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DOE OSTI2014

Dynamic tumor tracking using the Elekta Agility MLC

Purpose: To evaluate the performance of the Elekta Agility multileaf collimator (MLC) for dynamic real-time tumor tracking. Methods: The authors have developed a new control software which interfaces to the Agility MLC to dynamically program the movement of individual leaves, the dynamic leaf guides (DLGs), and the Y collimators (“jaws”) based on the actual target trajectory. A motion platform was used to perform dynamic tracking experiments with sinusoidal trajectories. The actual target positions reported by the motion platform at 20, 30, or 40 Hz were used as shift vectors for the MLC in beams-eye-view. The system latency of the MLC (i.e., the average latency comprising target device reporting latencies and MLC adjustment latency) and the geometric tracking accuracy were extracted from a sequence of MV portal images acquired during irradiation for the following treatment scenarios: leaf-only motion, jaw + leaf motion, and DLG + leaf motion. Results: The portal imager measurements indicated a clear dependence of the system latency on the target position reporting frequency. Deducting the effect of the target frequency, the leaf adjustment latency was measured to be 38 ± 3 ms for a maximum target speed v of 13 mm/s. The jaw + leaf adjustment latency was 53 ± 3 at a similar speed. The system latency at a target position frequency of 30 Hz was in the range of 56–61 ms for the leaves (v ≤ 31 mm/s), 71–78 ms for the jaw + leaf motion (v ≤ 25 mm/s), and 58–72 ms for the DLG + leaf motion (v ≤ 59 mm/s). The tracking accuracy showed a similar dependency on the target position frequency and the maximum target speed. For the leaves, the root-mean-squared error (RMSE) was between 0.6–1.5 mm depending on the maximum target speed. For the jaw + leaf (DLG + leaf) motion, the RMSE was between 0.7–1.5 mm (1.9–3.4 mm). Conclusions: The authors have measured the latency and geometric accuracy of the Agility MLC, facilitating its future use for clinical tracking applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRA-11: An Experimental Commissioning Test of Brachytherapy MBDCA Dosimetry, Based On a Commercial Radiochromic Gel/optical CT System

Purpose: To implement a 3D dose verification procedure of Model-Based Dose Calculation Algorithms (MBDCAs) for {sup 192}Ir HDR brachytherapy, based on a novel Ferrous Xylenol-orange gel (FXG) and optical CT read-out. Methods: The TruView gel was employed for absolute dosimetry in conjunction with cone-beam optical CT read-out with the VISTA scanner (both from Modus Medical Inc, London, ON, Canada). A multi-catheter skin flap was attached to a cylindrical PETE jar (d=9.6cm, h=16cm) filled with FXG, which served as both the dosimeter and the water equivalent phantom of bounded dimensions. X- ray CT image series of the jar with flap attached was imported to Oncentra Brachy v.4.5. A treatment plan consisting of 8 catheters and 56 dwell positions was generated, and Oncentra-ACE MBDCA as well as TG43 dose results were exported for further evaluation. The irradiation was carried out with a microSelecton v2 source. The FXG dose-response, measured via an electron irradiation of a second dosimeter from the same batch, was linear (R2>0.999) at least up to 12Gy. A MCNP6 input file was prepared from the DICOM-RT plan data using BrachyGuide to facilitate Monte Carlo (MC) simulation dosimetry in the actual experimental geometry. Agreement between experimental (reference) and calculated dose distributions was evaluated using the 3D gamma index (GI) method with criteria (5%-2mm applied locally) determined from uncertainty analysis. Results: The TG-43 GI failed, as expected, in the majority of voxels away from the flap (pass rate 59% for D>0.8Gy, corresponding to 10% of prescribed dose). ACE performed significantly better (corresponding pass rate 92%). The GI evaluation for the MC data (corresponding pass rate 97%) failed mainly at low dose points of increased uncertainty. Conclusion: FXG gel/optical CT is an efficient method for level-2 commissioning of brachytherapy MBDCAs. Target dosimetry is not affected from uncertainty introduced by TG43 assumptions in 192Ir skin brachytherapy. Research co-financed by the ESF and Greek funds through the Operational Program Education and Lifelong Learning Investing in Knowledge Society of the NSRF. Research Funding Program: Aristeia. Modus Medical Devices Inc. provided a TruView dosimeter batch and Nucletron, and Elekta company, provided access to Oncentra Brachy v4.5, for research purposes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Advanced Analytics Studies Applied to US Department of Veterans Affairs' Corporate Data Warehouse (Initial Draft)

