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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Computed Tomography Scanning and Petrophysical Measurements of Eastern Williston Basin Twin Buttes and Hagel Formations

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize core from two wells that represent coal resources across North Dakota. These include the MC23080C Well in Mercer County and the 23-B001 Well in Oliver County. The primary impetus of this work was to capture a detailed digital representation of the core from the MC23080C and 23-B001 Wells. The collaboration between the NETL and the Energy and Environment Research Center (EERC) enables other research entities to access information about this potential carbon ore, rare earth, and critical mineral resource plays in the Williston Basin. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. Fractures, discontinuities, and millimeter-scale features were readily detectable with the medical CT scanner acquired images. Imaging with the NETL medical CT scanner was performed on entire cores. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), gamma density, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for potential future analysis. Higher-resolution industrial and micro-CT images were acquired from selected zones along the depth of the core to visualize the structure in higher detail. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core, with the resulting macro- and micro-descriptions relevant to many subsurface energy-related examinations traditionally performed at NETL.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Digital Elevation Model, 0.25 m, Barrow Environmental Observatory, Utqiagvik (Barrow), Alaska, 2013

This 0.25m horizontal resolution digital elevation model (DEM) was developed from Airborne Laser Altimetry flown by Aerometric Inc, now known as Quantum Spatial, Inc. on July 12, 2013. One Mission was flown and the data jointly processed with LANL personnel to produce a 0.25m DEM covering a region approximately 2.8km wide and 12.4km long extending from the coast above North Salt Lagoon to south of Gas Well Road. This DEM encompasses a diverse range of hydrologic, geomorphic, geophysical and biological features typical of the Barrow Peninsula. Vertical accuracy at the 95% confidence interval was computed as 0.143m. The coordinate system, datum, and geoid for this DEM are UTM Zone 4N, NAD83 (2011), NAVD88 (GEOID09). This dataset includes a variety of file types.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Retrospective evaluation of exposure index (EI) values from plain radiographs reveals important considerations for quality improvement

Following X-ray exposure, radiographers receive immediate feedback on detector exposure in the form of the exposure index (EI). To identify whether radiographers are meeting manufacturer-recommended EI (MREI) ranges for routine chest, abdomen and pelvis X-ray examinations under a variety of conditions and to examine factors affecting the EI. Data on 5000 adult X-ray examinations including the following variables were collected: examination parameters, EI values, patient gender, date of birth, date and time of examination, grid usage and the presence of implant or prosthesis. Descriptive statistics were used to summarize each data set and the Mann–Whitney U test was used to determine significant differences, with P < 0.05 indicating significance for all tests. Most examinations demonstrated EI values that were outside the MREI ranges, with significantly higher median EI values recorded for female patient radiographs than those for male patients for all manufacturers, indicating higher detector exposures for all units except for Philips digital radiography (DR), where increased EI values indicate lower exposure (P = 0.01). Median EI values for out of hours radiography were also significantly higher compared with normal working hours for all technologies (P ≤ 0.02). Significantly higher median EI values were demonstrated for Philips DR chest X-rays without as compared to those with the employment of a grid (P = 0.03), while significantly lower median EI values were recorded for Carestream Health computed radiography (CR) chest X-rays when an implant or prosthesis was present (P = 0.02). Non-adherence to MREIs has been demonstrated with EI value discrepancies being dependent on patient gender, time/day of exposure, grid usage and the presence of an implant or prosthesis. Retrospective evaluation of EI databases is a valuable tool to assess the need of quality improvement in routine DR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Volumetric additive manufacturing of silica glass with microscale computed axial lithography

Glass is increasingly desired as a material for manufacturing complex microscopic geometries, from the micro-optics in compact consumer products to microfluidic systems for chemical synthesis and biological analyses. As the size, geometric, surface roughness, and mechanical strength requirements of glass evolve, conventional processing methods are challenged. We introduce microscale computed axial lithography (micro-CAL) of fused silica components, by tomographically illuminating a photopolymer-silica nanocomposite that is then sintered. We fabricated three-dimensional microfluidics with internal diameters of 150 micrometers, free-form micro-optical elements with a surface roughness of 6 nanometers, and complex high-strength trusses and lattice structures with minimum feature sizes of 50 micrometers. As a high-speed, layer-free digital light manufacturing process, micro-CAL can process nanocomposites with high solids content and high geometric freedom, enabling new device structures and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Exploratory study on potential safeguards applications for shared ledger technology

