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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Time calibration and synchronization of the scintillation light detection system in ICARUS-T600

The ICARUS-T600 Liquid Argon (LAr) Time Projection Chamber (TPC) is presently taking data in the Short Baseline Neutrino (SBN) program at Fermilab (U.S.A.) to search for a possible LSND-like sterile neutrino signal at Δm 2 ≈ 1 eV 2 with the Booster Neutrino Beam (BNB). A light detection system, based on 360 large area Photo-Multiplier Tubes (PMTs), has been realized for ICARUS-T600 to detect VUV photons produced by the passage of ionizing particles in LAr. This system is fundamental for the TPC operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the detector is exposed to a huge flux of cosmic rays due to its shallow depths installation, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of genuine neutrino interactions. The correct time reconstruction of events requires the precise knowledge of the delay of each PMT channel and a good synchronization of recording electronics, this last based on fast sampling digitizers. To achieve a time resolution better than 1 ns, we perform three consecutive timing corrections deployed at different stages of the optical data flow. Results demonstrate the capability of the ICARUS-T600 light detection system to allow a precise reconstruction of the temporal evolution of each event occurring in the detector and the association of neutrino events with the bunched structure of BNB.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1989

Molecule formation in fast neutral winds from protostars

A time-dependent chemical model is used to analyze the processes generating and destroying molecules in very high velocity winds from low-mass protostars. CO and SiO are found to be generated in significant quantities despite the persistence of H in atomic form, consistently with recent protostellar wind detections of CO and H I at velocities in excess of 100 km/sec. A moderate mass-loss rate, in conjunction with a temperature distribution that decreases rather rapidly with distance from the protostar, are the conditions for substantial molecule formation.

Glassgold, A. E.↗
NASA NTRS1992

Parallel solver for trajectory optimization search directions

A key algorithmic element of a real-time trajectory optimization hardware/software implementation is presented, the search step solver. This is one piece of an algorithm whose overall goal is to make nonlinear trajectory optimization fast enough to provide real-time commands during guidance of a vehicle such as an aeromaneuvering orbiter or the National Aerospace Plane. Many methods of nonlinear programming require the solution of a quadratic program (QP) at each iteration to determine the search step. In the trajectory optimization case, the QP has a special dynamic programming structure. The algorithm exploits this special structure with a divide- and conquer type of parallel implementation. The algorithm solves a (p.N)-stage problem on N processors in O(p + log2 N) operations. The algorithm yields a factor of 8 speed-up over the fastest known serial algorithm when solving a 1024-stage test problem on 32 processors.

Psiaki, M. L.↗
NASA NTRS1999

Quantum Algorithms

This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.

Quantum Algorithms polynomial time algorithm Hamil↗
NASA NTRS1977

A programmable microcomputer for real time speech processing

The implementation of a programmable microprocessor for real time speech processing is described. The design of a fast special-purpose computer operating at 150 nsec per instruction time reduces the problem of speech encoding and decoding to a software problem. Each instruction is a twelve-bit word, and the information conveyed by a word is explained. The microprocessor is controlled by two clocks - the A/D clock, or input sampling clock, which loads the digital input into the input register and presets the counter to a value set by the external switches; and the instruction clock, or system clock, which operates at 6 MHz. At this system clock rate and a sampling clock rate of 30 KHz, 200 instructions can be executed between samples, and for many speech encoding and decoding algorithms, 200 instructions are more than enough. The microcomputer is being used to test various delta modulator encoding algorithms.

Apelewicz, T.↗
NASA NTRS1990

Simulator evaluation of the final approach spacing tool

The design and simulator evaluation of an automation tool for assisting terminal radar approach controllers in sequencing and spacing traffic onto the final approach course is described. The automation tool, referred to as the Final Approach Spacing Tool (FAST), displays speed and heading advisories for arrivals as well as sequencing information on the controller's radar display. The main functional elements of FAST are a scheduler that schedules and sequences the traffic, a 4-D trajectory synthesizer that generates the advisories, and a graphical interface that displays the information to the controller. FAST was implemented on a high performance workstation. It can be operated as a stand-alone in the Terminal Radar Approach Control (TRACON) Facility or as an element of a system integrated with automation tools in the Air Route Traffic Control Center (ARTCC). FAST was evaluated by experienced TRACON controllers in a real-time air traffic control simulation. Simulation results show that FAST significantly reduced controller workload and demonstrated a potential for an increase in landing rate.