In this report, we describe our experience of applying several advanced analytics algorithms to the US Department of Veterans Affairs’ (VA’s) Corporate Data Warehouse (CDW) electronic health records datasets during FY2017-18. While various algorithms were applied to the CDW data, the main goal of this effort was to provide useful insights into the operational aspects (as opposed to the purely clinical aspect) of this specific implementation. Since there are not many reports in the public literature on advanced analytics applied to this data, this report provides unique insight in this regard. We focused on two machine learning (ML) applications: (1) clinical pathway inference (patterns dominating clinical pathways applied to a male dataset of Stable Ischemic Heart Disease patients as use case) and (2) medical-concept representation learning’s capability to inform and refine cohort membership based on probable patient outcomes. During our study on clinical pathway inference, we used two main modeling techniques: (a) topic probabilistic modeling (latent Dirichlet allocation [LDA]) and (b) feature imbedding. We observed that the applicability of LDA to the pathway inference remains in question. LDA provides results that are intuitive and easy for humans to comprehend; however, when applied to the pathway inference, it also generates pathway patterns that consist of a few dominant pathway components. In addition, LDA provides no information regarding the relationships among components in the same pathway. The outputs of LDA are also found to categorize patients based on their trace data of clinical procedures. However, the results suggest that LDA is biased toward statistically dominant components. This makes it particularly hard to discriminate pathway subbranches. To address the issue, we designed a new pathway inference methodology that integrates temporal ordering of pathway components into LDA results, as existing feature embedding tools such as word2vec are not readily applicable to our task. In addition, we developed our own feature embedding tool customized for patient traces. We conclude this study by suggesting two approaches to use embedding representation of a component into LDA and briefly list our lessons learned and recommendations for future work. For our study on medical-concept representation learning ability to inform and refine cohort membership based on probable patient outcomes, during our empirical evaluation we compared methods from medical-concept learning to standard one of a kind (one-of-K) encoding to evaluate the change in effectiveness as done in Choi, Schuetz, Stewart, and Sun (2016). We performed two primary empirical evaluations. The first evaluation was on a curated collection of 60,000 patients with no more than 1 year of medical history included. The second was a collection of patients with no restriction to the amount of medical history included. The hypothesis across both evaluations is that representation learning is broadly useful independent of downstream processing models; thus, for each experiment, we trained three models—a logistic regression model, a two-layer neural network model, and a nearest-neighbor model—and then averaged the results. Each model was trained using fivefold cross validation. We provided evidence that medical-representation learning improves predictions of the primary diagnosis category of a short patient history through 12 experiments. In addition, we provided evidence that medical-representation learning fails to improve prediction of the primary diagnosis category of an arbitrarily long patient history through 12 experiments. We conclude this study with a brief list of our lessons learned and recommendations for future work. We conclude the report with a discussion of recent technology trends as they relate to our artificial intelligence and, more specifically, to our ML research and approaches as described previously.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

3D tomodosimetry using long scintillating fibers: A feasibility study

Purpose: 3D dosimetry is recognized as an ideal for patient-specific quality assurance (QA) of highly conformal radiotherapy treatments. However, existing 3D dosimeters are not straightforward to implement in the clinic, as their read-out procedure is often tedious and their accuracy, precision, and/or sample size exhibit limitations. The purpose of this work is to develop a 3D dosimeter based on the concept of tomodosimetry inside concentric cylindrical planes using long scintillating fibers for the QA of modern radiotherapy techniques such as intensity-modulated radiation therapy (IMRT) or intensity-modulated arc therapy (IMAT).Methods: Using a model-based simulation, scintillating fibers were modeled on three concentric cylindrical planes of radii 2.5, 5.0, and 7.5 cm, inside a 10 cm radius water-equivalent cylinder phantom. The phantom was set to rotate around its central axis, made parallel to the linac gantry axis of rotation. Light acquisitions were simulated using the calculated dose from the treatment planning software and reconstructed in each cylindrical plane at a resolution of 1 mm{sup 2} using a total-variation minimization iterative reconstruction algorithm. The 3D dose was then interpolated from the reconstructed cylindrical plane doses at a resolution of 1 mm{sup 3}. Different scintillating fiber patterns were compared by varying the angle of each fiber in its cylindrical plane and introducing a light-tight cut in each fiber. The precision of the reconstructed cylindrical dose distribution was evaluated using a Poisson modeling of the acquired light signals and the accuracy of the interpolated 3D dose was evaluated using an IMRT clinical plan for a prostate case.Results: Straight scintillating fiber patterns with light-tight cuts were the most accurate in cylindrical dose reconstruction, showing less than 0.5 mm distance-to-agreement in dose gradients and a mean local dose difference of less than 0.2% in the high dose region for a 10 × 10 cm{sup 2} field. The precision attained with this fiber configuration was less than 0.9% in the high dose, low gradient region of an IMRT segment for light acquisitions of 0.1 MU over a 360 degree rotation of the cylinder phantom. 3D dose interpolation for the IMRT clinical plan yielded an overall dose difference with the reference input of less than 1%, except in high dose gradients.Conclusions: Using long scintillating fibers inside rotating, concentric cylindrical planes, the authors demonstrate that their tomodosimetry method has the potential for high resolution, precise, and accurate 3D dosimetry. Moreover, because of its water-equivalence and rotational symmetry, this design should find interesting application for both treatment QA and machine commissioning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Argonne Reactor Code Software Verification and Validation Plan for the Versatile Test Reactor

