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DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1993

The Database Query Support Processor (QSP)

The number and diversity of databases available to users continues to increase dramatically. Currently, the trend is towards decentralized, client server architectures that (on the surface) are less expensive to acquire, operate, and maintain than information architectures based on centralized, monolithic mainframes. The database query support processor (QSP) effort evaluates the performance of a network level, heterogeneous database access capability. Air Force Material Command's Rome Laboratory has developed an approach, based on ANSI standard X3.138 - 1988, 'The Information Resource Dictionary System (IRDS)' to seamless access to heterogeneous databases based on extensions to data dictionary technology. To successfully query a decentralized information system, users must know what data are available from which source, or have the knowledge and system privileges necessary to find out this information. Privacy and security considerations prohibit free and open access to every information system in every network. Even in completely open systems, time required to locate relevant data (in systems of any appreciable size) would be better spent analyzing the data, assuming the original question was not forgotten. Extensions to data dictionary technology have the potential to more fully automate the search and retrieval for relevant data in a decentralized environment. Substantial amounts of time and money could be saved by not having to teach users what data resides in which systems and how to access each of those systems. Information describing data and how to get it could be removed from the application and placed in a dedicated repository where it belongs. The result simplified applications that are less brittle and less expensive to build and maintain. Software technology providing the required functionality is off the shelf. The key difficulty is in defining the metadata required to support the process. The database query support processor effort will provide quantitative data on the amount of effort required to implement an extended data dictionary at the network level, add new systems, adapt to changing user needs, and provide sound estimates on operations and maintenance costs and savings.

Source record↗

NASA NTRS2002

The New NASA Orbital Debris Engineering Model ORDEM2000

The NASA Orbital Debris Program Office at Johnson Space Center has developed a new computer-based orbital debris engineering model, ORDEM2000, which describes the orbital debris environment in the low Earth orbit region between 200 and 2000 km altitude. The model is appropriate for those engineering solutions requiring knowledge and estimates of the orbital debris environment (debris spatial density, flux, etc.). ORDEM2000 can also be used as a benchmark for ground-based debris measurements and observations. We incorporated a large set of observational data, covering the object size range from 10 mm to 10 m, into the ORDEM2000 debris database, utilizing a maximum likelihood estimator to convert observations into debris population probability distribution functions. These functions then form the basis of debris populations. We developed a finite element model to process the debris populations to form the debris environment. A more capable input and output structure and a user-friendly graphical user interface are also implemented in the model. ORDEM2000 has been subjected to a significant verification and validation effort. This document describes ORDEM2000, which supersedes the previous model, ORDEM96. The availability of new sensor and in situ data, as well as new analytical techniques, has enabled the construction of this new model. Section 1 describes the general requirements and scope of an engineering model. Data analyses and the theoretical formulation of the model are described in Sections 2 and 3. Section 4 describes the verification and validation effort and the sensitivity and uncertainty analyses. Finally, Section 5 describes the graphical user interface, software installation, and test cases for the user.

Liou, Jer-Chyi↗

DOE OSTI2015

Performance of a Low Activity Beta-Sensitive SR{sup 90} Water Monitor for Fukushima

There are large volumes of contaminated water from the stabilization efforts at the damaged Fukushima Nuclear Power Plants. This water is being processed to remove radioactivity for eventual release to the environment. An on-line continuously operating system to confirm that the clean-up system is working properly, and to provide prompt feedback of the results is required by the system operator. While gamma emitting nuclides allow for the straight forward approach of gamma spectroscopy to identify and quantify radioactivity in water, pure beta emitting nuclides such as Sr{sup 90} pose a challenging problem. The relatively short range of beta radiation in water requires optimization of the measurement geometry in terms of the source-detector distance and source-detector interface while retaining a background sensitivity low enough to meet the Minimum Detectable Concentration (MDC) of 10 Bq/kg in 180 minutes. This issue is complicated by the continuum nature of the beta spectrum which does not allow for simple nuclide identification. The use of the Monte-Carlo code MCNP to estimate system performance before prototyping vastly increases the success of the end product. Various parameters such as detector size and thickness, water chamber size, water chamber construction materials were evaluated to help choose the optimum geometry. The final design was a system consisting of two large-area (16 x 35 cm) and thin (0.15 mm) plastic scintillators placed very close to a sealed a water chamber. The size of the chamber was optimized to obtain the maximum efficiency for the nuclide being measured (Sr/Y{sup 90}) but to minimize the efficiency for possible interferences (Ru/Rh{sup 106}, Cs{sup 137}). A thin carbon fiber window was selected with adequate material and thickness to contain the water under pressure, but also thin enough (0.5 mm) to allow enough beta radiation to pass through to the active detector volume. The entire measurement geometry is then housed in a thick lead shield to reduce contributions from external sources to an acceptable level. Data acquisition is accomplished through customized application-specific software that allows for long counting times to attain a low MDC, but also simultaneously provides alarms on short averaging times to achieve a fast response to sudden changes in activity concentration. Multiple monitors are then linked to supervisory software where real time data and alarms are available for analysis in remote locations. The system also allows for remote operation of the unit; check sources, background checks, systems settings and more may be accessed remotely. Testing of the production devices has shown that we can achieve the 10 Bk/kg MDC requirement for Sr{sup 90} in equilibrium with Y{sup 90} with a count time of approximately 20 minutes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2013

