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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which can be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microexplosions and ignition dynamics in engineered aluminum/polymer fuel particles

Aluminum particles are widely used as a metal fuel in solid propellants. However, poor combustion efficiencies and two-phase flow losses result due in part to particle agglomeration. Engineered composite particles of aluminum (Al) with inclusions of polytetrafluoroethylene (PTFE) or low-density polyethylene (LDPE) have been shown to improve ignition and yield smaller agglomerates in solid propellants, recently. Reductions in agglomeration were attributed to internal pressurization and fragmentation (microexplosions) of the composite particles at the propellant surface. We explore the mechanisms responsible for microexplosions in order to better understand the combustion characteristics of composite fuel particles. Single composite particles of Al/PTFE and Al/LDPE with diameters between 100 and 1200 µm are ignited on a substrate to mimic a burning propellant surface in a controlled environment using a CO 2 laser in the irradiance range of 78–7700 W/cm 2 . Furthermore, the effects of particle size, milling time, and inclusion content on the resulting ignition delay, product particle size distributions, and microexplosion tendencies are reported. For example particles with higher PTFE content (30 wt%) had laser flux ignition thresholds as low as 77 W/cm 2 , exhibiting more burning particle dispersion due to microexplosions compared to the other materials considered. Composite Al/LDPE particles exhibit relatively high ignition thresholds compared to Al/PTFE particles, and microexplosions were observed only with laser fluxes above 5500 W/cm 2 due to low LDPE reactivity with Al resulting in negligible particle self-heating. However, results show that microexplosions can occur for Al containing both low and high reactivity inclusions (LDPE and PTFE, respectively) and that polymer inclusions can be used to tailor the ignition threshold. Furthermore, this class of modified metal particles shows significant promise for application in many different energetic materials that use metal fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Autonomous vehicles↗
DOE OSTI2023

Ammonia Electrosynthesis from Nitrate Using a Ruthenium–Copper Cocatalyst System: A Full Concentration Range Study

Electrochemical synthesis of ammonia via the nitrate reduction reaction (NO3RR) has been intensively researched as an alternative to the traditional Haber–Bosch process. Most research focuses on the low concentration range representative of the nitrate level in wastewater, leaving the high concentration range, which exists in nuclear and fertilizer wastes, unexplored. The use of a concentrated electrolyte (≥1 M) for higher rate production is hampered by poor hydrogen transfer kinetics. Herein, we demonstrate that a cocatalytic system of Ru/Cu 2 O catalyst enables NO3RR at 10.0 A in 1 M nitrate electrolyte in a 16 cm 2 flow electrolyzer, with 100% faradaic efficiency toward ammonia. Detailed mechanistic studies by deuterium labeling and operando Fourier transform infrared (FTIR) spectroscopy allow us to probe the hydrogen transfer rate and intermediate species on Ru/Cu 2 O. Ab initio molecular dynamics (AIMD) simulations reveal that adsorbed hydroxide on Ru nanoparticles increases the density of the hydrogen-bonded water network near the Cu 2 O surface, which promotes the hydrogen transfer rate. Finally, our work highlights the importance of engineering synergistic interactions in cocatalysts for addressing the kinetic bottleneck in electrosynthesis.

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

Simulation of Mesoscale Cellular Convection in Marine Stratocumulus: 2. Nondrizzling Conditions

This is the second of two large-eddy simulation studies on the mechanisms of mesoscale cellular organization in drizzling (open cells) and nondrizzling marine stratocumulus (closed cells). This study uses a hard nudging approach which maintains fixed horizontal-mean temperature and humidity profiles for a well-mixed boundary layer with a constant boundary layer depth. For the case studied, closed cells develop and broaden by 32 hr to an aspect ratio of 25. Simulations show that the closed-cell mesoscale cellular convection is driven by positive feedback from cloud-induced mesoscale perturbations of longwave radiative cooling. A conceptual model for closed-cell stratocumulus as a mesoscale wavelength hydrodynamic instability in which mesoscale moist and dry anomalies spontaneously grow is presented. In simulations in which long-wavelength sinusoidal moisture anomalies are initially imposed, these anomalies evolve into amplifying closed cells. The cell structure is visualized with a compositing approach based on sorting grid columns by their mesoscale-smoothed total water path. A thermally direct mesoscale circulation pattern develops in the interior of the boundary layer with buoyant mesoscale updrafts, thicker cloud, and a slightly higher capping inversion in the moister columns. There is a mesoscale flow of above-inversion air down the slightly sloping capping inversion from the moist to the dry regions, reinforced by cloud top radiative cooling. This strengthens the mesoscale anomalies by preferentially cooling and drying the already dry regions. The sloping inversion flow is not driven as efficiently if the radiative cooling is artificially horizontally homogenized, partly disrupting this positive feedback and the resulting closed-cell development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancing detection of topological order by local error correction