This Argonne Reactor Code (ARC) software has taken a pivotal role in the design work of the Versatile Test Reactor. The ARC software itself consists of several independent or semiindependent pieces of software that are used in concert to carry out specific analysis and design objectives. In this report, we discuss the validation that is needed for the ARC software overall and discuss available, usable experimental data and how it relates to the VTR project. We also discuss the verification that is required for the ARC software with respect to its usage in the VTR project and give some concrete examples as to what it must accomplish. A list of goals for the verification and validation work are presented as the general procedure that will be implemented for every individual piece of software in ARC. The ARC software has been continuously developed for over 50 years and many of the features used for the VTR project have thus been rigorously tested for accuracy during that timeframe. The ARC software is presently under source code control and undergoes nightly regression testing of not only the individual pieces, but the interconnected aspects that are common to most analysis projects. Its greatest weakness, from a software verification and validation perspective, is both a lack of documentation and outdated documentation. As an example, much of the previous validation work will require contemporary effort to re-evaluate given the updated base data libraries and modifications to the software that have occurred since. This requires new documentation to be produced to support the usage of the software in the VTR project. The bulk of the ARC software is focused on steady state neutronics and TH behavior of a reactor system. In this regard, we have identified the ZPPR, FFTF, and EBR-II programs as the best candidates for sources of validation data for the VTR project. The ZPPR-15 series in the ZPPR program was chosen as it is the best representation of the VTR fuel form and reactor core layout of all of the ZPPR measurements. Additional support for it comes from the fact that most of the data has already been processed into usable ARC models for VTR validation. The FFTF and EBR-II reactors were both functional reactors that provide reactor scale measurements. FFTF is clearly a closer match to VTR and its startup measurements would be a very valuable validation basis. EBR-II has invaluable burnup related measurements that will play a key role in the ARC software validation work. Each piece of ARC software will require a report detailing the software verification. The validation work will be logically split into the results of modeling each identified experimental resource (ZPPR, EBR-II, FFTF). The intended timeline for the VTR project is to have the ARC software verified and validated by the end of fiscal year 2020. This is incumbent on sufficient funding allocated to V&V activities and no change in programmatic priorities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

A study of IMRT planning parameters on planning efficiency, delivery efficiency, and plan quality

