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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Application of parallel distributed Lagrange multiplier technique to simulate coupled Fluid-Granular flows in pipes with varying Cross-Sectional area

Fluid-granular flows are common phenomena in nature and industry. Here, an efficient computational technique based on the distributed Lagrange multiplier method is utilized to simulate complex fluid-granular flows. Each particle is explicitly resolved on an Eulerian grid as a separate domain, using solid volume fractions. The fluid equations are solved through the entire computational domain, however, Lagrange multiplier constrains are applied inside the particle domain such that the fluid within any volume associated with a solid particle moves as an incompressible rigid body. The particle–particle interactions are implemented using explicit force-displacement interactions for frictional inelastic particles similar to the DEM method with some modifications using the volume of an overlapping region as an input to the contact forces. Here, a parallel implementation of the method is based on the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

In-situ fabrication of graded material with the application of a horizontal magnetic field during directional solidification

Highlights: • The horizontal magnetic field caused the migration of primary grains and the formation of graded material. • TEMF play a major effect on the formation of graded material. • The magnitude of TEMF increases with the increase of magnetic field intensity. • This work initiates a new method to prepare the “graded material” via an applied horizontal magnetic field. - Abstract: The present paper proposes a method of graded materials preparation under a low horizontal magnetic field during directional solidification. The external horizontal magnetic field was applied to the mushy zone of the directionally solidified Al-10 wt% Cu and Al-18 wt% Si samples, which was perpendicular to the growth direction. Experimental results demonstrate that the applied horizontal magnetic field produces a gradient size distribution of the primary α(Al) grains in Al-10 wt% Cu alloys and a gradient fraction distribution of primary Si particles in Al-18 wt% Si alloys. 3D numerical simulations indicate that the formation of graded structure should be attributed to the migration of primary phase driven by the thermoelectric magnetic force (TEMF). The formation of segregation channel should be attributed to the TEM convection (TEMC) in the mushy zone. Further, in situ synchrotron X-ray radiography observations of the initial transient of directional solidification show that the primary α(Al) phases were migrated approximately along the direction perpendicular to the magnetic field. These results suggest that the TEM effects can greatly change the growth of primary grains and the solidification structure, and the application of an external horizontal magnetic field would be beneficial to fabricate the graded material during directional solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2016

On the progenitors of local group novae. II. The red giant nova rate of M31

In our preceding paper, Liverpool Telescope data of M31 novae in eruption were used to facilitate a search for their progenitor systems within archival Hubble Space Telescope data, with the aim of detecting systems with red giant secondaries (RG-novae) or luminous accretion disks. From an input catalog of 38 spectroscopically confirmed novae with archival quiescent observations, likely progenitors were recovered for 11 systems. Here we present the results of the subsequent statistical analysis of the original survey, including possible biases associated with the survey and the M31 nova population in general. As part of this analysis, we examine the distribution of optical decline times (t{sub 2}) of M31 novae, how the likely bulge and disk nova distributions compare, and how the M31 t{sub 2} distribution compares to that of the Milky Way. Using a detailed Monte Carlo simulation, we determine that 30{sub −10}{sup +13}% of all M31 nova eruptions can be attributed to RG-nova systems, and at the 99% confidence level, >10% of all M31 novae are RG-novae. This is the first estimate of a RG-nova rate of an entire galaxy. Our results also imply that RG-novae in M31 are more likely to be associated with the M31 disk population than the bulge; indeed, the results are consistent with all RG-novae residing in the disk. If this result is confirmed in other galaxies, it suggests that any Type Ia supernovae that originate from RG-nova systems are more likely to be associated with younger populations and may be rare in old stellar populations, such as early-type galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Real-time simulator and controller of power system using distributed data streaming server

Systems and methods for simulating and controlling a power system in real time, using a controller, are provided. The controller includes a simulation layer to simulate an operation of the power system, a disturbance generation layer to provide data to the simulation layer to disturb the simulated operation of the power system, an application layer to display the simulated operation of the power system and generate a control signal to control, based on the simulated operation of the power system, at least one element of the power system, and a distributed data streaming server (D2S2) to allow interoperability among the simulation layer, the disturbance layer, and the application layer.

