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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 OSTI2020

FASTSim™ (Future Automotive Systems Technology Simulator) [SWR-20-101 and SWR-12-07]

The Future Automotive Systems Technology Simulator (FASTSim™) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. This extremely fast simulation tool features a streamlined user interface and can rapidly perform a variety of tasks using basic computing resources: • less than 0.1 second to simulate second-by-second standard duty cycles • less than 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost • less than 5 minutes to perform powertrain comparisons of efficiency and cost. FASTSim models a variety of vehicle powertrains and fuel converter types: • Conventional vehicles - spark ignition, Atkinson, diesel, and hybrid diesel • Electric-drive vehicles - hybrid, plug-in hybrid, and all-electric • Hydrogen fuel cell vehicles. The default model includes a variety of vehicles and duty cycles and an option for adding additional vehicles and custom cycles: • Packaged with more than 20 vehicles • User interface enables addition of more vehicles • Includes standard U.S. drive cycles as well as European and Japanese cycles. FASTSim is available for download in Microsoft Excel and Python formats here: https://www.nrel.gov/transportation/fastsim.html

Baker, Chad↗
NASA NTRS1990

Scattered light in the echelle modes of the Goddard high-resolution spectrograph aboard the Hubble Space Telescope. I - Analysis of prelaunch calibration data

A study of scattered light in the echelle mode of the Goddard high-resolution spectrograph (GHRS), one of the first-generation science instruments aboard the Hubble Space Telescope, is reported. The data analyzed are from the GHRS ground-based test program and include observations with the 500 channel Digicon detectors through the small science aperture of UV emission-line sources, continuum sources, and continuum sources viewed through molecular absorption cells. The two largest contributors to scattered light are the echelle and cross-disperser, the effects of which have been quantified. A computer simulation using the derived scattering functions demonstrates that the combined effects of these sources of scattered light adequately explain the observed level of interorder light when viewing UV continuum sources. Observing strategies and data reduction algorithms for measuring and removing the effects of the scattered light are discussed.

Cardelli, Jason A.↗
DOE OSTI2024

An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms

Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Two mechanisms of rephasal of circadian rhythms in response to a 180 deg phase shift /simulated 12-hr time zone change/

A model developed by Wever (1966) is considered. The model describes the behavior of circadian rhythms in response to photoperiod phase shifts simulating time zone changes, as a function of endogenous periodicity, light intensity, and direction of phase shift. A description is given of an investigation conducted to test the model upon the deep body temperature rhythm in unrestrained subhuman primates. An evaluation is conducted regarding the applicability of the model in predicting the type and duration of desynchronization induced by simulated time zone changes as a function of endogenous periodicity.

Deroshia, C. W.↗
DOE OSTI2020

Diagnosis of convective organization and cold pools using ARM datasets and evaluation of a unified convection parameterization (UNICON)

Tropical thunderstorms often cluster together. Studies have suggested that the degree to which the tropical thunderstorms are clustered impacts Earth's energy balance and water cycle, as well as extreme precipitation events. However, the processes controlling the spatial distribution of the thunderstorms are poorly understood and are not properly represented in most computer models for weather and climate prediction. Under the goals of better understanding how convection organizes at the mesoscale and advancing the representation of mesoscale convective organization in global climate models, we i) objectively quantified the degrees of convective organization and diagnosed cold pool processes using ARM field campaign observations, ii) examined the organization processes in storm-resolving model simulations, and iii) evaluated the impacts of mesoscale convective organization in global model simulations. The project yielded a firm reference against which the global model representation of mesoscale convective organization and cold pools can be evaluated against and shed new light into the role of parameterized convective organization in the global model simulation of the basic state and variability. Our results revealed two distinct phases of convective clustering during the two-day rain episodes (Cheng et al. 2018) and a new mechanism through which vertical wind shear in the low-troposphere can aid convective organization over tropical oceans (Cheng et al. 2020). It was demonstrated that the interactive representation of cold pools and mesoscale convective organization is key for global models to successfully simulate both the mean state and intraseasonal variability in the tropics (Ahn et al. 2019; 2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗
NASA NTRS2005

Investigation of the Carbon Arc Source as an AM0 Solar Simulator for Use in Characterizing Multi-Junction Solar Cells

The operation of multi-junction solar cells used for production of space power is critically dependent on the spectral irradiance of the illuminating light source. Unlike single-junction cells where the spectral irradiance of the simulator and computational techniques may be used to optimized cell designs, optimization of multi-junction solar cell designs requires a solar simulator with a spectral irradiance that closely matches AM0.