Purpose: To improve planning and delivery efficiency of head and neck IMRT without compromising planning quality through the evaluation of inverse planning parameters.Methods: Eleven head and neck patients with pre-existing IMRT treatment plans were selected for this retrospective study. The Pinnacle treatment planning system (TPS) was used to compute new treatment plans for each patient by varying the individual or the combined parameters of dose/fluence grid resolution, minimum MU per segment, and minimum segment area. Forty-five plans per patient were generated with the following variations: 4 dose/fluence grid resolution plans, 12 minimum segment area plans, 9 minimum MU plans, and 20 combined minimum segment area/minimum MU plans. Each plan was evaluated and compared to others based on dose volume histograms (DVHs) (i.e., plan quality), planning time, and delivery time. To evaluate delivery efficiency, a model was developed that estimated the delivery time of a treatment plan, and validated through measurements on an Elekta Synergy linear accelerator. Results: The uncertainty (i.e., variation) of the dose-volume index due to dose calculation grid variation was as high as 8.2% (5.5 Gy in absolute dose) for planning target volumes (PTVs) and 13.3% (2.1 Gy in absolute dose) for planning at risk volumes (PRVs). Comparison results of dose distributions indicated that smaller volumes were more susceptible to uncertainties. The grid resolution of a 4 mm dose grid with a 2 mm fluence grid was recommended, since it can reduce the final dose calculation time by 63% compared to the accepted standard (2 mm dose grid with a 2 mm fluence grid resolution) while maintaining a similar level of dose-volume index variation. Threshold values that maintained adequate plan quality (DVH results of the PTVs and PRVs remained satisfied for their dose objectives) were 5 cm{sup 2} for minimum segment area and 5 MU for minimum MU. As the minimum MU parameter was increased, the number of segments and delivery time were decreased. Increasing the minimum segment area parameter decreased the plan MU, but had less of an effect on the number of segments and delivery time. Our delivery time model predicted delivery time to within 1.8%. Conclusions: Increasing the dose grid while maintaining a small fluence grid allows for improved planning efficiency without compromising plan quality. Delivery efficiency can be improved by increasing the minimum MU, but not the minimum segment area. However, increasing the respective minimum MU and/or the minimum segment area to any value greater than 5 MU and 5 cm{sup 2} is not recommended because it degrades plan quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free-breathing PET using respiration-suspended PET images as reference

Purpose: To assess and account for the impact of respiratory motion on the variability of activity and volume determination of liver tumor in positron emission tomography (PET) through a comparison between free-breathing (FB) and respiration-suspended (RS) PET images. Methods: As part of a PET/computed tomography (CT) guided percutaneous liver ablation procedure performed on a PET/CT scanner, a patient's breathing is suspended on a ventilator, allowing the acquisition of a near-motionless PET and CT reference images of the liver. In this study, baseline RS and FB PET/CT images of 20 patients undergoing thermal ablation were acquired. The RS PET provides near-motionless reference in a human study, and thereby allows a quantitative evaluation of the effect of respiratory motion on PET images obtained under FB conditions. Two methods were applied to calculate tumor activity and volume: (1) threshold-based segmentation (TBS), estimating the total lesion glycolysis (TLG) and the segmented volume and (2) histogram-based estimation (HBE), yielding the background-subtracted lesion (BSL) activity and associated volume. The TBS method employs 50% of the maximum standardized uptake value (SUV{sub max}) as the threshold for tumors with SUV{sub max} ≥ 2× SUV{sub liver-bkg}, and tumor activity above this threshold yields TLG{sub 50%}. The HBE method determines local PET background based on a Gaussian fit of the low SUV peak in a SUV-volume histogram, which is generated within a user-defined and optimized volume of interest containing both local background and lesion uptakes. Voxels with PET intensity above the fitted background were considered to have originated from the tumor and used to calculate the BSL activity and its associated lesion volume. Results: Respiratory motion caused SUV{sub max} to decrease from RS to FB by −15% ± 11% (p = 0.01). Using TBS method, there was also a decrease in SUV{sub mean} (−18% ± 9%, p = 0.01), but an increase in TLG{sub 50%} (18% ± 36%) and in the segmented volume (47% ± 52%, p = 0.01) from RS to FB PET images. The background uptake in normal liver was stable, 1% ± 9%. In contrast, using the HBE method, the differences in both BSL activity and BSL volume from RS to FB were −8% ± 10% (p = 0.005) and 0% ± 16% (p = 0.94), respectively. Conclusions: This is the first time that almost motion-free PET images of the human liver were acquired and compared to free-breathing PET. The BSL method's results are more consistent, for the calculation of both tumor activity and volume in RS and FB PET images, than those using conventional TBS. This suggests that the BSL method might be less sensitive to motion blurring and provides an improved estimation of tumor activity and volume in the presence of respiratory motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Edible oil structures at low and intermediate concentrations. II. Ultra-small angle X-ray scattering of in situ tristearin solids in triolein

