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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

MODELING STATISTICAL PROPERTIES OF SOLAR ACTIVE REGIONS THROUGH DIRECT NUMERICAL SIMULATIONS OF 3D-MHD TURBULENCE

Statistical properties of the Sun's photospheric turbulent magnetic field, especially those of the active regions (ARs), have been studied using the line-of-sight data from magnetograms taken by the Solar and Heliospheric Observatory and several other instruments. This includes structure functions and their exponents, flatness curves, and correlation functions. In these works, the dependence of structure function exponents ({zeta}{sub p}) of the order of the structure functions (p) was modeled using a non-intermittent K41 model. It is now well known that the ARs are highly turbulent and are associated with strong intermittent events. In this paper, we compare some of the observations from Abramenko et al. with the log-Poisson model used for modeling intermittent MHD turbulent flows. Next, we analyze the structure function data obtained from the direct numerical simulations (DNS) of homogeneous, incompressible 3D-MHD turbulence in three cases: sustained by forcing, freely decaying, and a flow initially driven and later allowed to decay (case 3). The respective DNS replicate the properties seen in the plots of {zeta}{sub p} against p of ARs. We also reproduce the trends and changes observed in intermittency in flatness and correlation functions of ARs. It is suggested from this analysis that an AR in the onset phase of a flare can be treated as a forced 3D-MHD turbulent system in its simplest form and that the flaring stage is representative of decaying 3D-MHD turbulence. It is also inferred that significant changes in intermittency from the initial onset phase of a flare to its final peak flaring phase are related to the time taken by the system to reach the initial onset phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Combining Phase Identification and Statistic Modeling for Automated Parallel Benchmark Generation

Parallel application benchmarks are indispensable for evaluating/optimizing HPC software and hardware. However, it is very challenging and costly to obtain high-fidelity benchmarks reflecting the scale and complexity of state-of-the-art parallel applications. Hand-extracted synthetic benchmarks are time-and labor-intensive to create. Real applications themselves, while offering most accurate performance evaluation, are expensive to compile, port, reconfigure, and often plainly inaccessible due to security or ownership concerns. This work contributes APPRIME, a novel tool for trace-based automatic parallel benchmark generation. Taking as input standard communication-I/O traces of an application's execution, it couples accurate automatic phase identification with statistical regeneration of event parameters to create compact, portable, and to some degree reconfigurable parallel application benchmarks. Experiments with four NAS Parallel Benchmarks (NPB) and three real scientific simulation codes confirm the fidelity of APPRIME benchmarks. They retain the original applications' performance characteristics, in particular the relative performance across platforms.

Jin, Ye↗
DOE OSTI2024

Scenario Planning Management Actions to Restore Cold Water Stream Habitat: Comparing Mechanistic and Statistical Modeling Approaches

ABSTRACT Under the United States Clean Water Act, states are required to periodically assess state waters to determine compliance with water quality criteria (including temperature) and then to develop total maximum daily loads (TMDLs) for impaired waters as necessary to bring them into compliance. We compared the performance of mechanistic stream temperature models (HeatSource, QUAL2K, and QUAL2Kw) applied to the mainstem of three TMDL watersheds (Middle Fork John Day, OR; Wind River, WA; South Fork Nooksack, WA) with that of spatial stream network (SSN) models applied to the full watersheds and used these to evaluate the potential effectiveness of restoration strategies. SSN models performed well with slightly lesser accuracy (RMSE = 0.47–0.87) for mainstem predictions than mechanistic models (RMSE = 0.4) but provided additional benefits to inform management, including information on spatial and temporal heterogeneity of restoration effectiveness throughout the watershed. Of the four scenarios considered (restoration of riparian zones to potential natural vegetation, channel narrowing, increasing flow by restricting irrigation withdrawals, and combined applications), riparian zone restoration was consistently the most effective in reducing temperatures at the outlet, mainstem, and throughout the watersheds. Predicted restoration effectiveness for thermal regimes varied significantly both within and among watersheds. A focus on water quality criteria exceedance only at the watershed outlet or along the mainstem reach can obscure knowledge of restoration potential for fish habitat in tributaries and headwaters, potential for creation of thermal refuge areas along the mainstem critical for maintaining migration corridors, and thermal regime heterogeneity across space and time.

