SEARCH · Search NASA
Results for “Identification”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Methods for rapid identification of anomalous layers in laser powder bed fusion
In situ process monitoring is a key requirement for increased industry acceptance of powder bed Additive Manufacturing. As sensing technologies increase in maturity, attention must also be given to effective data exploration techniques. These data are often high-resolution and multi-modal, with each build consisting of thousands of layers. Here, in this paper, the authors propose two methods enabling users to rapidly identify layers of interest within a build. Both methods leverage results from deep learning based segmentations of in situ powder bed images. The first method is an unsupervised “reverse layer search” algorithm while the second method uses supervised machine learning.
Identification of a gene encoding the last step of the L-rhamnose catabolic pathway in Aspergillus niger revealed the inducer of the pathway regulator
Not Available
Identification of the optimal carbon fiber shape for cost-specific compressive performance
We report carbon fiber composites offer superior mechanical performance compared to nearly all other useful materials for the design of structures. However, for cost-driven industries, such as with the wind energy and vehicle industries, the cost of commercial carbon fiber materials is often prohibitive for their usage compared to alternatives. This paper develops an approach to optimize fiber geometries for use in carbon fiber reinforced polymers to increase the compressive strength per unit cost. Compressive strength is a composite property that depends on the fiber, matrix, and interface, and an exact analytic expression does not exist that can accurately represent these complicated relationships. The approach taken instead is to use a weighted summation between the fiber cross-sectional area moment of inertia and perimeter as a proxy for compressive strength, with different weightings explored within the paper. Analyses are performed to identify optimal fiber geometries that increase the cost-specific compressive strength based on various assumptions and desired fiber volume fraction. Robust optimal shapes are identified which outperform circular fibers due to increases in area moment of inertia and perimeter, as well as decreases in carbon fiber processing costs.
Characterization of novel rotating scatter mask designs for gamma direction identification
Not Available
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.
Identification and recovery of ATLAS18 strip sensors with high surface static charge
Not provided.
Identification of positrons and electrons at TeV energy scale using the AMS tracker, time-of-flight counters, and electromagnetic calorimeter
Not Available
Expanded analysis of machine learning models for nuclear transient identification using TPOT
Industries around the world are becoming more and more data driven. The nuclear field is no exception with several different applications being proposed. One popular area of research is the use of machine learning in transient detection. This paper seeks to build upon a previous study which made use of the AutoML package TPOT to train traditional machine learning models to classify transient events occurring with a reactor. Synthetic data was once again collected using a GPWR reactor simulator. Data on 12 different events was collected using 15 different initial conditions. Here, a dataset consisting of over 100,000 data points was compiled and used to train 7 different machine learning models using a pre-defined TPOT dictionary with 12 different preprocessing techniques. Three of the trained models were able to produce validation results in the 90s with the expanded dataset. Once the models were trained, it was possible to look into where during the simulation, misclassifications occurred. Using these three models, analysis was done to determine if TPOT could be used to train models that were effective if important features were missing. The results from this were positive with the newly trained models scoring close to the original models. Finally, to conclude this study, the three high performing models were retrained using different random states to see if there was any major variation when different states were used.
A new approach to predict pump transient phenomena in Molten salt reactor Experiment (MSRE) by missing data identification and regeneration
Not provided.
Machine learning accelerates identification of lithiated phases in X-ray images of battery hosts
Explore the source record for details and available documents.
