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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

NRAP-Open-IAM: Open Wellbore Component (V.2.0)

The Open Wellbore component of NRAP-Open-IAM is applicable to the calculation of Area of Review at a carbon storage site and fast estimation of dense gas dispersion from multiple continuous CO 2 surface leakage sources for risk assessment. The Open Wellbore Component of NRAP-Open-IAM is a lookup table model based on the drift-flux approach. The National Research Assessment Partnership’s second-generation integrated assessment model, NRAP-Open-IAM, is open-source software written in Python for use in performance and quantitative risk assessment of geologic carbon storage (GCS) systems. The look-up table for open well leakage is an updated version the previous model which provides finer resolution of reservoir depth and more accurate fluid properties than the previous open well look-up table, especially in calculating the gas (CO 2 -rich) phase properties. The component model input parameters include the reservoir transmissivity, aquifer transmissivity, brine salinity, well radius, and well top and bottom depths. The reservoir transmissivity and brine salinity were set to values consistent with the reservoir component, and the well top and bottom depths varied with location. The possible outputs from the Open Wellbore component are leakage rates of CO 2 and brine to either an aquifer or atmosphere, depending on the depth of the well top. Several python test scripts are presented that demonstrate that the Open Wellbore component works correctly. Use of the open wellbore model in NRAP-Open-IAM may result in a large CO 2 leakage rates, comparable to the leakage rates of CO 2 blow out.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Development of a time-variable nuclear pulser for half life measurements

In this work a time-variable pulser system with an exponentially-decaying pulse frequency is presented, which was developed using the low-cost, open-source Arduino microcontroler plataform. In this system, the microcontroller produces a TTL signal in the selected rate and a pulse shaper board adjusts it to be entered in an amplifier as a conventional pulser signal; both the decay constant and the initial pulse rate can be adjusted using a user-friendly control software, and the pulse amplitude can be adjusted using a potentiometer in the pulse shaper board. The pulser was tested using several combinations of initial pulse rate and decay constant, and the results show that the system is stable and reliable, and is suitable to be used in half-life measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Scaling neural simulations in STACS

Abstract As modern neuroscience tools acquire more details about the brain, the need to move towards biological-scale neural simulations continues to grow. However, effective simulations at scale remain a challenge. Beyond just the tooling required to enable parallel execution, there is also the unique structure of the synaptic interconnectivity, which is globally sparse but has relatively high connection density and non-local interactions per neuron. There are also various practicalities to consider in high performance computing applications, such as the need for serializing neural networks to support potentially long-running simulations that require checkpoint-restart. Although acceleration on neuromorphic hardware is also a possibility, development in this space can be difficult as hardware support tends to vary between platforms and software support for larger scale models also tends to be limited. In this paper, we focus our attention on Simulation Tool for Asynchronous Cortical Streams (STACS), a spiking neural network simulator that leverages the Charm++ parallel programming framework, with the goal of supporting biological-scale simulations as well as interoperability between platforms. Central to these goals is the implementation of scalable data structures suitable for efficiently distributing a network across parallel partitions. Here, we discuss a straightforward extension of a parallel data format with a history of use in graph partitioners, which also serves as a portable intermediate representation for different neuromorphic backends. We perform scaling studies on the Summit supercomputer, examining the capabilities of STACS in terms of network build and storage, partitioning, and execution. We highlight how a suitably partitioned, spatially dependent synaptic structure introduces a communication workload well-suited to the multicast communication supported by Charm++. We evaluate the strong and weak scaling behavior for networks on the order of millions of neurons and billions of synapses, and show that STACS achieves competitive levels of parallel efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Estimating and parameterizing mismatch power loss in bifacial photovoltaic systems

Nonuniform irradiance on the rear side of bifacial photovoltaic (PV) systems can cause additional mismatch loss, which may not be appropriately captured in PV energy production estimates and software. We evaluated several scenarios including horizontal single-axis tracking (HSAT) over natural ground-cover and rooftop-mounted systems over high albedo reflective roofs. We found mismatch losses of up to 1.5% annual loss for very close-mounted (0.15 m) rooftop systems, but losses for HSAT systems and high-ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically, the mean absolute difference of irradiance) to the resulting mismatch loss factor, with an R 2 better than .99. Furthermore, this approximate relationship was experimentally validated on mismatched PV modules, and it provides a basis for rapidly estimating bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM. Additional parameters investigated include (a) climate dependence and module orientation, which were not found to have a strong impact on bifacial mismatch losses and (b) PV module fill factor and bifaciality ratio, which did have a strong linear impact on mismatch losses.

