satisfying the requirements of nuclear electric propulsion systems such as that on the proposed Prometheus 1 mission to explore the icy moons of Jupiter. State-of-the-art performance and life assessment tools were used to design the thruster. Following the successful performance validation of a Laboratory Model thruster, Development Model hardware was fabricated and subjected to vibration and wear testing. The results of a 2000-hour wear test are reported herein. Thruster performance achieved the target requirements and was steady for the duration of the test. Ion optics performance was similarly stable. Discharge loss increases of 6 eV/ion were observed in the first 500 hours of the test and were attributed to primary electron energy decreases due to cathode insert conditioning. Relatively high recycle rates were observed and were identified to be high-voltage-to-ground arcs in the back of the thruster caused by wire insulation outgassing and electron penetration through the plasma screen. Field emission of electrons between the accelerator and screen grids was observed and attributed to evolution of field emitter sites at accelerator grid aperture edges caused by ion bombardment. Preliminary modeling and analysis indicates that the NEXIS engine can meet mission performance requirements over the required lifetime. Finally, successful validation of the NEXIS design methodology, design tools, and technologies with the results of the wear test and companion performance and vibration tests presents significant applicability of the NEXIS development effort to missions of near-term as well as long-term interest for NASA.

Nuclear Electric Xenon Ion System (NEXIS)Thruster ↗
NASA NTRS2005

Results of a 2000 Hour Wear Tof the NEXIS Ion Engine

The Nuclear Electric Xenon Ion System (NEXIS) ion thruster was developed for potential outer planet robotic missions under NASA's Prometheus program. This engine was designed to operate at power levels ranging from 16 to over 20 kWe at specific impulses of 6000 to 7500 s for burn times of up to 10 years, satisfying the requirements of nuclear electric propulsion systems such as that on the proposed Prometheus 1 mission to explore the icy moons of Jupiter. State-of-the-art performance and life assessment tools were used to design the thruster. Following the successful performance validation of a Laboratory Model thruster, Development Model hardware was fabricated and subjected to vibration and wear testing. The results of a 2000-hour wear test are reported herein. Thruster performance achieved the target requirements and was steady for the duration of the test. Ion optics performance was similarly stable. Discharge loss increases of 6 eV/ion were observed in the first 500 hours of the test and were attributed to primary electron energy decreases due to cathode insert conditioning. Relatively high recycle rates were observed and were identified to be high-voltage-to-ground arcs in the back of the thruster caused by wire insulation outgassing and electron penetration through the plasma screen. Field emission of electrons between the accelerator and screen grids was observed and attributed to evolution of field emitter sites at accelerator grid aperture edges caused by ion bombardment. Preliminary modeling and analysis indicates that the NEXIS engine can meet mission performance requirements over the required lifetime. Finally, successful validation of the NEXIS design methodology, design tools, and technologies with the results of the wear test and companion performance and vibration tests presents significant applicability of the NEXIS development effort to missions of near-term as well as long-term interest for NASA.

Thruster performance↗
DOE OSTI2016

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Electronic structure and oxophilicity optimization of mono-layer Pt for efficient electrocatalysis

The slow kinetics of the anodic hydrogen oxidation reaction (HOR) in alkaline medium is one of the limitations for anion exchange membrane fuel cells (AEMFCs). Hence, accurately regulate and understand catalytic interface structure are essential to solve this bottleneck and reveal the structure-activity relationship. In this work, a novel trimetal core-shell model with mono-layer Pt-shell is employed for hydrogen electrooxidation to avoid thermodynamic driven bulk/surface composition deviation. On account of the atomic radius discrepancies of 3d-transition metals M (M = Fe, Co and Cu), the electronic structure of mono-layer Pt is regulated by the strain-engineered Pd-M core and the electrocatalytic activity for HOR is tuned accordingly. Nevertheless, step-by-step electrochemical monitoring and surface-treatment experiments indicate that the oxophilicity optimization by low-valence M(OH) x species, rather than the hydrogen binding energy (HBE) optimization caused by strain engineering, influence the activity obviously. It is mainly derived from the enhanced adsorption of OH ad and accelerated desorption of the H ad . The trimetal core-shell model breathes new life into the low-Pt catalyst design for hydrogen electrooxidation reaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

In-situ probing of the Fischer-Tropsch reaction on Co single crystal surfaces up to 1 bar