Memory-Efficient Onboard Rock Segmentation

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Burl, Michael C.↗

DOE OSTI2016

SU-F-R-07: Radiomics of CT Features and Associations and Correlation with Outcomes Following Lung SBRT

Objective: To investigate the prognostic significance of image gradients and in predicting clinical outcomes in a patients with non-small cell lung cancer treated with stereotactic body radiotherapy (SBRT) on 71 patients with 83 treated lesions. Methods: The records of patients treated with lung SBRT were retrospectively reviewed. When applicable, SBRT target volumes were modified to exclude any overlap with pleura, chestwall, or mediastinum. The ITK software package was utilized to generate quantitative measures of image intensity, inhomogeneity, shape morphology and first and second-order CT textures. Multivariate and univariate models containing CT features were generated to assess associations with clinicopathologic factors. Results: On univariate analysis, tumor size (HR 0.54, p=0.045) sumHU (HR 0.31, p=0.044) and short run grey level emphasis STD (HR 0.22, p=0.019) were associated with regional failure-free survival; meanHU (HR 0.30, p=0.035), long run emphasis (HR 0.21, p=0.011) and long run low grey level emphasis (HR 0.14, p=0.005) was associated with distant failure-free survival (DFFS). No features were significant on multivariate modeling however long run low grey level emphasis had a hazard ratio of 0.12 (p=0.061) for DFFS. Adenocarcinoma and squamous cell carcinoma differed with respect to long run emphasis STD (p=0.024), short run low grey level emphasis STD (p<0.001), and long run low grey level emphasis STD (p=0.024). Multivariate modeling of texture features associated with tumor histology was used to estimate histologies of 18 lesions treated without histologic confirmation. Of these, MVA suggested the same histology as a prior metachronous lung malignancy in 3/7 patients. Conclusion: Extracting radiomics features on clinical datasets was feasible with the ITK package with minimal effort to identify pre-treatment quantitative CT features with prognostic factors for distant control after lung SBRT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Energy-Efficient and Comfortable Buildings through Multivariate Integrated Control (ECoMIC)