The International Atomic Energy Agency (IAEA) is responsible for providing credible assurance that countries are meeting their obligations not to divert or misuse nuclear materials and facilities for non-peaceful purposes. To this end, the IAEA integrates information about States’ nuclear material inventories and transactions with other types of data to draw its safeguards conclusions. As the amount and variety of data and information has increased, the IAEA’s data acquisition, management, and analysis processes have greatly benefited from advancements in computer science, data management, and cybersecurity during the last 20 years. Despite these advancements, inconsistent use of advanced computer technologies as well as political concerns among certain IAEA Member States centered on trust, transparency, and IAEA authorities limit the overall effectiveness and efficiency of IAEA safeguards. As a result, there is an ongoing need to strengthen the effectiveness and efficiency of IAEA safeguards while improving Member State cooperation and trust in the safeguards system. These chronic safeguards needs could be met with some emerging technologies, specifically those associated with the digital currency bitcoin.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗
DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗
DOE OSTI2014

Measurement of the rate of stellar tidal disruption flares

We report an observational estimate of the rate of stellar tidal disruption flares (TDFs) in inactive galaxies based on a successful search for these events among transients in galaxies using archival Sloan Digital Sky Survey (SDSS) multi-epoch imaging data (Stripe 82). This search yielded 186 nuclear flares in galaxies, 2 of which are excellent TDF candidates. Because of the systematic nature of the search, the very large number of galaxies, the long time of observation, and the fact that non-TDFs were excluded without resorting to assumptions about TDF characteristics, this study provides an unparalleled opportunity to measure the TDF rate. To compute the rate of optical stellar tidal disruption events, we simulate our entire pipeline to obtain the efficiency of detection. The rate depends on the light curves of TDFs, which are presently still poorly constrained. Using only the observed part of the SDSS light curves gives a model-independent upper limit to the optical TDF rate, N-dot <2×10{sup −4} yr{sup −1} galaxy{sup −1} (90% CL), under the assumption that the SDSS TDFs are representative examples. We develop three empirical models of the light curves based on the two SDSS light curves and two more recent and better-sampled Pan-STARRS TDF light curves, leading to our best estimate of the rate: N-dot {sub TDF}=(1.5--2.0){sub −1.3}{sup +2.7}×10{sup −5} yr{sup −1} galaxy{sup −1}. We explore the modeling uncertainties by considering two theoretically motivated light curve models, as well as two different relationships between black hole mass and galaxy luminosity, and two different treatments of the cutoff in the visibility of TDFs at large M {sub BH}. From this we conclude that these sources of uncertainty are not significantly larger than the statistical ones. Our results are applicable for galaxies hosting black holes with mass in the range of a few 10{sup 6}-10{sup 8} M {sub ☉}, and translates to a volumetric TDF rate of (4-8) × 10{sup –8±0.4} yr{sup –1} Mpc{sup –3}, with the statistical uncertainty in the exponent.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown (LS2) in 2018, and a new LAr Trigger Digitizer Board (LTDB) will be designed and installed. Several commercial-off-the-shelf (COTS) multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. Here, to evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition (DAQ) board, signal generator, external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clock distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC (FPGA Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital (MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

LOWER BOUNDS ON MAGNETIC FIELDS IN INTERGALACTIC VOIDS FROM LONG-TERM GeV-TeV LIGHT CURVES OF THE BLAZAR MRK 421

Lower bounds are derived on the amplitude B of intergalactic magnetic fields (IGMFs) in the region between Galaxy and the blazar Mrk 421, from constraints on the delayed GeV pair-echo flux that are emitted by secondary e {sup -} e {sup +} produced in {gamma}{gamma} interactions between primary TeV gamma rays and the cosmic infrared background. The distribution of galaxies mapped by the Sloan Digital Sky Survey shows that this region is dominated by a large intergalactic void. We utilize data from long-term, simultaneous GeV-TeV observations by the Fermi Large Area Telescope and the ARGO-YBJ experiment extending over 850 days. For an assumed value of B, we evaluate the daily GeV pair-echo flux expected from the TeV data, select the dates where this exceeds the Fermi 2{sigma} sensitivity, compute the probability that this flux is excluded by the Fermi data for each date, and then combine the probabilities using the inverse normal method. Consequently, we exclude B < 10{sup -20.5} G for a field coherence length of 1 kpc at {approx}4{sigma} level, as long as plasma instabilities are unimportant for cooling of the pair beam. This is much more significant than the 2{sigma} bounds we obtained previously from observations of Mrk 501, by virtue of more extensive data from the ARGO-YBJ, as well as improved statistical analysis. Compared with most other studies of IGMF bounds, the evidence we present here for a non-zero IGMF is more robust as it does not rely on unproven assumptions on the primary TeV emission during unobserved periods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-E-CAMPUS-T-02: Can Pre-Treatment 4DCT-Based Motion Margins Estimates Be Trusted for Proton Radiotherapy?