The surface chemistry of the Fischer-Tropsch catalytic reaction over Co has still several unknows. Here, we report an in-situ X-ray photoelectron spectroscopy study of Co$(0001)$ and Co$(10\bar{1}4)$, and in-situ high energy surface X-ray diffraction of Co$(0001)$ during the Fischer-Tropsch reaction at 0.15 bar - 1 bar and 406 K - 548 K in a H 2 /CO gas mixture. We find that these Co surfaces remain metallic under all conditions and that the coverage of chemisorbed species ranges from 0.4–1.7 monolayers depending on pressure and temperature. The adsorbates include CO on-top, C/-C x H y and various longer hydrocarbon molecules, indicating a rate-limiting direct CO dissociation pathway and that only hydrocarbon species participate in the chain growth. The accumulation of hydrocarbon species points to the termination step being rate-limiting also. Furthermore, we demonstrate that the intermediate surface species are highly dynamic, appearing and disappearing with time delays after rapid changes in the reactants’ composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Enhancing Electrocatalytic Water Splitting by Strain Engineering

Electrochemical water splitting driven by sustainable energy such as solar, wind, and tide is attracting ever-increasing attention for sustainable production of clean hydrogen fuel from water. Leveraging these advances requires efficient and earth-abundant electrocatalysts to accelerate the kinetically sluggish hydrogen and oxygen evolution reactions (HER and OER). A large number of advanced water-splitting electrocatalysts have been developed through recent understanding of the electrochemical nature and engineering approaches. Specifically, strain engineering offers a novel route to promote the electrocatalytic HER/OER performances for efficient water splitting. Herein, the recent theoretical and experimental progress on applying strain to enhance heterogeneous electrocatalysts for both HER and OER are reviewed and future opportunities are discussed. A brief introduction of the fundamentals of water-splitting reactions, and the rationalization for utilizing mechanical strain to tune an electrocatalyst is given, followed by a discussion of the recent advances on strain-promoted HER and OER, with special emphasis given to combined theoretical and experimental approaches for determining the optimal straining effect for water electrolysis, along with experimental approaches for creating and characterizing strain in nanocatalysts, particularly emerging 2D nanomaterials. Finally, a vision for a future sustainable hydrogen fuel community based on strain-promoted water electrolysis is proposed.

42 ENGINEERING↗
DOE OSTI2020

Towards understanding the development and characteristics of under-expanded flash boiling jets

Here in this research, the n-hexane jets discharged from a straight channel were studied numerically to reveal the development and characteristics of under-expanded flashing jets. Firstly, the development of flash boiling jets was investigated and compared to that of two-phase jets without phase transition. It was shown that the two-phase jets without phase transition can be under-expanded only if the flow is choked. In contrast, flash boiling jets can be under-expanded whether or not the choked conditions are verified. Secondly, the factors affecting the flashing jet behaviors were discussed. The relaxation time in phase transition, the expansion ratio, and the injection pressure have been identified as three key factors determining the jet characteristics. With high enough expansion ratio and low enough relaxation time, the expansion was so strong that the flow became transonic and shock structures similar to those of under-expanded gaseous jets appeared near the orifice exit. Finally, two types of choking have been identified for flash boiling jets, i.e., vaporization-induced choking and expansion-induced choking. The former one is mainly ascribed to the vapor formation in the orifice which reduces the local speed of sound, while the latter one is due to the expansion of under-expanded two-phase flow and the resultant flow acceleration.

42 ENGINEERING↗
DOE OSTI2023

A multi-length-scale investigation of the applicability of ductility laws for annealed and work-hardened copper

Small-scale mechanical testing provides unique advantages over conventional testing in investigating the mechanical response of nuclear materials. While small-scale testing enables accelerated materials research, it raises the question of comparability to large-scale properties for engineering design considerations. Among different mechanical properties for structural design considerations such as yield and ultimate tensile stress, ductility is of critical importance with respect to structural component health. The effectiveness of using small-scale mechanical testing for probing these mechanical properties is dictated by understanding how the mechanical responses translate from the microscale to the engineering scale. Therefore, a better understanding of size scaling effects via gathering and analysis of experimental data is required to bridge length-scales. Further, this work builds upon previous reports to provide statistical data on how mechanical response changes as the size of the specimens are reduced from conventional sizes. One hundred twenty mesoscale tensile coupons of oxygen-free high thermal conductivity (OFHC) copper in work-hardened and annealed state have been manufactured using micro-wire electrical discharge machining (EDM) and tested under uniaxial tension. The mesoscale specimens have dimensions dictated by pre-selected geometric ratios (i.e., gauge section length over the square root of the cross-section area) with gauge length dimensions of 3 mm (or less) and sub-millimeter gauge widths and thicknesses. The mesoscale responses were compared to bulkscale properties to reveal the effect of specimen size on the mechanical response as a function of grain size and material state for a single phase face-centered cubic metal.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strategies for designing biocatalysts with new functions

Enzymes can be optimized to accelerate chemical transformations via a range of methods. In this review, we showcase how protein engineering and computational design techniques can be interfaced to develop highly efficient and selective biocatalysts.

09 BIOMASS FUELS↗