Li, Fangxing↗
DOE OSTI2012

Regenerative Markov Chain Monte Carlo for any distribution.

While Markov chain Monte Carlo (MCMC) methods are frequently used for difficult calculations in a wide range of scientific disciplines, they suffer from a serious limitation: their samples are not independent and identically distributed. Consequently, estimates of expectations are biased if the initial value of the chain is not drawn from the target distribution. Regenerative simulation provides an elegant solution to this problem. In this article, we propose a simple regenerative MCMC algorithm to generate variates for any distribution

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

On the Use of the Beta Distribution in Probabilistic Resource Assessments

The triangular distribution is a popular choice when it comes to modeling bounded continuous random variables. Its wide acceptance derives mostly from its simple analytic properties and the ease with which modelers can specify its three parameters through the extremes and the mode. On the negative side, hardly any real process follows a triangular distribution, which from the outset puts at a disadvantage any model employing triangular distributions. At a time when numerical techniques such as the Monte Carlo method are displacing analytic approaches in stochastic resource assessments, easy specification remains the most attractive characteristic of the triangular distribution. The beta distribution is another continuous distribution defined within a finite interval offering wider flexibility in style of variation, thus allowing consideration of models in which the random variables closely follow the observed or expected styles of variation. Despite its more complex definition, generation of values following a beta distribution is as straightforward as generating values following a triangular distribution, leaving the selection of parameters as the main impediment to practically considering beta distributions. This contribution intends to promote the acceptance of the beta distribution by explaining its properties and offering several suggestions to facilitate the specification of its two shape parameters. In general, given the same distributional parameters, use of the beta distributions in stochastic modeling may yield significantly different results, yet better estimates, than the triangular distribution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the C ommunity E arth S ystem M odel

Abstract This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super‐Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual‐mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double‐ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden‐Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM's low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved‐scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Simulating wind power forecast error distributions for spatially aggregated wind power plants

Dispersion and aggregation of wind power plants lower the uncertainty of wind power by reducing wind power forecasting errors. Using quantitative methods, this paper studies the dispersion's impact on the uncertainty of the aggregated wind power production. A method to simulate day-ahead forecast error distributions at different dispersion and forecasting skill scenarios is presented. The proposed method models the uncertainty of wind power forecasting on an annual basis and at different levels of production. As a result, the uncertainty in the forecasting of spatially dispersed wind power plants is modelled using two continuous distributions: Laplace and beta distribution. The analysis shows that even the production level uncertainty can be modelled in various dispersion and forecasting skill scenarios. The model for aggregated forecast error distributions requires only four variables: capacity-weighted distance of the total wind power plant fleet, mean of the site-specific mean absolute errors (MAEs), number of aggregated wind power plants, and the mean variability of the elevations from the proximities of the aggregated wind power plants. Here, the results are especially promising when the number of aggregated wind power plants exceeds five, the terrain complexity is low or moderate, and the aggregation region is large. This is demonstrated through a case study for Texas, United States.

17 WIND ENERGY↗
DOE OSTI2012

Study of the longitudinal distribution of power generated in a random distributed feedback Raman fibre laser with unidirectional pumping

The longitudinal distribution of the Stokes-component power in a Raman fibre laser with a random distributed feedback and unidirectional pumping is measured. The fibre parameters (linear loss and Rayleigh backscattering coefficient) are calculated based on the distributions obtained. A numerical model is developed to describe the lasing power distribution. The simulation results are in good agreement with the experimental data. (optical fibres, lasers and amplifiers. properties and applications)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Southeast Regional Carbon Sequestration Partnership (SECARB): Completed History Match: Subsurface Plume Development, Early Test