Davis, Thomas J.↗
NASA NTRS2021

Timing Calibration of the NuSTAR X-Ray Telescope

The Nuclear Spectroscopic Telescope Array (NuSTAR) mission is the first focusing X-ray telescope in the hard X-ray (3–79 keV) band. Among the phenomena that can be studied in this energy band, some require high time resolution and stability: rotation-powered and accreting millisecond pulsars, fast variability from black holes and neutron stars, X-ray bursts, and more. Moreover, a good alignment of the timestamps of X-ray photons to UTC is key for multi-instrument studies of fast astrophysical processes. In this paper, we describe the timing calibration of the NuSTAR mission. In particular, we present a method to correct the temperature-dependent frequency response of the on-board temperature-compensated crystal oscillator. Together with measurements of the spacecraft clock offsets obtained during downlinks passes, this allows a precise characterization of the behavior of the oscillator. The calibrated NuSTAR event timestamps for a typical observation are shown to be accurate to a precision of ∼65 μs.

Matteo Bachetti↗
DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Complexity growth in integrable and chaotic models

We use the SYK family of models with N Majorana fermions to study the complexity of time evolution, formulated as the shortest geodesic length on the unitary group manifold between the identity and the time evolution operator, in free, integrable, and chaotic systems. Initially, the shortest geodesic follows the time evolution trajectory, and hence complexity grows linearly in time. We study how this linear growth is eventually truncated by the appearance and accumulation of conjugate points, which signal the presence of shorter geodesics intersecting the time evolution trajectory. By explicitly locating such “shortcuts” through analytical and numerical methods, we demonstrate that: (a) in the free theory, time evolution encounters conjugate points at a polynomial time; consequently complexity growth truncates at O($\sqrt{N}$), and we find an explicit operator which “fast-forwards” the free N-fermion time evolution with this complexity, (b) in a class of interacting integrable theories, the complexity is upper bounded by O(poly(N)), and (c) in chaotic theories, we argue that conjugate points do not occur until exponential times O(e N ), after which it becomes possible to find infinitesimally nearby geodesics which approximate the time evolution operator. Finally, we explore the notion of eigenstate complexity in free, integrable, and chaotic models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗
NASA NTRS1991

Nuclear electric propulsion mission performance for fast piloted Mars missions

A mission study aimed at minimizing the time humans would spend in the space environment is presented. The use of nuclear electric propulsion (NEP), when combined with a suitable mission profile, can reduce the trip time to durations competitive with other propulsion systems. Specifically, a split mission profile utilizing an earth crew capture vehicle accounts for a significant portion of the trip time reduction compared to previous studies. NEP is shown to be capable of performing fast piloted missions to Mars at low power levels using near-term technology and is considered to be a viable candidate for these missions.

Hack, K. J.↗
NASA NTRS2001

Time-Accurate Solutions of Incompressible Navier-Stokes Equations for Potential Turbopump Applications

Two numerical procedures, one based on artificial compressibility method and the other pressure projection method, are outlined for obtaining time-accurate solutions of the incompressible Navier-Stokes equations. The performance of the two method are compared by obtaining unsteady solutions for the evolution of twin vortices behind a at plate. Calculated results are compared with experimental and other numerical results. For an un- steady ow which requires small physical time step, pressure projection method was found to be computationally efficient since it does not require any subiterations procedure. It was observed that the artificial compressibility method requires a fast convergence scheme at each physical time step in order to satisfy incompressibility condition. This was obtained by using a GMRES-ILU(0) solver in our computations. When a line-relaxation scheme was used, the time accuracy was degraded and time-accurate computations became very expensive.

