Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “particle identification methods”

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.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Summer 2025 SULI: Nucleus ID, TinyTPC, and Scientific Communication

This paper summarizes my work during the Summer 2025 SULI internship, which focused on two main projects and broader scientific development. The first project involved improving the particle identification (PID) of protons, deuterons, and tritons using PIDA distributions and template fitting, with the goal of modeling nuclear final-state interactions (FSI) and testing the robustness of the method against systematic uncertainties. These techniques pave the way for future application to LArTPC data from the ICARUS detector. The second project centered on the optimization and data-taking of the TinyTPC detector, a compact LArTPC used for high-resolution low-energy measurements. I adjusted gain and threshold parameters, performed hardware validation tests, and developed analysis strategies to extract meaningful physics from collected data. Throughout the summer, I also enhanced my scientific communication and mentorship skills through presentations, collaborative analysis, and peer guidance.

McCright, Hannah [Maryland U.]↗
NASA NTRS1975

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Fordyce, J. S.↗
DOE OSTI2023

Study of nanodiamond photocathodes for MPGD-based detectors of single photons

The proposed new Electron–Ion Collider poses a technical and intellectual challenge for the detector design to accommodate the long-term diverse physics goals envisaged by the program. This requires a 4π detector system capable of reconstructing the energy and momentum of final state particles with high precision. The Electron-Ion Collider also requires identification of particles of different masses over a wide momentum range. A diverse spectrum of Particle IDentification detectors has been proposed. Of the four types of detectors for hadron identification, three are based on Ring Imaging Cherenkov Counter technologies, and one is realized by the Time of Flight method. The quest for a novel photocathode, sensitive in the far vacuum ultraviolet wavelength range and more robust than cesium iodide, motivated an R&D programme to explore nano-diamond (ND) based photocathodes, started by a collaboration between INFN and CNR Bari and INFN Trieste. Systematic measurements of the photoemission in different Ar:CH 4 and Ar:CO 2 gas mixtures with various types of ND powders and Hydrogenated ND (H-ND) powders are reported. A first study of the response of THGEMs coated with different photocathode materials is presented. Additionally, the progress of this R&D programme and the results obtained so far by these exploratory studies are described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Identification of $^{3}$He–$^{3}$H clusters in the $^{6}$Li+$^{89}$Y experiment using particle-$\gamma$ coincidence measurement

The 6 Li+ 89 Y experiment was performed to explore the reaction mechanism induced by a weakly bound nucleus 6 Li and its cluster configuration. Here, the particle-$\gamma$ coincidence method was used to identify the different reaction channels. The $\gamma$-rays coincident with 3 He/ 3 H indicate that the 3 H/ 3 He stripping reaction plays a significant role in the formation of Zr/Nb isotopes. The obtained results support the existence of a 3 He- 3 H cluster in 6 Li. Direct and sequential transfer reactions are adequately discussed, and the FRESCO code is used to perform precise finite-range cyclic redundancy check calculations. In the microscopic calculation, direct cluster transfer is more predominant than sequential transfer in 3 H transfer. However, the direct cluster transfer is of comparable magnitude to the sequential transfer in the 3 He transfer.

CRC calculations↗
NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗
NASA NTRS1973

Identification of comet nucleus from comet coma.

The study of comets is of important scientific value as part of the exploration of the solar system. This paper proposes a method, called 'stationary target identification,' to detect the nucleus within the coma. The method makes use of the fact that the coma is ever expanding about the nucleus. Therefore, when a radar beam is used for detection, the coma particles will produce a return signal that is Doppler shifted. The effects of the spatial extent of the coma and Doppler bandwidth of the coma returns upon the required data processing are considered. Also different methods of implementation are considered.-

Brock, H. I.↗
NASA NTRS1974

X-ray diffraction identification of minerals in lunar regolith returned by Luna 16 automatic station

The methods of powder and monocrystal X-ray diffraction served in identifying the mineral composition of gross samples of regolith from different levels of the drill core and about 80 individual regolith particles returned by the Luna 16 station. It was established that the Sea of Fertility regolith includes pyroxenes of the augite-pigeonite series, anorthites, ilmenite, olivines, spinels, alpha cristobalite, iron particles, glass, and several as yet unidentified particles. Crystallographic and roentgenometric data are given for all the lunar minerals found.