14 SOLAR ENERGY↗
DOE OSTI2017

Phantom Study Investigating the Accuracy of Manual and Automatic Image Fusion with the GE Logiq E9: Implications for use in Percutaneous Liver Interventions

PurposeTo determine the accuracy of automatic and manual co-registration methods for image fusion of three-dimensional computed tomography (CT) with real-time ultrasonography (US) for image-guided liver interventions.Materials and MethodsCT images of a skills phantom with liver lesions were acquired and co-registered to US using GE Logiq E9 navigation software. Manual co-registration was compared to automatic and semiautomatic co-registration using an active tracker. Also, manual point registration was compared to plane registration with and without an additional translation point. Finally, comparison was made between manual and automatic selection of reference points. In each experiment, accuracy of the co-registration method was determined by measurement of the residual displacement in phantom lesions by two independent observers.ResultsMean displacements for a superficial and deep liver lesion were comparable after manual and semiautomatic co-registration: 2.4 and 2.0 mm versus 2.0 and 2.5 mm, respectively. Both methods were significantly better than automatic co-registration: 5.9 and 5.2 mm residual displacement (p < 0.001; p < 0.01). The accuracy of manual point registration was higher than that of plane registration, the latter being heavily dependent on accurate matching of axial CT and US images by the operator. Automatic reference point selection resulted in significantly lower registration accuracy compared to manual point selection despite lower root-mean-square deviation (RMSD) values.ConclusionThe accuracy of manual and semiautomatic co-registration is better than that of automatic co-registration. For manual co-registration using a plane, choosing the correct plane orientation is an essential first step in the registration process. Automatic reference point selection based on RMSD values is error-prone.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

IMRT QA: Selecting gamma criteria based on error detection sensitivity

Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent across all studied combinations of %Diff/DTA. Criteria such as 2%/3 mm and 3%/2 mm with a 50% threshold at 90% pixels passing are shown to be more appropriately sensitive without being overly strict. However, a broadening of the penumbra by as much as 5 mm in the beam configuration was difficult to detect with commonly used criteria, as well as with the previously mentioned criteria utilizing a threshold of 50%. Conclusions: We have introduced the error curve method, an analysis technique which allows the quantitative determination of gamma criteria sensitivity to induced errors. The application of the error curve method using DMLC IMRT plans measured on the ArcCHECK® device demonstrated that large errors can potentially be missed in IMRT QA with commonly used gamma criteria (e.g., 3%/3 mm, threshold = 10%, 90% pixels passing). Additionally, increasing the dose threshold value can offer dramatic increases in error sensitivity. This approach may allow the selection of more meaningful gamma criteria for IMRT QA and is straightforward to apply to other combinations of devices and treatment techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Bubble masks for time-encoded imaging of fast neutrons.

Time-encoded imaging is an approach to directional radiation detection that is being developed at SNL with a focus on fast neutron directional detection. In this technique, a time modulation of a detected neutron signal is induced typically, a moving mask that attenuates neutrons with a time structure that depends on the source position. An important challenge in time-encoded imaging is to develop high-resolution two-dimensional imaging capabilities; building a mechanically moving high-resolution mask presents challenges both theoretical and technical. We have investigated an alternative to mechanical masks that replaces the solid mask with a liquid such as mineral oil. Instead of fixed blocks of solid material that move in pre-defined patterns, the oil is contained in tubing structures, and carefully introduced air gaps bubbles propagate through the tubing, generating moving patterns of oil mask elements and air apertures. Compared to current moving-mask techniques, the bubble mask is simple, since mechanical motion is replaced by gravity-driven bubble propagation; it is flexible, since arbitrary bubble patterns can be generated by a software-controlled valve actuator; and it is potentially high performance, since the tubing and bubble size can be tuned for high-resolution imaging requirements. We have built and tested various single-tube mask elements, and will present results on bubble introduction and propagation as a function of tubing size and cross-sectional shape; real-time bubble position tracking; neutron source imaging tests; and reconstruction techniques demonstrated on simple test data as well as a simulated full detector system.