The exploration of topologically-ordered states of matter is a long-standing goal at the interface of several subfields of the physical sciences. Such states feature intriguing physical properties such as long-range entanglement, emergent gauge fields and non-local correlations, and can aid in realization of scalable fault-tolerant quantum computation. However, these same features also make creation, detection, and characterization of topologically-ordered states particularly challenging. Motivated by recent experimental demonstrations, we introduce a paradigm for quantifying topological states—locally error-corrected decoration (LED)—by combining methods of error correction with ideas of renormalization-group flow. Our approach allows for efficient and robust identification of topological order, and is applicable in the presence of incoherent noise sources, making it particularly suitable for realistic experiments. We demonstrate the power of LED using numerical simulations of the toric code under a variety of perturbations. We subsequently apply it to an experimental realization, providing new insights into a quantum spin liquid created on a Rydberg-atom simulator. Finally, we extend LED to generic topological phases, including those with non-abelian order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Automated Approach for Construction of Long-Term, Data-Intensive Watershed Models

Watershed models such as the Hydrological Simulation Program in FORTRAN (HSPF) are frequently used to analyze large-scale water quantity and water quality issues. The construction of HSPF models is a difficult and time-consuming process, because it requires compilation of extensive quantities of data into formatted files followed by a simultaneous fitting of many uncertain parameters. Because of these complications, studies are often limited to calibration periods of only a few years even when analyzing long time-scale issues such as climate and land-use changes that are difficult or impossible to reproduce. High-level, open source programming languages provide an environment for automating the extraction and processing of various sources of data in addition to the calibration process required by HSPF. Recently developed software can be used to build HSPF input files, run simulations, and postprocess simulation results using the Python programming language. The combination of tools in Python, public data sets on the Internet, and software extensions enables rapid development of long-term, reproducible, and sophisticated models for new hydrologic insight. Herein, the utility of these tools is illustrated by developing an automated 30-year HSPF model with a Nash-Sutcliffe efficiency of 0.88 for monthly flows and 0.75 for daily flows in a simulation time of approximately 3h. The integration of HSPF with a high-level programming language creates opportunities to more rigorously explore model assumptions, calibration methods, and alternative data sets.

Lampert, Dave J↗
DOE OSTI2024

Cosmic quenching and scaling laws for the evolution of supermassive black holes and host galaxies

ABSTRACT Observations suggest a co-evolution of supermassive black holes (SMBHs) and host galaxies. In this paper, we consider the mass and energy flow in a near-equilibrium bulge suffused by gases of varying temperatures. By assuming the rate of energy flow independent of the distance r from the bulge center and the local virial equilibrium for permeated gases on scale r, a key parameter $\varepsilon _b$ was identified that quantifies the mass and energy flow in gases and the efficiency of gas cooling (or the "specific" cooling rate per unit mass), and thus regulates the co-evolution of both SMBHs and hosts. With the help of Illustris simulations and observations, we determined the redshift variation $\varepsilon _b\propto (1+z)^{5/2}$. A higher $\varepsilon _b$ in the early Universe means a higher specific cooling rate that allows rapid evolution of SMBHs and hosts. This simple theory, characterized by a single parameter $\varepsilon _b$, provides the dominant mean cosmic evolution of SMBHs and hosts. All other transient phenomena may only contribute to the dispersion around this mean evolution. Based on this theory and relevant assumptions, scaling laws involving $\varepsilon _b$ were identified for the evolution of SMBHs and hosts. For host galaxies, the mass–size relation $M_b\propto \varepsilon _b^{2/3}r_b^{5/3}G^{-1}$, the dispersion–size relation $\sigma _b^2\propto (\varepsilon _b r_b)^{2/3}\propto (1+z)$, or the mass–dispersion relation $M_b\propto \varepsilon _b^{-1}G^{-1}\sigma _b^5$ were identified, where $r_b\propto (1+z)^{-1}$ is the bulge size. For SMBHs, three evolution phases were found involving an initial rapid growth stage with a rising luminosity $L_B\propto (\varepsilon _b M_{\rm BH})^{4/5}$, a transition stage with a declining $L_B\propto \varepsilon _b^2 M_{\rm BH} \propto (1+z)^5$, and a dormant stage with $L_B\propto (\varepsilon _b M_{\rm BH})^{4/3}$. Our results suggest a rapid initial super-Eddington growth in a short period with a new redshift-dependent luminosity limit $L_X\propto\varepsilon _b^{4/5}M_{\rm BH}^{4/5}G^{-1/5}c$, in contrast to the Eddington limit. Analytical solutions were formulated for the BH mass function $\Phi _{\rm BH}$, active galactic nucleus (AGN) mass function $\Phi _{\rm AGN}$, and duty cycle U that predict $\Phi _L\propto L^{-1/5}$ for the faint-end luminosity function, $\Phi _{\rm AGN}\propto M^{-1/5}$ for small-mass-end AGN mass function $\Phi _L$, and $U\propto M^{-1/5}$ at high redshift.