Makarov, Y. S.↗
DOE OSTI2021

Jet tagging in the Lund plane with graph networks

The identification of boosted heavy particles such as top quarks or vector bosons is one of the key problems arising in experimental studies at the Large Hadron Collider. In this article, we introduce LundNet, a novel jet tagging method which relies on graph neural networks and an efficient description of the radiation patterns within a jet to optimally disentangle signatures of boosted objects from background events. We apply this framework to a number of different benchmarks, showing significantly improved performance for top tagging compared to existing state-of-the-art algorithms. We study the robustness of the LundNet taggers to non-perturbative and detector effects, and show how kinematic cuts in the Lund plane can mitigate overfitting of the neural network to model-dependent contributions. Finally, we consider the computational complexity of this method and its scaling as a function of kinematic Lund plane cuts, showing an order of magnitude improvement in speed over previous graph-based taggers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 7

Topics discussed include: Lunar Geologic Mapping: Preliminary Mapping of Copernicus Quad High-Resolution Topography of Layers in the Valles Marineris Via Thermoclinometry ; The Critical Importance of Data Reduction Calibrations in the Interpretability of S-type Asteroid Spectra; (sup 238)U-(sup 206)Pb Age and Uranium-Lead Isotope Systematics of Mare Basalt 10017; Morphological Investigations of Martian Spherules, Comparisons to Collected Terrestrial Counterparts; The Vapor Pressure of Palladium at Temperatures up to 1973K; Areas of Favorable Illumination at the Lunar Poles Calculated from Topography; An Indigenous Origin for the South Pole-Aitken Basin Thorium Anomaly; Ar-Ar Ages of Nakhlites Y000593, NWA998, and Nakhla and CRE Ages of NWA998; Experiments on the Acoustic Properties of Titan-like Atmospheres; Analysis of Downstream Transitions in Morphology and Structure of Lava Channels on Mars; Structure and Bonding of Carbon in Clays from CI Carbonaceous Chondrites; Comparison of Three Hydrogen Distributions at the Equator of Mars; An Impact Origin for the Foliation of Ordinary Chondrites; A New Micrometeorite Collection from Antarctica and Its Preliminary Characterization by Microobservation, Microanalysis and Magnetic Methods; Volcanic Plumes and Plume Deposits on Io; Results of the Alpha-Particle-X-Ray Spectrometer on Board of the Mars Exploration Rovers; Effects of Oceans on Atmospheric Loss During the Stage of Giant Impacts; and Identification of Predominant Ferric Signatures in Association to the Martian Sulfate Deposits

Source record↗
NASA NTRS1976

A thermoluminescent method for aerosol characterization

A thermoluminescent method has been used to study the interactions of aerosols with ozone. The preliminary results show that ozone reacts with many compounds found in aerosols, and that the thermoluminescence curves obtained from ozonated aerosols are characteristic of the aerosol. The results suggest several important applications of the thermoluminescent method: development of a detector for identification of effluent sources; a sensitive experimental tool for study of heterogeneous chemistry; evaluation of importance of aerosols in atmospheric chemistry; and study of formation of toxic, electronically excited species in airborne particles.

Long, E. R., Jr.↗
DOE OSTI2023

Novel method for the identification of the production flavor of neutral charmed mesons

We propose a new algorithm for the identification of the production flavor of neutral D mesons in the Belle II experiment. The algorithm exploits the correlation between the flavor of a reconstructed neutral D meson (signal D meson) and the electric charges of particles reconstructed in the rest of the e + e – →$c\bar{c}$ event. These include those originating from the decay of the other charm hadron produced in the event, as well as those possibly produced in association with the signal D meson. We develop the algorithm using simulation and calibrate it in data using decay modes that identify the flavor of the decaying neutral D meson. We use a data sample of e + e – collisions, corresponding to 362 fb –1 of integrated luminosity, collected by Belle II at center-of-mass energies near the Υ(4S) mass. The effective tagging efficiency in data is (47.91±0.07 (stat) ±0.51 (syst)) %, independent of the neutral-D-meson decay mode. This charm flavor tagger will approximately double the effective sample size of many CP-violation and charm-mixing measurements that so far have exclusively relied on neutral D mesons originating from D* ± decays. While developed for Belle II, the basic principles underlying the charm flavor tagger can be used in other experiments, including those at hadron colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Dual particle imaging using time-of-flight neutron classification