This project aims to develop an integrated control solution for enhanced energy efficiency and user comfort in commercial buildings. The developed technology is a zone-based control framework that minimizes energy usage while maintaining occupants’ visual and thermal comfort through control of electric lights, motorized venetian blinds and thermostats. The control framework is designed following a modular, scalable and flexible architecture to facilitate easy integration with exiting building management systems. The control framework contains two key algorithms: 1) the lighting load balancing algorithm and 2) the thermostat control algorithm. The lighting load balancing algorithm adopts a model-based closed-loop control approach to determine the optimal electric light and venetian blind settings. It is formulated into an optimization problem with minimizing lighting-related energy consumptions as the objective and delivering adequate task light and preventing daylight glare as the constraints. The thermostat control algorithm is based on a well-established thermal comfort model and formulated as a root-finding problem to dynamically determine the optimal thermostat setpoint for both energy savings and improved thermal comfort. To address building-wide scalability, a system architecture was developed for the zone-based control technology. Three levels of services are defined in the architecture: external services, facility level services and zone level services. The zone-level service includes the control algorithms described above as well as the corresponding interfaces, profiles, sensors and actuators to realize the zone controller. The facility level services connect to the zones through a backbone network, handle supervisory level information and controls, and thus facilitate building-wide scalability. The external services provide communication capability to entities outside of the building for grid interaction and remote access. Various aspects of the developed control technology were evaluated and verified through both simulations and testbed implementations. Simulations coupling a DOE medium office reference building in EnergyPlus building simulation software and a prototype controller in Matlab were performed. During summer time in a mixed-humid climate zone, the simulations revealed reductions of 27% and 42% in electric lighting load and cooling load, respectively, when compared to an advanced base case with daylight dimming and blinds automatically tilted to block direct sun. Two single-room testbeds were established. The testbed at Philips Lighting business building (Rosemont, IL) was designed for quantifying energy performance of integrated controls. This particular implementation achieved 40% and 79% savings on lighting and HVAC energy, respectively, compared to a relatively simple base case operated on predefined schedules. While the resulting energy savings was very encouraging, it should be noted that there may be several caveats associated with it. 1) The test was run during late spring and early summer, and the savings numbers might not be directly used to extrapolate the annual energy savings. 2) Due to the needs for separate control and metering of the small-scale demonstrator within a large building, the HVAC system, hence the corresponding savings, did not represent a typical energy code-compliant design. 3) The light level in the control case was regulated at a particular setpoint, which was lower than then the full-on light level in the base case, and the savings resulted from tuning down the light level to the setpoint was not attributable to the contribution of the developed technology. The testbed at the Lawrence Berkeley National Laboratory (Berkeley, CA) specifically focused on glare control integration, and has demonstrated the feasibility and capability of the glare detection and prevention technique. While the short one-month test in this testbed provided a functional indication of the developed technology, and it would require at least a full solstice-to-solstice cycle to ruinously quantify the performance, which was not possible within the project timeframe. There are certain limitations inherited from the operational assumptions, which could potentially affect the effectiveness and applicability of the developed control technologies. The system takes a typical ceiling-mounting approach for the photosensor locations, and therefore, the control performance relies on proper commissioning or the built-in intelligence of the photosensor for pertinent task light level estimations. For spaces where daylight penetration diminishes significantly deeper into the zone, certain modification to the control algorithms is required to accommodate multiple lighting control subzones and the corresponding sensors for providing a more uniform light level across the entire zone. Integrated control of visual and thermal comfort requires the lighting control zone and thermal control zone to coincide with each other. In other words, the area illuminated by a lighting circuit needs to be the same area served by the thermostat. Thus, the original zoning will potentially constrain the applicability of this technology in retrofitting projects. This project demonstrated the technical feasibility of a zone-based integrated control technology. From the simulation results and testbed implementations, up to 60% lighting energy savings in daylit areas relative to a “no-controls” case can easily be achieved. A 20% reduction of whole building energy consumption is also attainable. In the aspect of occupant comfort, the testbed demonstrated the ability to maintain specified light level on the workplane while promptly mitigate daylight glare 90% of the time. The control system also managed to maintain the thermal environment at a comfortable level 90% of the time. The aspect of system scalability was guaranteed by the system architecture design, based on which the testbeds were instantiated. Analysis on the aspect of economic benefit has yielded an about 6-year payback time for a medium-sized building, including the installation of all hardware and software, such as motorized blinds and LED luminaires. The payback time can be significantly reduced if part of the hardware is already in place for retrofitting projects. It needs to be noted that since the payback analysis was partly based on the testbed performance results, it is constrained by the caveats associated with the testbed implementations. The main uncertainty lies in the contribution from the space conditioning energy savings as it was non-trivial to realistically configure a room-size HVAC system for directly extrapolating whole-building HVAC energy savings. It is recommended to further evaluate the developed technology at a larger scale, where the lighting and HVAC energy consumption can be realistically measured at the building level, to more rigorously quantify the performance potentials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2012

Automated size-specific CT dose monitoring program: Assessing variability in CT dose

Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED{sub adj}). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED{sub adj} between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED{sub adj} that differed by up to 44% from effective dose estimates that were not adjusted by patient size. Additionally, considerable differences were noted in ED{sub adj} distributions between scanners, with scanners employing iterative reconstruction exhibiting significantly lower ED{sub adj} (range: 9%-64%). Finally, a significant difference (up to 59%) in ED{sub adj} distributions was observed between institutions, indicating the potential for dose reduction. Conclusions: The authors developed a robust automated size-specific radiation dose monitoring program for CT. Using this program, significant differences in ED{sub adj} were observed between scanner models and across institutions. This new dose monitoring program offers a unique tool for improving quality assurance and standardization both within and across institutions.