(galaxies:) quasars: supermassive black holes↗
DOE OSTI2024

Swarm Intelligence Based Optimal Design of Local Volt/Var Control Function for Distributed Energy Resources

The increasing penetration of renewable based distributed energy resources (DERs) in distribution network (DN) leads to larger and more frequent voltage variation in distributions network (DN), thus posing challenges on voltage control. Real-time local voltage control method is a promising solution for the above issue. However, the local voltage control function needs to be customized and optimized according to real distribution system condition. In this paper, a swarm intelligence based Volt/Var control optimal design method (SO-VVC) is proposed to optimize the control function. Compared with existing approaches, the proposed method can not only represent the nonlinear behaviour of power flow but is also computation efficient. The performance of the proposed SO-VVC is demonstrated by case studies on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2025

Integrated Routing and Traffic Signal Control for CAVs via Reinforcement Learning Approach

Incorporating Connected and Automated Vehicles (CAVs) into urban traffic networks presents opportunities and challenges for traffic management systems. This paper aims to develop an integrated routing and traffic signal control system designed explicitly for CAVs, utilizing a Reinforcement Learning (RL) approach. The objective is to enhance traffic flow and improve overall transportation efficiency in the controlled areas. We propose an innovative framework that employs the Deep Reinforcement Learning (DRL) algorithm, especially the Deep Q-network (DQN), to dynamically adjust the number of vehicles in the routes and the duration of traffic signals. Our simulation results demonstrate that a DQN agent successfully optimizes the number of vehicles in the routes and traffic signal timings of traffic signal controllers, eventually reducing total travel time. The study illustrates the potential usage of RL-based systems in managing routing and traffic signals for CAVs, offering a promising opportunity for future urban traffic management strategies.

Park, Jiho [New York University]↗
DOE OSTI2015

Reliability and Maintainability Data for Liquid Metal Cooling Systems

One of the coolants of interest for future fusion breeding blankets is lead-lithium. As a liquid metal it offers the advantages of high temperature operation for good station efficiency, low pressure, and moderate flow rate. This coolant is also under examination for use in test blanket modules to be used in the ITER international project. To perform reliability, availability, maintainability and inspectability (RAMI) assessment as well as probabilistic safety assessment (PSA) of lead-lithium cooling systems, component failure rate data are needed to quantify the system models. RAMI assessment also requires repair time data and inspection time data. This paper presents a new survey of the data sets that are available at present to support RAMI and PSA quantification. Recommendations are given for the best data values to use when quantifying system models.

maintainability data↗
DOE OSTI2025

Preliminary Testing of a Continuous Cryopump for Primary Fusion Device Pumping and Direct Internal Recycling

Here, the concept of directly recirculating fusion machine exhaust gas, bypassing the tritium plant, to make fuel pellets was proposed in the 1990s and later termed direct internal recycling (DIR). In the DIR concept, the residual fusion fuel in the machine exhaust stream is separated from impurities locally and diverted directly to the fueling systems, bypassing isotopic separation and other processing equipment, and therefore significantly reducing the required size of the fuel processing plant, reducing plant inventory, and thus increasing the economic viability of fusion as an energy source. One concept for DIR consists of a series of cryogenic pumps to separate the impurities from the machine exhaust gas using different triple point temperatures and saturation curves of exhaust constituents. In this concept, the plasma exhaust is initially passed through an impurity trap operating at ~25–30 K to desublimate impurities such as hydrocarbons, argon, oxygen, and nitrogen. The resulting process stream will consist of DT fuel and helium. The process stream is then pumped by a continuous cryopump known as a “snail pump.” This pump is a steady-state continuous cryopump that desublimates all remaining exhaust gas constituents while allowing helium, a byproduct of the fusion reaction, to pass through. The helium is pumped to the tritium plant for processing while the desublimated material is continuously scraped off, heated up, and transported to the fueling system. This article will present the cryogenic DIR concept and outline the design and operation of the snail pump, along with results from preliminary testing. Tests to assess pumping and separation efficiency found that at D2 flows below 50.7 Pa ⋅ m3/s with 1% helium, the pump is capable of pumping and separating the gas with a resulting DIR fraction of >99%, with no helium entrained in the primary fuel exhaust stream. The main limitation is due to the thermal performance of the cryogenic circuits of the pump, which will be addressed in future testing.