Kiris, Cetin↗
DOE OSTI2023

ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study

Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.

critical clearing time↗
DOE OSTI2022

A Nonaqueous Redox‐Matched Flow Battery with Charge Storage in Insoluble Polymer Beads**

Abstract We describe the nonaqueous redox‐matched flow battery (RMFB), where charge is stored on redox‐active moieties covalently tethered to non‐circulating, insoluble polymer beads and charge is transferred between the electrodes and the beads via soluble mediators with redox potentials matched to the active moieties on the beads. The RMFB reported herein uses ferrocene and viologen derivatives bound to crosslinked polystyrene beads. Charge storage in the beads leads to a high (approximately 1.0–1.7 M) effective concentration of active material in the reservoirs while preventing crossover of that material. The relatively low concentration of soluble mediators (15 mM) eliminates the need for high‐solubility molecules to create high energy density batteries. Nernstian redox exchange between the beads and redox‐matched mediators was fast relative to the cycle time of the RMFB. This approach is generalizable to many different redox‐active moieties via attachment to the versatile Merrifield resin.

25 ENERGY STORAGE↗
DOE OSTI2021

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗
DOE OSTI2023

Irradiation creep measurement and microstructural analysis of chromium nitride–coated zirconium alloy using pressurized tubes

Environmental barrier coatings for Zr-based materials are currently under development to reduce oxidation and embrittlement in light-water reactors. Chromium nitride is one such candidate for this application, particularly as accident-tolerant fuel cladding. However, quantifying the impact of coatings on the irradiation-induced creep of zircaloy (Zry) is critical as this mechanism often exceeds thermal creep rates under light-water reactor operating conditions and can be a limiting design characteristic. Additionally, examining irradiation effects in the microstructure at the coating interface is key to understanding the compatibility of the material system. Here, to accelerate the experimental measurement of irradiation creep and microstructure evolution in CrN-Zry, compact, pressurized creep tubes were fabricated and irradiated in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. Miniature, thin-walled rodlets fabricated from annealed Zr-Sn barstock were coated with CrN using physical vapor deposition (PVD) to nominal thicknesses of 4 and 8 μm. Coated and uncoated rodlet specimens were internally pressurized and welded, generating nominal circumferential hoop stresses of 0, 90, or 180 MPa under 300°C irradiation conditions. Twelve specimens were measured diametrically prior to irradiation using a low-cost, automated, contactless laser profilometer developed for this work. Specimens were irradiated in sealed capsules for one 25-day HFIR cycle, accumulating approximately 1.8 $\times$ 10 21 n/cm 2 fast fluence (E n > 10 MeV). The irradiated samples were retrieved and remeasured using the same profilometry system in a shielded hot cell facility. Irradiation creep between specimens was compared using standard statistical tests and showed that both thicknesses of CrN coating had a negligible effect on the irradiation creep strain of the Zry material. Microstructure characterization of pre- and post-irradiated CrN-Zry specimens showed minimal changes due to irradiation but did show a substantial O-rich region at the Zry-CrN interface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Novel imaging technique for thermal neutrons using a fast optical camera

A novel imaging technique for thermal neutrons using a fast optical camera is presented. Thermal neutrons are reacted with 6 Lithium to produce a pair of 2.73 MeV tritium and 2.05 MeV alpha particles, which in turn interact in a thin layer of LYSO crystal scintillator to produce a localized flash of light. These photons are directed by a pair of lenses to a micro-channel plate intensifier, and its output is connected to the optical camera, TPX3CAM. The results from the camera are reconstructed through a custom algorithm. Various cutting parameters were found through data analysis to eliminate the background, and they were shown effective in matching the simulated rate of the neutron source. The system is fast with 40 ns decay time and allows free-space light collection, both vastly enhances flexibility of neutron detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Modulating the dynamics of Brønsted acid sites on PtWOx inverse catalyst

Here metal-metal oxide (M-MO) inverse catalysts are broadly applied. Brønsted acid sites on the oxide overlayers are often hypothesized to drive selective C-O bond activation. However, the Brønsted acid site nature and dynamics under working conditions remain poorly understood due to multiple materials functionalities. Here, we investigate the formation and the dynamics of Brønsted acid and redox sites on PtWO x /C under working conditions. DFT-based thermodynamic calculations and microkinetic modeling reveal a complex interplay between Brønsted acid and redox sites and potentially fast catalyst dynamics at comparable time scales to the chemistry. Combining in situ characterization and probe chemistry, we demonstrate that the density of Brønsted acid sites on the PtWO x /C inverse catalyst could be modulated by up to two orders of magnitude by altering the reaction parameters and by the chemistry itself. We elicit an order of magnitude increase in the acid-catalyzed dehydration average reaction rate by periodic hydrogen pulsing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