60 APPLIED LIFE SCIENCES↗

NASA NTRSDate not supplied

Toward an IMU-based Space Suit Motion Capture System

Spacesuits are complex engineering systems that sustain human health and enable performance outside of Earth-like environments. These systems must support human mobility and physical workload demands while minimizing injury risk during extravehicular activity (EVA). Future EVA on the lunar surface during the Artemis program is expected to be more frequent and require higher physical workloads than previous EVAs during the ISS, Shuttle, or Apollo programs. Hence it is important to optimize future as well as current spacesuits to be efficient and comfortable for the success of space and planetary missions. To enable this, an efficient method is needed to test these spacesuits on the ground.When testing spacesuits in ground environments, it is often necessary to understand the kinematics of the suit to validate the design against relevant requirements or characterize the physical workload necessary to operate the suit. This is a challenging task for traditional optical motion capture (OMC) approaches: suit-mounted OMC markers are easily occluded by the subject or environment and may become detached during testing. Controlling lighting and reflectivity of objects in the motion capture volume is also difficult. Fixed-position OMC cameras also constrain testing to a small and contrived laboratory environment, disallowing kinematics capture in field environments.One promising alternative is the use of suit-mounted inertial measurement units (IMUs). These sensors are small, unobtrusive, and portable, but come at the cost of increased sensor noise and complexity of the software and mathematics to analyze the collected data. To this end, engineers at NASA are developing the Augmented Suit Inverse Kinematics (ASIK) system, a complete motion capture methodand inverse kinematics solver which relies solely on a network of wireless IMUs attached to the major kinematic segments of the spacesuit. The ASIK modeling language allows for the simple inclusion of probabilistic priors such as suit size and shape or IMU positions and rotations. Furthermore, to increase accuracy and reduce operational overhead to use this motion capture approach, the developed inverse kinematics solver exploits so-called self-calibratingalgorithmic techniques, which reduce the need for precise alignment of the sensors on the segments or scripted functional calibration procedures. The ASIK system was tested in a 7-subject pilot study. Each subject donned NASA’s new prototype exploration spacesuit in the Active Response Gravity Offload System (ARGOS) facility at the NASA Johnson Space Center. The subjects were outfitted with a set of 14 APDM (Portland, OR, USA) Opal IMUs, 12 of which were used in the ASIK model to estimate lower body and trunk kinematics. The subjects were also outfitted with a set of reflective OMC markers and traditional OMC data was collected and processed. Presented results will include characterization of ASIK-derived suit joint angles accuracy against an optical motion capture datum. Discussion of these results, as well as discussion of system calibration and nuances of mathematical observability, will be included.If successful, IMU-based motion capture will enable testing and validation of spacesuits more frequently, with less overhead, in more extreme environments. Future work will apply these techniques to common spacesuit testing tasks, such as gait, mobility, and balance assessment, physical workload characterization, and ergonomics evaluations.

Timothy Mcgrath↗

DOE OSTI2014

TU-A-9A-03: Development and Verification of a Forward Model That Assists in Iterative Post-Processing Algorithms Used to Reduce Blur in Compton Backscatter Imaging Systems

Purpose: In Compton Backscatter Imaging (CBI), the source and detector reside on the same side of the patient. We previously demonstrated the applicability of CBI systems for medical purposes using an industrial system. To assist in post-processing images from a CBI system, a forward model based on radiation absorption and scatter principles has been developed. Methods: The forward model was developed in C++ using raytracing to track particles. The algorithm accepts phantoms of any size and resolution to calculate the fraction of incident photons scattered back to the detector, and can perform these calculations for any detector geometry and source specification. To validate the model, results were compared to MCNP-X, which is a Monte Carlo based simulation software, for various combinations of source specifications, detector geometries, and phantom compositions. Results: The model verified that the backscatter signal to the detector was based on three interaction probabilities: a) attenuation of photons going into the phantom, b) Compton scatter of photons toward the detector, and c) attenuation of photons coming out of the phantom. The results from the MCNP-X simulations and the forward model varied from 1 to 5%. This difference was less than 1% for energies higher than 30 keV, but was up to 4% for lower energies. At 50 keV, the difference was less than 1% for multiple detector widths and for both homogeneous and heterogeneous phantoms. Conclusion: As part of the optimization of a medical CBI system, an efficient and accurate forward model was constructed in C++ to estimate the output of CBI system. The model characterized individual components contributing to CBI output and increased computational efficiency over Monte Carlo simulations. It is now used in the development of novel post-processing algorithms that reduce image blur by reversing undesired contribution from outside the region of interest.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗

DOE OSTI2016

TU-H-CAMPUS-IeP1-03: Comparison of Monte Carlo Simulation and Conversion Factor Based Method On Estimation of Effective Dose in Pediatric Patients Undergoing Interventional Cardiac Procedures

