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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deriving the Infrared Complex Refractive Indices of Organic Powders for Optical Modeling: Comparison of Methods

Identification of solids via infrared reflection spectroscopy requires a spectral library of all solids likely to be encountered. A confounding factor in populating such a spectral library is that the reflectance spectra of solids vary with their form, including particle size, film thickness, and substrate. To reduce the efforts of experimentally constructing such a library, an alternate strategy is to use the wavelength-dependent optical constants, n and k, of a solid to calculate a series of reflectance spectra corresponding to each scenario or morphology. Because most n/k measurements are best performed on mm-sized crystals, however, the challenge of determining the optical constants increases when a solid is only readily available as a powder, as is often the case. Some organic solids, such as caffeine, are both unavailable in large crystals and difficult to press into pellets. In this study, the infrared optical constants, or complex refractive indices, of caffeine were determined using three different methods: single-angle reflectance, infrared spectroscopic ellipsometry, and quantitative absorbance measurements of KBr pellets. The n and k values derived through each method were used to model the hyperspectral imaging reflectance spectrum of a caffeine film on a steel planchet. Over 1,110 – 870 cm-1, the single-angle reflectance-derived n and k had the best correlation with the experimental spectrum. These results suggest different organic solids may require different methods to determine the most accurate infrared complex refractive indices for synthetic spectral libraries.

FTIR, hyperspectral imaging, infrared, infrared (I↗
DOE OSTI2020

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

A functional form for liquid scintillator pulse shapes

Digitization of detector signals enables analysis of the original waveform to extract timing, particle identification, and energy deposition information. Here we present the use of analytical functions based on sigmoids to model and fit such pulse shapes from liquid organic scintillators, though the method should also be applicable to other detector systems. Neutron and gamma interactions in NE213 detectors were digitized from the phototube anode and fit using a sigmoid-based function. The acuity of the fit in extracting timing information and performing neutron-gamma pulse-shape discrimination are presented and discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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.]↗
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↗
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↗
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↗
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↗
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↗
DOE OSTI2023

Review of multi-faceted morphologic signatures of actinide process materials for nuclear forensic science

Particle morphology is an emerging signature that has the potential to identify the processing history of unknown nuclear materials. Using readily available scanning electron microscopes (SEM), the morphology of nearly any solid material can be measured within hours. Coupled with robust image analysis and classification methods, the morphological features can be quantified and support identification of the processing history of unknown nuclear materials. The viability of this signature depends on developing databases of morphological features, coupled with a rapid data analysis and accurate classification process. With developed reference methods, datasets, and throughputs, morphological analysis can be applied within days to (i) interdicted bulk nuclear materials (gram to kilogram quantities), and (ii) trace amounts of nuclear materials detected on swipes or environmental samples. In conclusion, this review aims to develop validated and verified analytical strategies for morphological analysis relevant to nuclear forensics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modelling a Heaving Point-Absorber with a Closed-Loop Control System Using the DualSPHysics Code

The present work addresses the need for an efficient, versatile, accurate and open-source numerical tool to be used during the design stage of wave energy converters (WECs). The device considered here is the heaving point-absorber developed and tested by Sandia National Laboratories. The smoothed particle hydrodynamics (SPH) method, as implemented in DualSPHysics, is proposed since its meshless approach presents some important advantages when simulating floating devices. The dynamics of the power take-off system are also modelled by coupling DualSPHysics with the multi-physics library Project Chrono. A satisfactory matching between experimental and numerical results is obtained for: (i) the heave response of the device when forced via its actuator; (ii) the vertical forces acting on the fixed device under regular waves and; (iii) the heave response of the WEC under the action of both regular waves and the actuator force. This proves the ability of the numerical approach proposed to simulate accurately the fluid–structure interaction along with the WEC’s closed-loop control system. In addition, radiation models built from the experimental and WAMIT results are compared with DualSPHysics by plotting the intrinsic impedance in the frequency domain, showing that the SPH method can be also employed for system identification.

42 ENGINEERING↗