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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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DOE OSTI2021

Improvements of pre-emptive identification of particle accelerator failures using binary classifiers and dimensionality reduction

In this paper we look at the properties of the Spallation Neutron Source (SNS) Differential Beam Current Monitor (DCM) data and various methods of data transformation to improve pre-emptive detection of machine trips. In this study, the foundation of the approach is the analysis of new underlying data and understanding various properties with the goal of faster classification, higher precision and higher recall with the aim to reduce false positives as low as required. The result of the research presented in this paper are a binary classifier capable of predicting accelerator failures with millisecond classification time, 96% precision, 58% true positive and 0% false positive rate and optimization techniques enabling real-time implementations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Identifying Nanoscale Structure–Function Relationships Using Multimodal Atomic Force Microscopy, Dimensionality Reduction, and Regression Techniques

Not provided.

Chemistry↗

DOE OSTI2019

Dimensionality Reduction and Network Inference for Climate Data Using δ -MAPS: Application to the CESM Large Ensemble Sea Surface Temperature

Not Available

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Dimensional reduction of the small-bandgap double perovskite Cs2AgTlBr6

The Ag–Tl perovskites provide the first clear evidence that quantum confinement can significantly alter the optical properties of 2D halide double perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Combining enhanced sampling and deep learning dimensionality reduction for the study of the heat shock protein B8 and its pathological mutant K141E

The study provides the first 3D structural characterization of HSPB8 and its K141E mutant: extensive TREMD are combined with a deep learning algorithm to rationalize the disordered ensemble of structures adopted by each variant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Dimensional reduction in causal set gravity

Not Available

Carlip, S.↗

DOE OSTI2025

Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction

Here, this work introduces an online greedy method for constructing quadratic manifolds from streaming data, designed to enable in situ analysis of numerical simulation data on the Petabyte scale. Unlike traditional batch methods, which require all data to be available upfront and take multiple passes over the data, the proposed online greedy method incrementally updates quadratic manifolds in one pass as data points are received, eliminating the need for expensive disk input/output operations as well as storing and loading data points once they have been processed. A range of numerical examples demonstrate that the online greedy method learns accurate quadratic manifold embeddings while being capable of processing data that far exceed common disk input/output capabilities and volumes as well as main-memory sizes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019