In this paper, we compare 4D seismic interpretations of CO 2 plume evolution with fluid flow numerical simulation results for the SECARB Early test at Cranfield, Mississippi. Historic pressure trends, oil and gas production rates and current CO 2 -EOR production data from the field were history matched and tuned model used for predictive simulations. For CO 2 -EOR operations the tuned model results showing CO 2 plume distribution and CO 2 first arrival (break-through) times in production wells were compared to the available field data. Reasonable matches were observed with breakthrough times. However 4D seismic interpretations of saturated region distributions and simulation results mismatch in some significant ways, likely showing limitations in 4D seismic interpretations for Cranfield. The tuned model then used to predict reservoir response and storage capacity in different field development scenarios. We compared hypothetical scenarios where the operator decided to transition into CO 2 injection without oil production (CO 2 -EORT) when oil production is not economical versus a scenario of continuing with CO 2 -EOR. Our results show that CO 2 -EOR can store more CO 2 and operations will last longer whereas if switched to CO 2 -EORT field has to be abandoned earlier because of out-of-area movement of the CO 2 plume. However, the amount of CO2 stored per year during the operational period is larger for CO 2 -EORT.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Distributed Wind Representation in Modeling and Simulation Tools: An Assessment of Existing Tools

PNNL evaluated the inclusion of wind in distributed energy resource modeling and simulation tools. Tools were assessed based on a survey of publicly available and readily accessible information. While the authors have made a good faith effort to understand these tools, PNNL does not know the intentions of the developers and acknowledges that some tool capabilities or features may not have been accurately captured in this assessment. This evaluation informs an ongoing effort by PNNL to modernize existing tools both directly by working with developers of some tools and indirectly by providing best practices on how different types of tools could enhance certain modeling features to improve distributed wind’s representation and valuation.

17 WIND ENERGY↗
DOE OSTI2018

Combining Simulation and Emulation Systems for Smart Grid Planning and Evaluation

Software-defined networking (SDN) enables efficient network management. As the technology matures, utilities are looking to integrate those benefits to their operations technology (OT) networks. To help the community to better understand and evaluate the effects of such integration, we develop DSSnet, a testing platform that combines a power distribution system simulator and an SDN-based network emulator for smart grid planning and evaluation. DSSnet relies on a container-based virtual time system to achieve efficient synchronization between the simulation and emulation systems. To enhance the system scalability and usability, we extend DSSnet to support a distributed controller environment. To enhance system fidelity, we extend the virtual time system to support kernel-based switches. In conclusion, we also evaluate the system performance of DSSnet and demonstrate the usability of DSSnet with a resilient demand response application case study.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

Abstract Representing cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

High spatial resolution Fe xii observations of solar active regions

We use UV spectral observations of active regions with the Interface Region Imaging Spectrograph (IRIS) to investigate the properties of the coronal Fe xii 1349.4 Å emission at unprecedented high spatial resolution (∼0.33″). We find that by using appropriate observational strategies (i.e., long exposures, lossless compression), Fe xii emission can be studied with IRIS at high spatial and spectral resolution, at least for high-density plasma (e.g., post-flare loops and active region moss). We find that upper transition region (TR; moss) Fe xii emission shows very small average Doppler redshifts (v{sub D} ∼ 3 km s{sup −1}) as well as modest non-thermal velocities (with an average of ∼24 km s{sup −1} and the peak of the distribution at ∼15 km s{sup −1}). The observed distribution of Doppler shifts appears to be compatible with advanced three-dimensional radiative MHD simulations in which impulsive heating is concentrated at the TR footpoints of a hot corona. While the non-thermal broadening of Fe xii 1349.4 Å peaks at similar values as lower resolution simultaneous Hinode Extreme Ultraviolet Imaging Spectrometer (EIS) measurements of Fe xii 195 Å, IRIS observations show a previously undetected tail of increased non-thermal broadening that might be suggestive of the presence of subarcsecond heating events. We find that IRIS and EIS non-thermal line broadening measurements are affected by instrumental effects that can only be removed through careful analysis. Our results also reveal an unexplained discrepancy between observed 195.1/1349.4 Å Fe xii intensity ratios and those predicted by the CHIANTI atomic database.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Limitations of Separate Cloud and Rain Categories in Parameterizing Collision-Coalescence for Bulk Microphysics Schemes

Warm rain collision-coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud-to-rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two-category, two-moment scheme with a reduced size threshold, or a four-moment single-category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single-category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single-category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision-coalescence rates.

54 ENVIRONMENTAL SCIENCES↗