Purpose: Radiotherapy motion margins are generated using pre-treatment 4DCT data. The purpose of this study is to assess if pre-treatment 4DCT is sufficient in proton therapy to provide accurate estimate of motion margins. A dosimetric assessment is performed comparing pre-treatment margins with daily-customized margins. Methods: Gold fiducial markers implanted in lung tumors of patients were used to track the tumor. A spherical tumor of diameter 20 mm is inserted into a realistic digital respiratory phantom, where the tumor motion is based on real patient lung tumor trajectories recorded over multiple days. Using “Day 1” patient data, 100 ITVs were generated with 1 s interval between consecutive scan start times. Each ITV was made up by the union of 10 tumor positions obtained from 6 s scan time. Two ITV volumes were chosen for treatment planning: ITVmean-σ and ITVmean+σ. The delivered dose was computed on i) 10 phases forming the planning ITV (“10-phase” - simulating dose calculation based on 4DCT) and ii) 50 phantoms produced from 100 s of data from any other day with tumor positions sampled every 2 s (“dynamic” - simulating the dose that would actually be delivered). Results: For similar breathing patterns between “Day 1” and any other “Day N(>1)”, the 95% volume coverage (D95) for “dynamic” case was 8.13% lower than the “10-phase” case for ITVmean+σ. For breathing patterns that were very different between “Day 1” and any other “Day N(>1)”, this difference was as high as 24.5% for ITVmean-σ. Conclusion: Proton treatment planning based on pre-treatment 4DCT can lead to under-dosage of the tumor and over-dosage of the surrounding tissues, because of inadequate estimate of the range of motion of the tumor. This is due to the shift of the Bragg peak compared to photon therapy in which the tumor is surrounded by an electron bath.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-22: A Feasibility Study On KV-Based Whole Breast Radiation Patient Setup

Purpose: In room kilovoltage x-ray (kV) imaging provides higher contrast than Megavoltage (MV) imaging with faster acquisition time compared with on-board cone-beam computed tomography (CBCT), thus improving patient setup accuracy and efficiency. In this study we evaluated the clinical feasibility of utilizing kV imaging for whole breast radiation patient setup. Methods: For six breast cancer patients with whole breast treatment plans using two opposed tangential fields, MV-based patient setup was conducted by aligning patient markers with in room lasers and MV portal images. Beam-eye viewed kV images were acquired using Varian OBI system after the set up process. In house software was developed to transfer MLC blocks information overlaying onto kV images to demonstrate the field shape for verification. KV-based patient digital shift was derived by performing rigid registration between kV image and the digitally reconstructed radiography (DRR) to align the bony structure. This digital shift between kV-based and MV-based setup was defined as setup deviation. Results: Six sets of kV images were acquired for breast patients. The mean setup deviation was 2.3mm, 2.2mm and 1.8mm for anterior-posterior, superior-inferior and left-right direction respectively. The average setup deviation magnitude was 4.3±1.7mm for six patients. Patient with large breast had a larger setup deviation (4.4–6.2mm). There was no strong correlation between MV-based shift and setup deviation. Conclusion: A preliminary clinical workflow for kV-based whole breast radiation setup was established and tested. We observed setup deviation of the magnitude below than 5mm. With the benefit of providing higher contrast and MLC block overlaid on the images for treatment field verification, it is feasible to use kV imaging for breast patient setup.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

In situ Parallel Training of Analog Neural Network Using Electrochemical Random-Access Memory