Brubaker, Erik↗
DOE OSTI2013

Benchmark Imagery Project: Selection of Real World Images for Creating Composite Images of Facilities

The "Benchmark Imagery" project is a DOE NA-22-funded effort whose three-year goal is to create a suite of imagery (both real and composite) that can be used to test geospatial algorithms used for extracting semantic content from overhead images of industrial facilities. A composite image is an image that contains both real elements such as photographic imagery and synthetic elements such as 3D models. Composite images have the advantage of being customizable and distributable, and they can contain complete ground truth. It is our goal to generate composite images which appear realistic to both human and algorithm. When generating composite images of facilities we use real overhead imagery to increase realism and decrease effort. To construct all elements with purely synthetic textures would require too much effort and still may not look as realistic as a real image. We use real time 3D rendering software "SceneWorks" for rendering composite images. In SceneWorks, a scene is constructed by placing 3D models of facility components on top of a base terrain. A base terrain is a 3D model constructed from digital elevation mapping (DEM) data and then textured with overhead orthorectified imagery. The base terrain is constructed to be geospatially accurate using a real location’s source data (DEM and Imagery.) This document outlines the selection criteria in selecting appropriate location and source data for constructing the base terrain. Imagery should have resolution equal or better than desired composite image resolution. The imagery should have no seams. Seams can occur when two or more different imagery data sets exist in a single area with neither set covering the entire area. Elevation data (DEM) resolution generally should be 1/9 arc second or better depending on the variability of elevation. The imagery must contain a flat clearing of land large enough for multiple facility types. There should be no high-rise buildings anywhere in the base terrain.

42 ENGINEERING↗
DOE OSTI2015

Hydrogen Selective Exfoliated Zeolite Membranes

The objective of this project was to develop and evaluate an innovative membrane technology at process conditions that would be representative of Integrated Gasification Combined Cycle (IGCC) advanced power generation with pre-combustion capture of carbon dioxide (CO 2 ). This research focused on hydrogen (H 2 )-selective zeolite membranes that could be utilized to separate conditioned syngas into H 2 -rich and CO 2 -rich components. Both experiments and process design and optimization calculations were performed to evaluate the concept of ultra-thin membranes made from zeolites nanosheets. In this work, efforts in the laboratory were made to tackle two fundamental challenges in application of zeolite membranes in harsh industrial environments, namely, membrane thickness and membrane stability. Conventional zeolite membranes have thicknesses in the micron range, limiting their performance. In this research, we developed a method for fabrication of ultimately thin zeolite membranes based on zeolite nanosheets. A range of layered zeolites (MWW, RWR, NSI structure types) suitable for hydrogen separation was successfully exfoliated to their constituent nanosheets. Further, membranes were made from one of these zeolites, MWW, to demonstrate the potential of this group of materials. Moreover, long-term steam stability of these zeolites (up to 6 months) was investigated in high concentrations of steam (35 mol% and 95 mole%), high pressure (10 barg), and high temperatures (350 °C and 600 °C) relevant to conditions of water-gas-shift and steam methane reforming reactions. It was found that certain nanosheets are stable, and that stability depends on the concentration of structural defects. Additionally, models that represent a water-gas-shift (WGS) membrane reactor equipped with the zeolite membrane were developed for systems studies. These studies had the aim of analyzing the effect of the membrane reactor integration into IGCC plants in terms of performance and economic aspects of the plants. Specifically, simulation and design optimization studies were performed using the developed stand-alone membrane reactor models to identify the membrane selectivity and permeance characteristics necessary to achieve desired targets of CO 2 capture and H 2 recovery, as well as guide the selection of the optimal reactor design that minimizes the membrane cost as a function of its surface area required. The isothermal membrane reactor model was also integrated into IGCC system models using both the MATLAB and Aspen software platforms and techno-economic analyses of the integrated plants have been carried out to evaluate the feasibility of replacing current technologies for pre-combustion capture by the proposed novel approach in terms of satisfying stream constraints and achieving the DOE target goal of 90% CO 2 capture. The results of the performed analyses based on present value of annuity calculations showed break even costs for the membrane reactor within the feasible range for membrane fabrication. However, the predicted membrane performance used in these simulations exceeded the performance achieved experimentally. Therefore, further work is required to improve membrane performance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Numerical Implementation of Time-Dependent Density Functional Theory for Extended Systems in Extreme Environments

