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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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The XRD pipeline software is a program to reduce 2D X-ray diffraction data from area detectors with advanced algorithms on automatic masking and image segmentation, which help characterization of multiple phases recorded in the data and facilitate data analysis.SF-25-114
The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. https://github.com/nrel-pipes/pipes-api https://github.com/nrel-pipes/pipes-web https://github.com/nrel-pipes/nrel-pipes
SF-25-081 Utility software for creating high-performance data pipelines to extract, load, and transform raw electric power systems measurements. For use with anomaly detection models training workflows. The software supports the project: Adaptive Cybersecurity for DER: A Game-Theoretic and Machine Learning approach for Real-Time Threat Detection and Mitigation
The NLR Data Processing Pipeline for MADIS software package is for downloading, processing, and performing QA/QC on MADIS data. Designed to handle the following steps: 1) Download all MADIS data as compressed netcdf files for a given time period. 2) Unpack netcdf files into timeseries csvs for each coordinate within the given bounding box. 3) Process the csvs to filter according to quality control checks and convert variables to correct units. 4) Write processed csvs to a single nc file.
This is FECM/NETL H2 pipeline transportation cost and economic model development and analysis. The paper will report the results of the analysis and potential applications. The models have been released through the link https://netl.doe.gov/node/14168
In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.
We developed an analysis pipeline for transposase-accessible chromatin sequencing (ATAC-Seq) data derived from bulk samples, which brings together publicly available R packages in addition to command-line tools designed for analysis of bulk ATAC-Seq data and can be run on any computer running a Linux-like operating system such as Ubuntu or Apple OSX.
Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.
Device for locating leaks in a vacuum-jacketed liquid-hydrogen transfer line consists of two Mylar discs, a source of nitrogen and helium gas, and a mass spectrometer. The outer jacket of the pipeline does not need to be removed for the locator to be used.
Cooldown time for simple cryogenic pipelines
Cooldown time for cryogenic pipelines, discussing analytical model based on enthalpy, density and velocity of sound in warm gas
A method of implementing a pipelined fast Fourier transform (FFT) is presented that makes full use of the elements that comprise it. For a given bandwidth and spectral resolution, this approach requires 25 percent less memory, and needs only half the logic speed required for the conventional implementation. Since the spectrum is broken into two parts, two analog-to-digital converters, and attendant mixer-filters, are needed. These two input elements need only operate at half the speed of the one they replaced.
The investigation described was aimed at establishing the degree of compatibility between a plain carbon pipeline-type steel and hydrogen and also hydrogen-rich environments containing small additions of H2S, O2, H2O, CO, CO2, CH4, and natural gas at pressures near 1 atm. Test were carried out under conditions of static and cyclic loading; the subcritical crack growth was monitored. The rates of crack growth observed in the hydrogen and hydrogen-rich environments are compared with the crack rate observed in a natural gas environment to determine the compatibility of the present natural gas transmission system with gaseous hydrogen transport.
The possibility of using hydrogen for storing and carrying energy obtained from nonfossil sources such as nuclear and solar energy is examined. According to the method proposed, these nonfossil raw energy sources will be used to obtain hydrogen from water by three basically distinct routes: (1) electrical generation followed by electrolysis; (2) thermochemical decomposition; and (3) direct neutron or ultraviolet irradiation of hydrogen bearing molecules. The hydrogen obtained will be transmitted in long-distance pipelines, and distributed to all energy-consuming sectors. As a fuel gas, hydrogen has many qualities similar to natural gas and with only minor modifications, it can be transmitted and distributed in the same equipment, and can be burned in the same appliances as natural gas. Hydrogen can also be used as a clean fuel (water is the only combustion product) for automobiles, fleet vehicles, and aircraft.
A precise statement of the relationship between sequential computation at one rate, parallel or pipeline computation at a much higher rate, the data movement rate between levels of memory, the fraction of inherently sequential operations or data that must be processed sequentially, the fraction of data to be moved that cannot be overlapped with computation, and the relative computational complexity of the algorithms for the two processes, scalar and vector, was developed. The relationship should be applied to the multirate processes that obtain in the employment of various new or proposed computer architectures for computational aerodynamics. The relationship, an efficiency measure that the single user of the computer system perceives, argues strongly in favor of separating scalar and vector processes, sometimes referred to as loosely coupled processes, to achieve optimum use of hardware.
Optical matrix processors using acoustooptic transducers are described, with emphasis on new systolic array architectures using frequency multiplexing in addition to space and time multiplexing. A Kalman filtering application is considered in a case study from which the operations required on such a system can be defined. This also serves as a new and powerful application for iterative optical processors. The importance of pipelining the data flow and the ordering of the operations performed in a specific application of such a system are also noted. Several examples of how to effectively achieve this are included. A new technique for handling bipolar data on such architectures is also described.
It is pointed out that the two-dimensional cyclic convolution is a useful tool for many two-dimensional digital signal processing applications. Two important applications are related to spaceborne high-resolution synthetic aperture radar (SAR) processing and image processing. Nussbaumer and Quandalle (1978) showed that a radix-2 polynomial transform analogous to the conventional radix-2 FFT algorithm can be used to compute a two-dimensional cyclic convolution. On the basis of results reported by Arambepola and Rayner (1979), a radix-2 polynomial transform can be defined to compute a multidimensional cyclic convolution. Truong et al. (1981) used the considered ideas together with the Chinese Theorem to further reduce the complexity of the radix-2 fast polynomial transform (FPT). Reed et al. (1981) demonstrated that such a new FPT algorithm is significantly faster than the FFT algorithm for computing a two-dimensional convolution. In the present investigation, a parallel-pipeline architecture is considered for implementing the FPT developed by Truong et al.
A pipeline structure of a transform decoder similar to a systolic array was developed to decode Reed-Solomon (RS) codes. An important ingredient of this design is a modified Euclidean algorithm for computing the error locator polynomial. The computation of inverse field elements is completely avoided in this modification of Euclid's algorithm. The new decoder is regular and simple, and naturally suitable for VLSI implementation.