Identification of azadirachtin responsive genes in Spodoptera frugiperda larvae based on RNA-seq
Not Available
Identification of the molecular-weight growth reaction network in counterflow flames of the C 3 H 4 isomers allene and propyne
The reaction networks responsible for aromatics formation in counterflow flames of the C 3 H 4 isomers allene and propyne are identified through a combined experimental and modeling study. Mole fraction profiles of near-atmospheric pressure (933 mbar) diffusion flames fueled by the C 3 H 4 isomers are analyzed by means of a newly assembled, chemically detailed kinetic mechanism. The experiment consists of a counterflow burner system that is coupled to a high-resolution time-of-flight molecular-beam mass spectrometer with single-photon ionization via synchrotron-generated vacuum-ultraviolet photons. Flame-sampled, mass-specific photoionization efficiency curves are used to identify the presence of aliphatically substituted aromatic species in addition to the commonly considered pericondensed ring structures. The new mechanism describes the formation and growth of aromatics through repetitive sequences of radical–radical and radical–molecule reactions that include C 1 6 intermediates. Higher concentrations of aromatic species are observed in the allene flame and the new mechanism captures the observed experimental trends very accurately. The results indicate the importance of the aliphatically substituted aromatics and of ring-enlargement reactions for the growth reactions. According to the model simulations, radical+radical recombination and PAH-radical+molecule reactions play an important role in PAH growth.
Gamma and pulsed electron radiolysis studies of CyMe 4 BTBP and CyMe 4 BTPhen: Identification of radiolysis products and effects on the hydrometallurgical separation of trivalent actinides and lanthanides
The radiolytic stability of the highly selective ligands CyMe 4 BTBP and CyMe 4 BTPhen against ionizing gamma radiation was studied in 1-octanol solution. CyMe 4 BTBP and CyMe 4 BTPhen are important extractants for a potential treatment of used nuclear fuel. They were studied under identical experimental conditions to directly compare the effects of gamma and pulsed electron radiolysis on the ligands and systematically study the influence of structural changes in the ligand backbone. Distribution ratios of Am 3+ , Cm 3+ and Eu 3+ , the residual concentration of CyMe 4 BTBP and CyMe 4 BTPhen in solution, and the formation of radiolysis products were studied as a function of absorbed gamma dose and presence of an acidic aqueous phase during irradiation. Quantitative and semi-quantitative analyses were used to elucidate the radiolysis mechanism for both ligands. Addition products of alpha-hydroxyoctyl radicals formed through radiolysis of the 1-octanol diluent to the ligand molecules were identified as the predominant radiolysis products. These addition products also extract trivalent metal ions, as distribution ratios remained high although the parent molecule concentrations decreased. Therefore, the utilization time of a solvent using these extractants under the harsh conditions of used nuclear fuel treatment could be considerably longer than expected. Understanding the radiolysis mechanism is crucial for designing more radiation resistant extractants.
Identification of opportunities for integrating chemical processes for carbon (dioxide) utilization to nuclear power plants
The energy and industrial sectors are responsible for more than 75% of global carbon dioxide emissions, which are primary contributors to climate change. Decarbonization strategies to reduce overall carbon dioxide emissions are urgently needed. Among the numerous decarbonization strategies that are being defined and implemented, a particular strategy of interest for the present work is “the Re-X or zero waste” strategy, which involves recycling, reuse, repurposing, and remanufacturing of industrial emissions, by-products, and waste in general. A circular value chain or Circular Economy is embedded within this strategy. In a circular carbon economy, efficient reuse of emitted carbon dioxide is considered. However, the stability of carbon dioxide implies the requirement of significant amounts of energy for its transformation into value-added chemicals or products, which must be supplied by low carbon emitting energy sources. Nuclear power plants are low carbon energy sources that, additionally to electricity, could also supply heat and radiation for chemical transformations. This work identifies the opportunities and challenges for the development of integrated energy systems to upgrade and transform carbon dioxide, involving chemical and nuclear energy. The analysis encompasses possible use of the different forms of energy that can be obtain from nuclear reactors (i.e., radiation, electricity, and heat), by reviewing the published literature on potential routes for its conversion. Overall, our review indicates that an universal technology of the one-fits-all solution-type is an utopic dream. Instead, a suite of (contaminants tolerant) technologies for processing various concentrations CO 2 and producing a variety of products is currently needed.
Distribution and source identification of polycyclic aromatic hydrocarbons (PAHs) with PCA-MLR and PMF methods in the topsoil of Chengdu at SW, China
Not provided.