Fast-neutron imaging technology is well-suited for passive nuclear material monitoring, secondary inspection of flagged cargo, and wide-area search for lost neutron sources. However, imaging systems that use pulse shape discrimination for event classification require complex pulse waveform analysis. In this work, we evaluate time-of-flight (TOF) based particle classification as an alternative solution for fast-neutron imaging by classifying all events with a TOF above a maximum threshold as neutrons. We measured a Cf-252 source next to Cs-137 using a 12-bar organic-glass scintillator array. By varying the TOF thresholds for neutron identification, we demonstrate a clear trade-off between event yield and backprojection image fidelity, with stricter thresholds improving precision at the cost of statistics, TOF thresholded data generated an image that predicted the neutron source direction with 20% reduced mean central angle prediction error compared to a traditional pulse shape discrimination (PSD) method with comparable event count. Time-of-flight particle classification shows promise as an alternative to pulse shape discrimination systems for fast neutron imaging systems looking to minimize costs and size of electronics with comparable imaging quality. The sources used demonstrate that the method is effective in classifying measured neutrons in a measurement environment with 150 μCi Cs-137 and 1.6 × 10 6 n/s Cf-252 sources positioned at distances of 66 cm and 81 cm from the detector. Additionally, the method classifies low-energy neutron events that pulse shape discrimination removes, so a combination of both methods would result in a higher overall neutron event efficiency.

Heriot, William [Univ. of Michigan, Ann Arbor, MI ↗
DOE OSTI2022

Fundamental Studies on the Recovery of Rare Earth Elements from Coal and Coal Byproducts (Final Product Report)

The objective of this project was to collect fundamental information that can be used to develop disruptive physical and chemical separation methods that may be used to extract the rare earth elements (REEs) from coal-based feedstocks in a highly efficient, cost-effective, and environmentally benign manner. To meet the stated objective, a set of interrelated fundamental studies have been conducted. The project has been subdivided into three broad areas of tasks as follows, (1) measurement of surface forces in the thin liquid films (TLFs) of water confined between two macroscopic surfaces to establish the optimal conditions for efficiently collecting the ultrafine particles of rare earth minerals (REMs) present in the coal-based feedstocks using the flotation and/or the hydrophobic-hydrophilic separation process(es), (2) identification of the fundamental mechanisms by which REE ions adsorb and desorb on clay minerals present in coal byproducts, and the characterization of the ion-adsorption clays (IACs) present in U.S. coals, and (3) developing methods of extracting the REEs from the REMs and IACs present in US coal byproducts in a cost-effective and sustainable manner.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1983

Extraction of cloud cover parameters from multispectral satellite measurements

An approach to the extraction of cloud cover parameters from multispectral satellite measurements is proposed which combines the best features of the threshold method and of the cluster approach. The approach proposed here utilizes radiative transfer equations, as in the threshold method, along with the identification of clusters in the two-dimensional histogram formed by the visible and 11-micron infrared channels. Information from a third channel, at 3.7 microns, is used to determine the microphysical model of the cloud particles. Examples of applications of the proposed approach are presented.

Arking, A.↗
DOE OSTI2020

Impedance localization and identification

The beam coupling impedance represents one of the sources of potential beam instabilities in particle accelerators. The localization of large coupling impedance sources is therefore very important in order to focus the efforts for mitigation measures when these are needed. In this work we will focus on the common methods adopted to quantify the transverse impedance of a particle accelerator both from the global and the local point of views. This activity can be performed in both bunched and coasting beams following different strategies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Pressure-based process monitoring of direct-ink write material extrusion additive manufacturing

As additive manufacturing (AM) has become a reliable method for creating complex and unique hardware rapidly, the quality assurance of printed parts remains a priority. In situ process monitoring offers an approach for performing quality control while simultaneously minimizing post-production inspection. For extrusion printing processes, direct linkages between extrusion pressure fluctuations and print defects can be established by integrating pressure sensors onto the print head. In this work, the sensitivity of process monitoring is tested using engineered spherical defects. Pressure and force sensors located near an ink reservoir and just before the nozzle are shown to assist in identification of air bubbles, changes in height between the print head and build surface, clogs, and particle aggregates with a detection threshold of 60–70% of the nozzle diameter. Visual evidence of printed bead distortion is quantified using optical image analysis and correlated to pressure measurements. Importantly, this methodology provides an ability to monitor the quality of AM parts produced by extrusion printing methods and can be accomplished using commonly available pressure-sensing equipment.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