Purpose: Interventional cardiac procedures utilize frequent fluoroscopy and cineangiography, which impose considerable radiation risk to patients, especially pediatric patients. Accurate calculation of effective dose is important in order to estimate cancer risk over the rest of their lifetime. This study evaluates the difference in effective dose calculated by Monte Carlo simulation with those estimated by locally-derived conversion factors (CF-local) and by commonly quoted conversion factors from Karambatsakidou et al (CF-K). Methods: Effective dose (E),of 12 pediatric patients, age between 2.5–19 years old, who had undergone interventional cardiac procedures, were calculated using PCXMC-2.0 software. Tube spectrum, irradiation geometry, exposure parameters and dose-area product (DAP) of each projection were included in the software calculation. Effective doses for each patient were also estimated by two Methods: 1) CF-local: conversion factor derived locally by generalizing results of 12 patients, multiplied by DAP of each patient gives E-local. 2) CF-K: selected factor from above-mentioned literature, multiplied by DAP of each patient gives E-K. Results: Mean of E, E-local and E-K were 16.01 mSv, 16.80 mSv and 22.25 mSv respectively. A deviation of −29.35% to +34.85% between E and E-local, while a greater deviation of −28.96% to +60.86% between E and EK were observed. E-K overestimated the effective dose for patients at age 7.5–19. Conclusion: Effective dose obtained by conversion factors is simple and quick to estimate radiation risk of pediatric patients. This study showed that estimation by CF-local may bear an error of 35% when compared with Monte Carlo calculation. If using conversion factors derived by other studies may result in an even greater error, of up to 60%, due to factors that are not catered for in the estimation, including patient size, projection angles, exposure parameters, tube filtration, etc. Users must be aware of these potential inaccuracies when simple conversion method is employed.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2022

Quantifying Errors in 3D CME Parameters Derived from Synthetic Data Using White-Light Reconstruction Techniques

Current efforts in space weather forecasting of CMEs have been focused on predicting their arrival time and magnetic structure. To make these predictions, methods have been developed to derive the true CME speed, size, position, and mass, among others. Difficulties in determining the input parameters for CME forecasting models arise from the lack of direct measurements of the coronal magnetic fields and uncertainties in estimating the CME 3D geometric and kinematic parameters after eruption. White-light coronagraph images are usually employed by a variety of CME reconstruction techniques that assume more or less complex geometries. This is the first study from our International Space Science Institute (ISSI) team “Understanding Our Capabilities in Observing and Modeling Coronal Mass Ejections”, in which we explore how subjectivity affects the 3D CME parameters that are obtained from the Graduated Cylindrical Shell (GCS) reconstruction technique, which is widely used in CME research. To be able to quantify such uncertainties, the “true” values that are being fitted should be known, which are impossible to derive from observational data. We have designed two different synthetic scenarios where the “true” geometric parameters are known in order to quantify such uncertainties for the first time. We explore this by using two sets of synthetic data: 1) Using the ray-tracing option from the GCS model software itself, and 2) Using 3D magnetohydrodynamic (MHD) simulation data from the Magnetohydrodynamic Algorithm outside a Sphere code. Our experiment includes different viewing configurations using single and multiple viewpoints. CME reconstructions using a single viewpoint had the largest errors and error ranges overall for both synthetic GCS and simulated MHD white-light data. As the number of viewpoints increased from one to two, the errors decreased by approximately 4° in latitude, 22° in longitude, 14° in tilt, and 10° in half-angle. Our results quantitatively show the critical need for at least two viewpoints to be able to reduce the uncertainty in deriving CME parameters. We did not find a significant decrease in errors when going from two to three viewpoints for our specific hypothetical three spacecraft scenario using synthetic GCS white-light data. As we expected, considering all configurations and numbers of viewpoints, the mean absolute errors in the measured CME parameters are generally significantly higher in the case of the simulated MHD white-light data compared to those from the synthetic white-light images generated by the GCS model. We found the following CME parameter error bars as a starting point for quantifying the minimum error in CME parameters from white-light reconstructions: Δθ (latitude)=6° +2° -3° , Δϕ (longitude)=11° +18° -6° , Δγ (tilt)=25° +8° -7° , Δx (half-angle)=10° +12° -6° , Δh (height)=0.6 +1.2 -0.4 R ⨀ , and Δκ (ratio)=0.1 +0.03 -0.02 .