Xu, Jianzeng↗
DOE OSTI2020

Constraining the masses of high-redshift clusters with weak lensing: Revised shape calibration testing for the impact of stronger shears and increased blending

Weak lensing measurements suffer from well-known shear estimation biases, which can be partially corrected for with the use of image simulations. Here we present an analysis of simulated images that mimic Hubble Space Telescope/Advance Camera for Surveys observations of high-redshift galaxy clusters, including cluster specific issues such as non-weak shear and increased blending. Our synthetic galaxies have been generated to have similar observed properties as the background-selected source samples studied in the real images. First, we used simulations with galaxies placed on a grid to determine a revised signal-to-noise-dependent (S/N KSB ) correction for multiplicative shear measurement bias, and to quantify the sensitivity of our KSB+ bias calibration to mismatches of galaxy or PSF properties between the real data and the simulations. Next, we studied the impact of increased blending and light contamination from cluster and foreground galaxies, finding it to be negligible for high-redshift (z > 0.7) clusters, whereas shear measurements can be affected at the ~1% level for lower redshift clusters given their brighter member galaxies. Finally, we studied the impact of fainter neighbours and selection bias using a set of simulated images that mimic the positions and magnitudes of galaxies in Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) data, thereby including realistic clustering. While the initial SExtractor object detection causes a multiplicative shear selection bias of –0.028 ± 0.002, this is reduced to –0.016 ± 0.002 by further cuts applied in our pipeline. Given the limited depth of the CANDELS data, we compared our CANDELS-based estimate for the impact of faint neighbours on the multiplicative shear measurement bias to a grid-based analysis, to which we added clustered galaxies to even fainter magnitudes based on Hubble Ultra Deep Field data, yielding a refined estimate of ~ –0.013. Our sensitivity analysis suggests that our pipeline is calibrated to an accuracy of ~0.015 once all corrections are applied, which is fully sufficient for current and near-future weak lensing studies of high-redshift clusters. As an application, we used it for a refined analysis of three highly relaxed clusters from the South Pole Telescope Sunyaev-Zeldovich survey, where we now included measurements down to the cluster core (r > 200 kpc) as enabled by our work. Compared to previously employed scales (r > 500 kpc), this tightens the cluster mass constraints by a factor 1.38 on average.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Modeling light signals using data from the first pulsed neutron source program at the DUNE vertical drift ColdBox test facility at the CERN Neutrino Platform

In this paper, we present a first quantitative test of detected light signals produced in a pulsed neutron source run in a small vertical drift LArTPC at the CERN Neutrino Platform ColdBox test facility. The ColdBox cryostat, detectors, neutron sources, and particle interactions are modeled and simulated using Fluka. We demonstrate the ability to identify the contribution from neutron interactions using X-ARAPUCA photodetectors, and show first comparisons of data to simulation, which indicate reasonable agreement. A time constant is also fitted from the neutron-beam-off light signal spectrum and found consistent between data and simulation. Several important systematic effects are discussed and serve as guides for future runs at larger LArTPCs.

Detector modelling and simulations I (interaction ↗
DOE OSTI2024

Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria. Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases. The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins. The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform. This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria. This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct Observation of Photoinduced Ion Migration in Lead Halide Perovskites

Unique optoelectronic, electronic, and sensing properties of hybrid organic–inorganic perovskites (HOIPs) are underpinned by the complex interactions between electronic and ionic states. In this study, the photoinduced field ion migration in HOIPs is directly observed. Using newly developed local probe time-resolved techniques, more significant CH 3 NH 3 + migration than I – /Br – migration in HOIPs is unveiled. It is found that light illumination only induces CH 3 NH 3 + migration but not I – /Br – migration. By directly observing temporal changes in bias-induced and photoinduced ion migration in device conditions, it is revealed that light illumination suppresses the bias-induced ion redistribution in the lateral device. These findings, being a necessary compensation of previous understandings of ion migration in HOIPs based on simulations and static and/or indirect measurements, offer advanced insights into the distinct light effects on the migration of organic cation and halides in HOIPs, which are expected to be helpful for improving the performance and the long-term stability of HOIPs optoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A phenomenological rate of injection model for predicting fuel injection with application to mixture formation in light-duty diesel engines

