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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 505 records · Page 28

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DOE OSTI2023

Community Based Data of Potentiometric Titration of Iron Oxides: Ferrihydrite (HFO), Goethite, Hematite, Magnetite

This data release includes experimental data of potentiometric titration for iron oxides. The data in the provided .csv files is not our own experimental data but have been compiled from the multiple literature sources. The master database is L-SCIE (LLNL Surface Complexation/Ion Exchange) database, and the provided .csv files are extracted data from L-SCIE. The .csv files were obtained by using the Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) code written in the R programming language (free licensing available at https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc).The released data was used for developing a comprehensive community data-driven surface complexation modeling (SCM) framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Deep learning-based data assimilation in the latent space for real-time forecasting of geologic carbon storage.

Abstract not provided.

Yoon, Hongkyu↗

DOE OSTI2014

Online stress corrosion crack and fatigue usages factor monitoring and prognostics in light water reactor components: Probabilistic modeling, system identification and data fusion based big data analytics approach

Nuclear reactors in the United States account for roughly 20% of the nation's total electric energy generation, and maintaining their safety in regards to key component structural integrity is critical not only for long term use of such plants but also for the safety of personnel and the public living around the plant. Early detection of damage signature such as of stress corrosion cracking, thermal-mechanical loading related material degradation in safety-critical components is a necessary requirement for long-term and safe operation of nuclear power plant systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

Path Scan Operational Data-Based Test Report

The TTP program is managed by DHS S&T Cyber Division and facilitates the transition of technology from the research lab to the Homeland Security Enterprise. It serves as a connection point for cyber security researchers, the Federal Government, and the private sector. Technologies targeted are those that are likely to transition successfully to the commercial market and expected to have notable impact on the cyber security of our Nation’s networks or systems. The test element of the TTP program aids in the technology transfer process and is not intended to be adversarial. Additional information on the TTP program and the iterative process used can be found in Appendix A - TTP Program Overview.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Deep learning-based data assimilation in the latent space for real-time forecasting of geologic carbon storage.

Abstract not provided.

Yoon, Hongkyu↗

DOE OSTI2025

Towards AI Based Data Classification for Decision Making During Testing

During the development of high-consequence items, test systems should be capable of differentiating between test failures resulting from narrowly missing requirements versus those indicating potentially catastrophic faults. In many instances, classifying the data corresponds to simply identifying whether measured waveforms have approximately the anticipated shape. Cast in this light, the problem reduces to converting raw data into a form optimal for use with neural network classifiers. This manuscript investigates different means of representing raw data for image classification. Raw data plots and Short Time Fourier Transform (STFT) spectrograms are classified by both custom built, small-scale, Convolution Neural Networks (CNN) and open-source, multi-million parameter, pre-trained deep CNNs. In the case of time varying frequency content, the STFTs provide images with greater detail and can be accurately classified with simpler networks. This requires less memory and runs faster than classifying the raw data using the more sophisticated options—making STFTs optimal for applications with memory constraints. STFTs are not a panacea. In some cases the time-domain signal contains useful information that should not be discarded. Rather than using raw data or STFTs, the images can be constructed from both by using red and green channels of an RGB image to visualize the real and imaginary components of the transform, with the raw data occupying the blue channel.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025