Coronal mass ejections↗

NASA NTRS2022

Quantifying Errors in 3D CME Parameters Derived From Synthetic Data Using White-Light Reconstruction Techniques

Coronal mass ejections↗

NASA NTRS2023

Thermal Management System Modeling in the Heat Transport System Simulation (HeaTSSPy) Package

This paper describes the development of a thermal management system (TMS) concept design and analysis software package called Heat Transport System Simulation (HeaTSSPy). Built within Python using the OpenMDAO framework, HeaTSSPy can be used to size and optimize an active (using liquid/air heat exchangers) or passive (using finned heat sinks) TMS. The package makes use of modular TMS elements that allow for the creation of different system architectures and includes components such as heat sinks, heat exchangers, liquid pumps, fans, ducts, air inlets, air nozzles, and liquid pipes. Modeling methods for these components include a combination of physics-based analytical and empirical equations that relate component sizing criteria to system performance. The HeatSSPy heat sink methods are fully detailed within this paper, while the heat exchanger methods are described and referenced from previous work. This paper also uses high-fidelity simulation to validate two different methods of calculating thermal resistance using CFD results. Once the methods are fully described, the code is exercised to compare an active TMS with that of a passive TMS. Design criteria for this study include rejected heat, system altitude, Mach number, and ambient temperature. These criteria are used to develop a TMS system with estimated performance metrics such as weight, drag, and operational power. Results of this paper show the crossover point when a passive system begins to weigh more than an active system for a given heat rejection.

Thermal management system↗

DOE OSTI2013

Investigating the effect of characteristic x-rays in cadmium zinc telluride detectors under breast computerized tomography operating conditions

A number of research groups have been investigating the use of dedicated breast computerized tomography (CT). Preliminary results have been encouraging, suggesting an improved visualization of masses on breast CT as compared to conventional mammography. Nonetheless, there are many challenges to overcome before breast CT can become a routine clinical reality. One potential improvement over current breast CT prototypes would be the use of photon counting detectors with cadmium zinc telluride (CZT) (or CdTe) semiconductor material. These detectors can operate at room temperature and provide high detection efficiency and the capability of multi-energy imaging; however, one factor in particular that limits image quality is the emission of characteristic x-rays. In this study, the degradative effects of characteristic x-rays are examined when using a CZT detector under breast CT operating conditions. Monte Carlo simulation software was used to evaluate the effect of characteristic x-rays and the detector element size on spatial and spectral resolution for a CZT detector used under breast CT operating conditions. In particular, lower kVp spectra and thinner CZT thicknesses were studied than that typically used with CZT based conventional CT detectors. In addition, the effect of characteristic x-rays on the accuracy of material decomposition in spectral CT imaging was explored. It was observed that when imaging with 50-60 kVp spectra, the x-ray transmission through CZT was very low for all detector thicknesses studied (0.5–3.0 mm), thus retaining dose efficiency. As expected, characteristic x-ray escape from the detector element of x-ray interaction increased with decreasing detector element size, approaching a 50% escape fraction for a 100 μm size detector element. The detector point spread function was observed to have only minor degradation with detector element size greater than 200 μm and lower kV settings. Characteristic x-rays produced increasing distortion in the spectral response with decreasing detector element size. If not corrected for, this caused a large bias in estimating tissue density parameters for material decomposition. It was also observed that degradation of the spectral response due to characteristic x-rays caused worsening precision in the estimation of tissue density parameters. It was observed that characteristic x-rays do cause some degradation in the spatial and spectral resolution of thin CZT detectors operating under breast CT conditions. These degradations should be manageable with careful selection of the detector element size. Even with the observed spectral distortion from characteristic x-rays, it is still possible to correctly estimate tissue parameters for material decomposition using spectral CT if accurate modeling is used.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) Version 4.1 Technical Reference Manual

The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 4.1. The two most significant changes for HyRAM+ version 4.1 from HyRAM+ version 4.0 are direct incorporation of unconfined overpressure into the QRA calculations and modification of the models for cryogenic liquid flow through an orifice. In QRA mode, the user no longer needs to input peak overpressure and impulse values that were calculated separately; rather, the unconfined overpressure is estimated for the given system inputs, leak size, and occupant location. The orifice flow model now solves for the maximum mass flux through the orifice at constant entropy while conserving energy, which does not require a direct speed of sound calculation. This does not affect the mass flow for all-gaseous releases; the method results in the same speed of sound for choked flow. However, this method does result in a higher (and more realistic) mass flow rate for a given leak size for liquid releases than was previously calculated.

08 HYDROGEN↗