Fuel injection rate laws are one of the most important pieces of information needed when modeling engine combustion with computational fluid dynamics. In this study, a simple phenomenological model of a common-rail injector was developed and calibrated for the Bosch CRI2.2 platform. The model requires three tunable parameter fits, making it relatively easy to calibrate and suitable for injector modeling when high-fidelity information about the internal injector’s geometry and electrical circuit details are not available. Each injection pulse is modeled as a sequence of up to four stages: an injection needle mechanical opening transient, a full-lift viscous flow inertial transient, a Bernoulli steady-state stage, and a needle descent transient. Parameters for each stage are obtained as polynomial fits from measured injection rate properties. The model enforces total injected mass, and the intermediate stages are only introduced if the injection pulse duration is long enough. Experimental rates of injection from two separate campaigns on the same injector were used to calibrate the model. The model was first validated against measured injection rate laws featuring pilot injections, short partially premixed combustion pulses, and conventional diesel combustion injection strategies. Then, it was employed as an input to engine computational fluid dynamics simulations, which were run to simulate experiments of mixture formation in an optically accessible light-duty diesel engine. It was found that, though simple, this model is capable of predicting both pilot and main injection pulse mass flow rates well: the simulations yielded accurate predictions of in-cylinder equivalence ratio distributions from injection strategies for both partially premixed combustion and pilot injections. Also, once calibrated, the model produced appropriate results for a wide range of injected mass and rail pressure values. Finally, it was observed that usage of such a relatively simple model can be a good choice when high-fidelity injection rate input and highly detailed information of the injector’s geometry and operation are not available, particularly as noticeable discrepancies can be present also among different experimental campaigns on similar hardware.

42 ENGINEERING↗
NASA NTRS1988

Three-axis attitude determination via Kalman filtering of magnetometer data

A three-axis Magnetometer/Kalman Filter attitude determination system for a spacecraft in low-altitude Earth orbit is developed, analyzed, and simulation tested. The motivation for developing this system is to achieve light weight and low cost for an attitude determination system. The extended Kalman filter estimates the attitude, attitude rates, and constant disturbance torques. Accuracy near that of the International Geomagnetic Reference Field model is achieved. Covariance computation and simulation testing demonstrate the filter's accuracy. One test case, a gravity-gradient stabilized spacecraft with a pitch momentum wheel and a magnetically-anchored damper, is a real satellite on which this attitude determination system will be used. The application to a nadir pointing satellite and the estimation of disturbance torques represent the significant extensions contributed by this paper. Beyond its usefulness purely for attitude determination, this system could be used as part of a low-cost three-axis attitude stabilization system.

Martel, Francois↗
DOE OSTI2019

Summary of Grizzly Development for Advanced Reactor Structural Materials

This summary report contains an overview of work performed during Fiscal Year 2019 under the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) Fuels Product Line work package entitled "MS-19IN020106 - GRIZZLY - INL". Grizzly is a code based on the MOOSE framework that has been under development for several years funded by the US Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Prior to 2019, Grizzly development was focused on development of capabilities needed to simulate the effects of aging mechanisms in light water reactor (LWR) components. The goal of this LWR-focused work has been to develop tools that can be used to assess the ability of existing LWRs to perform safety in long term operation (LTO) scenarios. This LWR-focused work has primarily focused on the effects of reactor pressure vessel (RPV) embrittlement and aging of reinforced concrete structures. Grizzly development to support LWR degradation needs is still ongoing, but starting in 2019, Grizzly’s capabilities are being expanded to also meet growing needs for a tool to address structural component integrity and degradation in advanced reactors. A simulation capability for advanced reactor components has many of the same basic requirements that one for LWRs does, such as the ability to solve coupled systems of partial differential equations that arise from the fact that many of the problems of interest involve multiple coupled physics. The materials issues also inherently involve multiple length scales, with the response at the engineering scale being strongly affected by mechanisms occurring at atomistic and mesoscopic scales.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Oscillatory and Collective Dynamics of Gold‐Nanoparticle‐Laden Droplets Driven by Photothermal‐Induced Thermocapillarity