In recent years, DFT-MD has been shown to be a useful computational tool for exploring the properties of WDM. These calculations achieve excellent agreement with shock compression experiments, which probe the thermodynamic parameters of the Hugoniot state. New X-ray Thomson Scattering diagnostics promise to deliver independent measurements of electronic density and temperature, as well as structural information in shocked systems. However, they require the development of new levels of theory for computing the associated observables within a DFT framework. The experimentally observable x-ray scattering cross section is related to the electronic density-density response function, which is obtainable using TDDFT - a formally exact extension of conventional DFT that describes electron dynamics and excited states. In order to develop a capability for modeling XRTS data and, more generally, to establish a predictive capability for first principles simulations of matter in extreme conditions, real-time TDDFT with Ehrenfest dynamics has been implemented in an existing PAW code for DFT-MD calculations. The purpose of this report is to record implementation details and benchmarks as the project advances from software development to delivering novel scientific results. Results range from tests that establish the accuracy, efficiency, and scalability of our implementation, to calculations that are verified against accepted results in the literature. Aside from the primary XRTS goal, we identify other more general areas where this new capability will be useful, including stopping power calculations and electron-ion equilibration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-48: A Multi-Institutional Study of Independent Dose Verification for Conventional, SRS and SBRT

Purpose: To show the results of a multi-institutional study of the independent dose verification for conventional, Stereotactic radiosurgery and body radiotherapy (SRS and SBRT) plans based on the action level of AAPM TG-114. Methods: This study was performed at 12 institutions in Japan. To eliminate the bias of independent dose verification program (Indp), all of the institutions used the same CT-based independent dose verification software (Simple MU Analysis, Triangle Products, JP) with the Clarkson-based algorithm. Eclipse (AAA, PBC), Pinnacle{sup 3} (Adaptive Convolve) and Xio (Superposition) were used as treatment planning system (TPS). The confidence limits (CL, Mean±2SD) for 18 sites (head, breast, lung, pelvis, etc.) were evaluated in comparison in dose between the TPS and the Indp. Results: A retrospective analysis of 6352 treatment fields was conducted. The CLs for conventional, SRS and SBRT were 1.0±3.7 %, 2.0±2.5 % and 6.2±4.4 %, respectively. In conventional plans, most of the sites showed within 5 % of TG-114 action level. However, there were the systematic difference (4.0±4.0 % and 2.5±5.8 % for breast and lung, respectively). In SRS plans, our results showed good agreement compared to the action level. In SBRT plans, the discrepancy between the Indp was variable depending on dose calculation algorithms of TPS. Conclusion: The impact of dose calculation algorithms for the TPS and the Indp affects the action level. It is effective to set the site-specific tolerances, especially for the site where inhomogeneous correction can affect dose distribution strongly.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Particle in cell simulation of peaking switch for breakdown evaluation