Gebhart III, Trey E. [Oak Ridge National Laborator↗
DOE OSTI2015

Multiphase Modeling of Geologic Carbon Sequestration in Saline Aquifers

Abstract Geologic carbon sequestration ( GCS ) is being considered as a climate change mitigation option in many future energy scenarios. Mathematical modeling is routinely used to predict subsurface CO 2 and resident brine migration for the design of injection operations, to demonstrate the permanence of CO 2 storage, and to show that other subsurface resources will not be degraded. Many processes impact the migration of CO 2 and brine, including multiphase flow dynamics, geochemistry, and geomechanics, along with the spatial distribution of parameters such as porosity and permeability. In this article, we review a set of multiphase modeling approaches with different levels of conceptual complexity that have been used to model GCS . Model complexity ranges from coupled multiprocess models to simplified vertical equilibrium (VE) models and macroscopic invasion percolation models. The goal of this article is to give a framework of conceptual model complexity, and to show the types of modeling approaches that have been used to address specific GCS questions. Application of the modeling approaches is shown using five ongoing or proposed CO 2 injection sites. For the selected sites, the majority of GCS models follow a simplified multiphase approach, especially for questions related to injection and local‐scale heterogeneity. Coupled multiprocess models are only applied in one case where geomechanics have a strong impact on the flow. Owing to their computational efficiency, VE models tend to be applied at large scales. A macroscopic invasion percolation approach was used to predict the CO 2 migration at one site to examine details of CO 2 migration under the caprock.

Bandilla, Karl W.↗
DOE OSTI2015

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm{sup 3} in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

GPU-FPX

GPU-FPX is a tool based on NVBit that detects and analyzes floating-point exceptions on NVIDIA GPUs through binary instrumentation. Its purpose is to detect and report the occurrences of floating-point exceptions during numerical computations, offering efficient location detections and exception flow. GPUFPX achieves exceptional performance, being 16x faster than comparable prior tools, such as BinFPE.

Laguna Peralta, Ignacio↗
DOE OSTI2013

Hydrodynamic and shock heating instabilities of liquid metal strippers for RIA

Stripping of accelerated ions is a key problem for the design of RIA to obtain high efficiency. Thin liquid Lithium film flow is currently considered as stripper for RIA ion beams to obtain higher Z for following acceleration: in extreme case of Uranium from Z=29 to Z=60-70 (first stripper) and from Z=70 till full stripping Z=92 (second stripper). Ionization of ion occurs due to the interaction of the ion with electrons of target material (Lithium) with the loss of parts of the energy due to ionization, Q U , which is also accompanied with ionization energy losses, Q Li of the lithium. The resulting heat is so high that can be removed not by heat conduction but mainly by convection, i.e., flowing of liquid metal across beam spot area. The interaction of the beam with the liquid metal generates shock wave propagating along direction perpendicular to the beam as well as excites oscillations along beam direction. We studied the dynamics of these excited waves to determine conditions for film stability at the required velocities for heat removal. It will allow optimizing jet nozzle shapes and flow parameters to prevent film fragmentation and to ensure stable device operation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Development of quantum dot materials for infrared cameras (Final CRADA Report)

The aim of this project was to develop scalable methods to produce infrared (IR) mercury telluride (HgTe) colloidal quantum dot (CQD) thin films and demonstrate their utility in a proof-of-concept monolithic SWIR focal plane array (FPA). These objectives were accomplished by scaling up the HgTe CQD synthesis, characterizing physical and electrical properties of HgTe CQDs, evaluating solution-processed coating methods for quality and efficiency, and developing a process flow to integrate HgTe CQDs with commercial-off-the-shelf silicon CMOS readout circuits by solution-processed coating to produce monolithic FPAs. The FPA is the image sensor in an infrared imaging system responsible for detecting and processing reflected or emitted light into an infrared image of the scene under observation. The quality of the image is determined by the sensitivity and resolution of the image sensor in the system. Higher resolution IR FPAs enable higher throughput in manufacturing quality assurance, wider field of view for autonomous navigation, and longer range surveillance for defense.

77 NANOSCIENCE AND NANOTECHNOLOGY↗