Droplets have long intrigued researchers due to their ability to exhibit complex and fascinating behavior when subjected to external stimuli. Here, a coupled oscillatory behavior of gold-nanoparticle-surfactant-laden aqueous droplets is investigated at an oil-oil interface stimulated by light. This study shows that the interaction between light and the droplets gives rise to a range of oscillatory modes, including bouncing and clustering, where droplets exhibit collective movement. From experiment and numerical simulations, this study elucidates the underlying mechanism: upon laser irradiation, gold nanoparticles convert light into heat, generating asymmetric thermal gradients that drive upward thermocapillary flows and a hydrodynamic force from photothermal convection. These forces compete with gravity and buoyancy to induce droplet bouncing, while the resulting asymmetric flow fields bias neighboring droplets toward the illuminated droplet, leading to clustering. These findings not only expand the library of dynamic droplet behavior but also offer insights into the potential applications of light-driven systems in materials science, soft robotics, and microfluidics.

Marangoni effect↗
NASA NTRS1993

Orbital docking system centerline color television camera system test

A series of tests was run to verify that the design of the centerline color television camera (CTVC) system is adequate optically for the STS-71 Space Shuttle Orbiter docking mission with the Mir space station. In each test, a mockup of the Mir consisting of hatch, docking mechanism, and docking target was positioned above the Johnson Space Center's full fuselage trainer, which simulated the Orbiter with a mockup of the external airlock and docking adapter. Test subjects viewed the docking target through the CTVC under 30 different lighting conditions and evaluated target resolution, field of view, light levels, light placement, and methods of target alignment. Test results indicate that the proposed design will provide adequate visibility through the centerline camera for a successful docking, even with a reasonable number of light failures. It is recommended that the flight deck crew have individual switching capability for docking lights to provide maximum shadow management and that centerline lights be retained to deal with light failures and user preferences. Procedures for light management should be developed and target alignment aids should be selected during simulated docking runs.

Mongan, Philip T.↗
DOE OSTI2020

Stabilization of light-induced effects in Si modules for IEC 61215 design qualification

Standardized testing of commercial photovoltaic modules is widely used around the world and decreases risks of module failures. Such testing also reduces financial risks for module manufacturers and customers. This work examines the expected impact of certain defects in silicon (Si) modules during standardized accelerated testing. Specifically, the behavior of boron-oxygen (BO) light-induced degradation (LID) and light- and elevated temperature-induced degradation (LeTID) are simulated during some of the stress tests in IEC 61215. LID and LeTID reaction rates at qualification temperatures are estimated from earlier published data. It is demonstrated the BO-related LID may cause some false positives and false negatives when IEC 61215 tests are performed as prescribed in the 2016 published version. Possible stabilization steps to avoid these false results are suggested. State changes for the defects causing LeTID occur much more slowly than those causing BO LID, and therefore LeTID is predicted to have a lesser impact on the IEC 61215 stress tests results.

14 SOLAR ENERGY↗
DOE OSTI2020

Calorimetry for low-energy electrons using charge and light in liquid argon

Precise calorimetric reconstruction of 5–50 MeV electrons in liquid argon time projection chambers (LArTPCs) will enable the study of astrophysical neutrinos in DUNE and could enhance the physics reach of oscillation analyses. Liquid argon scintillation light has the potential to improve energy reconstruction for low-energy electrons over charge-based measurements alone. Here we demonstrate light-augmented calorimetry for low-energy electrons in a single-phase LArTPC using a sample of Michel electrons from decays of stopping cosmic muons in the LArIAT experiment at Fermilab. Michel electron energy spectra are reconstructed using both a traditional charge-based approach as well as a more holistic approach that incorporates both charge and light. A maximum-likelihood fitter, using LArIAT’s well-tuned simulation, is developed for combining these quantities to achieve optimal energy resolution. A sample of isolated electrons is simulated to better determine the energy resolution expected for astrophysical electron-neutrino charged-current interaction final states. In LArIAT, which has very low wire noise and an average light yield of 18 pe/MeV, an energy resolution of σ/E≃9.3%/E⊕1.3% is achieved. Samples are then generated with varying wire noise levels and light yields to gauge the impact of light-augmented calorimetry in larger LArTPCs. At a charge-readout signal-to-noise of S/N≃30, for example, the energy resolution for electrons below 40 MeV is improved by ≈10%, ≈20%, and ≈40% over charge-only calorimetry for average light yields of 10 pe/MeV, 20 pe/MeV, and 100 pe/MeV, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