Marx generator connected to peaking capacitor and peaking switch can generate Ultra-Wideband (UWB) radiation. A new peaking switch is designed for converting the existing nanosecond Marx generator to a UWB source. The paper explains the particle in cell (PIC) simulation for this peaking switch, using MAGIC 3D software. This peaking switch electrode is made up of copper tungsten material and is fixed inside the hermitically sealed derlin material. The switch can withstand a gas pressure up to 13.5 kg/cm{sup 2}. The lower electrode of the switch is connected to the last stage of the Marx generator. Initially Marx generator (without peaking stage) in air; gives the output pulse with peak amplitude of 113.75 kV and pulse rise time of 25 ns. Thus, we design a new peaking switch to improve the rise time of output pulse and to pressurize this peaking switch separately (i.e. Marx and peaking switch is at different pressure). The PIC simulation gives the particle charge density, current density, E counter plot, emitted electron current, and particle energy along the axis of gap between electrodes. The charge injection and electric field dependence on ionic dissociation phenomenon are briefly analyzed using this simulation. The model is simulated with different gases (N{sub 2}, H{sub 2}, and Air) under different pressure (2 kg/cm{sup 2}, 5 kg/cm{sup 2}, 10 kg/cm{sup 2}). (author)

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

SU-F-J-76: Evaluation of the Performance of Different Deformable Image Registration Algorithms in Helical, Axial and Cone-Beam CT Images of a Mobile Phantom

Purpose: To investigate quantitatively the performance of different deformable-image-registration algorithms (DIR) with helical (HCT), axial (ACT) and cone-beam CT (CBCT) by evaluating the variations in the CT-numbers and lengths of targets moving with controlled motion-patterns. Methods: Four DIR-algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from the DIRART-software are used to register CT-images of a mobile-phantom. A mobile-phantom is scanned with different imaging techniques that include helical, axial and cone-beam CT. The phantom includes three targets with different lengths that are made from water-equivalent material and inserted in low-density-foam which is moved with adjustable motion-amplitudes and frequencies. Results: Most of the DIR-algorithms are able to produce the lengths of the stationary-targets, however, they do not produce the CT-number values in CBCT. The image-artifacts induced by motion are more regular in CBCT imaging where the mobile-target elongation increases linearly with motion-amplitude. In ACT and HCT, the motion-artifacts are irregular where some mobile -targets are elongated or shrunk depending on the motion-phase during imaging. The DIR-algorithms are successful in deforming the images of the mobile-targets to the images of the stationary-targets producing the CT-number values and length of the target for motion-amplitudes < 20 mm. Similarly in ACT, all DIR-algorithms produced the actual CT-number and length of the stationary-targets for motion-amplitudes < 15 mm. As stronger motion-artifacts are induced in HCT and ACT, DIR-algorithms fail to produce CT-values and shape of the stationary-targets and fast-demons-algorithm has worst performance. Conclusion: Most of DIR-algorithms produce the CT-number values and lengths of the stationary-targets in HCT and ACT images that has motion-artifacts induced by small motion-amplitudes. As motion-amplitudes increase, the DIR-algorithms fail to deform mobile-target images to the stationary-images in HCT and ACT. In CBCT, DIR-algorithms are successful in producing length and shape of the stationary-targets, however, they fail to produce the accurate CT-number level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-229: Craniospinal Radiotherapy Planning with VMAT, Two First Years Experience