Fuller, M. R.↗
DOE OSTI2014

Statistical modelling of discharge behavior of atmospheric pressure dielectric barrier discharge

In this work, stochastic behavior of atmospheric pressure dielectric barrier discharge (DBD) has been investigated. The experiment is performed in a DBD reactor consisting of a pair of stainless steel parallel plate electrodes powered by a 50 Hz ac high voltage source. Current pulse amplitude distributions for different space gaps and the time separation between consecutive current pulses are studied. A probability distribution function is proposed to predict the experimental distribution function for the current pulse amplitudes and the occurrence of the transition regime of the pulse distribution. Breakdown voltage at different positions on the dielectric surface is suggested to be stochastic in nature. The simulated results based on the proposed distribution function agreed well with the experimental results and able to predict the regime of transition voltage. This model would be useful for the understanding of stochastic behaviors of DBD and the design of DBD device for effective operation and applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Short-term wind forecasting using statistical models with a fully observable wind flow

The utility of model output data from the Weather Research and Forecasting mesoscale model is explored for very short-term forecasting (5-30 minutes horizon) of wind speed to be used in large scale simulations of an autonomous electric power grid. Using this synthetic data for the development and evaluation of short-term forecasting algorithms offer many unique advantages over observational data, such as the ability to observe the full wind flow field in the surrounding region. Several short-term forecasting algorithms are implemented and evaluated using the synthetic data at several different time horizons and for three different geographic locations. Comparison is made with observational data from one location. We find that short-term forecasts of the synthetic data considering wind flow from the surrounding region perform 26% better than persistence in terms of root mean square error at the 5-minute time horizon. This improvement is comparable to studies of observational data in the literature. These results provide motivation to use synthetic data for short term forecasting in grid simulations, and open the door to future algorithmic improvements.

17 WIND ENERGY↗
DOE OSTI2019

Development of a statistical model (tool) for classifying buried object detectability

To improve warfighter safety under changing requirements, assets must be adaptable and able to detect and mark buried hazards. Current GPR systems would benefit by improvements in speed, usability, and operational versatility to enhance operational effectiveness for all platforms and missions. Our sponsor requests that LLNL research GPR methodologies and approaches to allow for specific improvements to be made in those areas. MiRadar uses a novel multi-static array architecture coupled with tomographic processing to focus returned energy from the real (physical) and synthetic (motion-derived) apertures. 3D streaming movies of the subsurface are easily interpreted, slashing training times. Real-time processing codes enable imaging and operation three times faster; automated volumetric detection algorithms warn of possible hazards. In a two-week trial, multiple vehicle-mounted arrays and a new ultralightweight architecture on a small, unmanned aircraft system executed 498 runs, collecting over 400km of data on 13 preemplaced lanes containing 384 simulated buried threats.

42 ENGINEERING↗
DOE OSTI2019

Detailed Statistical Models of Host-Based Data for Detection of Malicious Activity

The cybersecurity research community has focused primarily on the analysis and automation of intrusion detection systems by examining network traffic behaviors. Expanding on this expertise, advanced cyber defense analysis is turning to host-based data to use in research and development to produce the next generation network defense tools. The ability to perform deep packet inspection of network traffic is increasingly harder with most boundary network traffic moving to HTTPS. Additionally, network data alone does not provide a full picture of end-to-end activity. These are some of the reasons that necessitate looking at other data sources such as host data. We outline our investigation into the processing, formatting, and storing of the data along with the preliminary results from our exploratory data analysis. In writing this report, it is our goal to aid in guiding future research by providing foundational understanding for an area of cybersecurity that is rich with a variety of complex, categorical, and sparse data, with a strong human influence component. Including suggestions for guiding potential directions for future research.

97 MATHEMATICS AND COMPUTING↗