In-memory computing based on non-volatile resistive memory can significantly improve the energy efficiency of artificial neural networks. However, accurate in situ training has been challenging due to the nonlinear and stochastic switching of the resistive memory elements. One promising analog memory is the electrochemical random-access memory (ECRAM), also known as the redox transistor. Its low write currents and linear switching properties across hundreds of analog states enable accurate and massively parallel updates of a full crossbar array, which yield rapid and energy-efficient training. While simulations predict that ECRAM based neural networks achieve high training accuracy at significantly higher energy efficiency than digital implementations, these predictions have not been experimentally achieved. In this work, we train a 3 × 3 array of ECRAM devices that learns to discriminate several elementary logic gates (AND, OR, NAND). We record the evolution of the network’s synaptic weights during parallel in situ (on-line) training, with outer product updates. Due to linear and reproducible device switching characteristics, our crossbar simulations not only accurately simulate the epochs to convergence, but also quantitatively capture the evolution of weights in individual devices. The implementation of the first in situ parallel training together with strong agreement with simulation results provides a significant advance toward developing ECRAM into larger crossbar arrays for artificial neural network accelerators, which could enable orders of magnitude improvements in energy efficiency of deep neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Digital Elevation Model, 0.5 m, Barrow Environmental Observatory, Utqiagvik (Barrow), Alaska, 2012

This 0.5m horizontal resolution digital elevation model (DEM) was developed from Airborne Laser Altimetry flown by Aerometric Inc, now know as Quantum Spatial, Inc. on August 12, 2012. One Mission was flown and the data jointly processed with Los Alamos National Laboratory (LANL) personnel to produce a 0.5m DEM covering a region approximately 2.8km wide and 12.5km long extending from the coast above North Salt Lagoon to south of Gas Well Road. This DEM encompasses a diverse range of hyrdrologic, geomorphic, geophysical and biological features typical of the Barrow Peninsula. Vertical accuracy at the 95% confidence interval was computed as 0.145m. The coordinate system, datum, and geoid for this DEM are UTM Zone 4N, NAD83 (2011), NAVD88 (GEOID09). This dataset includes one .tif file and one .pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optical authentication of images

Systems and methods performed for generating authentication information for an image using optical computing are provided. When a user takes a photo of an object, an optical authentication system receives light reflected and/or emitted from the object. The system also receives a random key from an authentication server. The system converts the received light to plenoptic data and uploads it to the authentication server. In addition, the system generates an optical hash of the received light using the random key, converts the generated optical hash to a digital optical hash, and uploads the digital optical hash to the authentication server. When the authentication server receives the upload, it verifies whether the time of the upload is within a certain threshold time from the sending of the random key and whether the digital optical hash was generated from the same light as the plenoptic data.

Murialdo, Maxwell R.↗
DOE OSTI2015

Effect of CT contrast on volumetric arc therapy planning (RapidArc and helical tomotherapy) for head and neck cancer

The objectives of the study were to evaluate the effect of intravenous contrast in the dosimetry of helical tomotherapy and RapidArc treatment for head and neck cancer and determine if it is acceptable during the computed tomography (CT) simulation to acquire only CT with contrast for treatment planning of head and neck cancer. Overall, 5 patients with head and neck cancer (4 men and 1 woman) treated on helical tomotherapy were analyzed retrospectively. For each patient, 2 consecutive CT scans were performed. The first CT set was scanned before the contrast injection and secondary study set was scanned 45 seconds after contrast. The 2 CTs were autoregistered using the same Digital Imaging and Communications in Medicine coordinates. Tomotherapy and RapidArc plans were generated on 1 CT data set and subsequently copied to the second CT set. Dose calculation was performed, and dose difference was analyzed to evaluate the influence of intravenous contrast media. The dose matrix used for comparison included mean, minimum and maximum doses of planning target volume (PTV), PTV dose coverage, and V{sub 45} {sub Gy}, V{sub 30} {sub Gy}, and V{sub 20} {sub Gy} organ doses. Treatment planning on contrasted images generally showed a lower dose to both organs and target than plans on noncontrasted images. The doses for the points of interest placed in the organs and target rarely changed more than 2% in any patient. In conclusion, treatment planning using a contrasted image had insignificant effect on the dose to the organs and targets. In our opinion, only CT with contrast needs to be acquired during the CT simulation for head and neck cancer. Dose calculations performed on contrasted images can potentially underestimate the delivery dose slightly. However, the errors of planning on a contrasted image should not affect the result in clinically significant way.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