Purpose: To describe how we moved to VMAT in the craniospinal radiotherapy planning process, the actual procedure details, and the results for the patients treated. Methods: Twelve patients underwent craniospinal irradiation with the new procedure, based on the paper by Lee et al. (IJROBP 82, 2012), with some additional modifications. Patients were treated in supine position in Varian Clinac iX linacs with 6 MV RapidArc; prescription doses ranged from 23.4 to 40 Gy (13 to 20 fractions); depending on the PTV length, 2 or 3 isocenters were used, all coordinates being equal except the longitudinal one, setting a few centimeter-long overlapping region; 2 arcs (RA) sharing isocentre for the cranial region, RA1 encompassing cranium and superior spinal region, and RA2 intended to improve conformity, only for cranium; for spine, 1 or 2 isocenters were employed; optimization was performed with Eclipse (V 13.0) using AAA algorithm, establishing sets of optimization parameters to give high conformity while sparing OAR. In pediatric patients, homogeneous irradiation of the vertebrae was also required.Conformity (CI) and heterogeneity (HI) indices (same as Lee et al.), and mean and maximum doses for OAR were calculated. Several pre-treatment verification methods were used: Octavius4D (PTW) for each isocentre, point dose at the junction region, Portal Dosimetry (when possible), and independent MU verification software (Diamond, PTW). Results: CI median value was 1.02 (0.99–1.07) and HI, 1.07 (1.06–1.09); a great reduction was observed for CI and OAR mean doses with respect to Lee et al. data; median maximum eye lens dose was 7.3 Gy (4.0–12.0); mean LungV20Gy was 1.9%; in children, vertebrae were homogeneously irradiated (D95%=20.8 Gy, Dmean= 23.2 Gy).All pre-treatment verifications were found within our action levels except for Portal Dosimetry. Conclusion: A RapidArc planning process for craniospinal axis irradiation has been implemented with significant advantages on conformity, homogeneity, feasibility and efficiency. and increase brain tissue sparing. Variations in volume decrease may be related to shape or location of the tumor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Open Source Software Prevalence Ingest Tool

The OSSP Ingest Tool accepts user-input organizational information, ingests IT/OT asset lists in Excel format, and ingests the associated CycloneDX SBOM's. It then performs analytics demonstrating the ability to answer the follow research questions: o RQ1. Ability to identify all OSS services running on, and all OSS components present within, an OT device o RQ1a: Ability to differentiate multiple versions of the same OSS component within each OT device. o RQ1b: Ability to differentiate running from not-running OSS components. o RQ1c: Ability to differentiate based on the originator of the component, because a supplier may have modified it after retrieval from the upstream software source. o RQ2. Ability to correlate the identity of a single OSS component across multiple OT devices, mitigating common name variations such as differences in capitalization, '-' vs '_', and so on. o RQ3. Ability to perform subset analysis of OSS components across multiple OT devices o RQ3a: Ability to perform subset analysis across OSS libraries, generating density & distribution graphs to identify commonly-used libraries and outliers. o RQ3b: Ability to perform subset analysis of a single OSS library, generating density & distribution by CI sector, by device type, by device make/model, and/or by firmware version. o RQ3c: Ability to perform subset analysis by grouping OSS libraries according to programming language, then overlay with RQ4b. o RQ3d: Ability to perform subset analysis by OSS upstream source, providing insight into degree of modifications performed by suppliers. o RQ4. Ability to identify dependencies (transitive and direct) of each differentiated OSS library within each OT device, and enable RQ1,2,3 iteratively for dependencies. o RQ1. Ability to identify all OSS services running on, and all OSS components present within, an OT device o RQ1a: Ability to differentiate multiple versions of the same OSS component within each OT device. o RQ1b: Ability Page

Kapadia, Shayna [Lawrence Livermore National Labor↗
DOE OSTI2025

Monte Carlo N-Particle Transport Performance of Predicting Digital Radiographic IQI Inspection

The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.

digital X-ray radiography↗
DOE OSTI2022

Covariance matrices for variance-suppressed simulations

ABSTRACT Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistical uncertainties in simulations, usually achieved by increasing simulation sizes at the expense of computational power. It was recently proposed to reduce simulation variance without incurring additional computational costs by adopting fixed-amplitude initial conditions. This method has been demonstrated not to introduce bias in various statistics, including the two-point statistics of galaxy samples typically used for extracting cosmological parameters from galaxy redshift survey data, but requires us to revisit current methods for estimating covariance matrices of clustering statistics for simulations. In this work, we find that it is not trivial to construct covariance matrices analytically for fixed-amplitude simulations, but we demonstrate that ezmock (Effective Zel’dovich approximation mock catalogue), the most efficient method for constructing mock catalogues with accurate two- and three-point statistics, provides reasonable covariance matrix estimates for such simulations. We further examine how the variance suppression obtained by amplitude-fixing depends on three-point clustering, small-scale clustering, and galaxy bias, and propose intuitive explanations for the effects we observe based on the ezmock bias model.

79 ASTRONOMY AND ASTROPHYSICS↗