Ultra-small angle X-ray scattering has been used for the first time to elucidate, in situ, the aggregation structure of a model edible oil system. The three-dimensional nano- to micro-structure of tristearin solid particles in triolein solvent was investigated using 5, 10, 15, and 20% solids. Three different sample preparation procedures were investigated: two slow cooling rates of 0.5°/min, case 1 (22 days of storage at room temperature) and case 2 (no storage), and one fast cooling of 30°/min, case 3 (no storage). The length scale investigated, by using the Bonse-Hart camera at beamline ID-15D at the Advanced Photon Source, Argonne National Laboratory, covered the range from 300 Å to 10 μm. The unified fit and the Guinier-Porod models in the Irena software were used to fit the data. The former was used to fit 3 structural levels. Level 1 structures showed that the primary scatterers were essentially 2-dimensional objects for the three cases. The scatterers possessed lateral dimensions between 1000 and 4300 Å. This is consistent with the sizes of crystalline nanoplatelets present which were observed using cryo-TEM. Level 2 structures were aggregates possessing radii of gyration, R{sub g2} between 1800 Å and 12000 Å and fractal dimensions of either D{sub 2}=1 for case 3 or 1.8≤D{sub 2}≤2.1 for case 1 and case 2. D{sub 2} = 1 is consistent with unaggregated 1-dimensional objects. 1.8 ≤ D{sub 2} ≤ 2.1 is consistent with these 1-dimensional objects (below) forming structures characteristic of diffusion or reaction limited cluster-cluster aggregation. Level 3 structures showed that the spatial distribution of the level 2 structures was uniform, on the average, for case 1, with fractal dimension D{sub 3}≈3 while for case 2 and case 3 the fractal dimension was D{sub 3}≈2.2, which suggested that the large-scale distribution had not come to equilibrium. The Guinier-Porod model showed that the structures giving rise to the aggregates with a fractal dimension given by D{sub 2} in the unified fit level 2 model were cylinders described by the parameter s≈1 in the Guinier-Porod model. The size of the base of these cylinders was in agreement with the cryo-TEM observations as well as with the results of the level 1 unified fit model. By estimating the size of the nanoplatelets and understanding the structures formed via their aggregation, it will be possible to engineer novel lipids systems that embody desired functional characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

SISTec: Mathematical Calibration of Large Clearance Monitors - 18265

One major path for clearance of large amount of waste arising from the decommission of nuclear power plants is based on measurement with large clearance monitors (also known as free release measurement facilities). These devices utilize multi-detector plastic scintillator arrays (large clearance monitors can consist of up to 24 plastic scintillators) to offer both, extremely low minimum detectable activities (MDA) and short measurement times for waste packages weighing up to one metric ton. However, a major problem with these devices is to obtain nuclide specific efficiencies, especially for geometrically complex large waste packages. Normal procedure for estimating the efficiency is to device dummy waste packages and attach point sources with well-known activities to unfavourable positions in these packages. In accordance with this procedure, calibration factors can be derived in a radiological conservative way. Devising such test dummies is not always possible and the procedure is prone to generating large measurement uncertainties. In this publication, we propose a new method to derive calibration factors by means of the Los Alamos National Laboratory (LANL) simulation tool Monte Carlo N-Particle (MCNP) and a statistical-phenomenological model for the detector characterization. In a multi-step approach, first the detector response for a distribution of activity in a waste package is calculated and subsequently the detectors are mathematically characterized. Applying state of the art statistical and optimizing procedures, parameters for the detector response are derived in a self-consistent way. This also allows to rigorously propagate the uncertainties to the final calculated calibration factors according to the Guide to the Expression of Uncertainty in Measurement (GUM supplement 1). To validate the derived parameters for the detector characterization a minimally invasive experimental setup was devised and installed into the large clearance monitor. It consisted of an aluminum swivel arm which could position point sources to the relevant coordinates. The so collected measurement data not only allowed to investigate the precision of the calculated calibration factors, but also to probe the location of concentrated activity sources in the waste package. Furthermore, data on measurements with dummy waste packages were collected to test the reproducibility of well-known calibration factors. We present the software tool SIStec, which will provide an intuitive user-interface to generate and simulate waste package models and execute the above-mentioned method. Using SIStec, different scenarios for the distribution of activity in the waste package can be probed. This will also allow to optimize the clearance process on various levels. For example, measurement time for pre-measurements can be reduced in exchange for unfavourable calibration factors, which would still allow to meet the regulator limits for clearance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Precursor Analysis Report: Conti Ransomware Attack on the Health Service Executive of Ireland 2021

The Conti Ransomware Attack on the Health Service Executive (HSE) of Ireland 2021 Precursor Analysis Report leverages publicly available information about the attack and catalogs anomalous observables for each technique employed by the adversary. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The HSE provides public healthcare corporate services and operational services throughout Ireland, with critical functions including the acute national ambulance service, acute hospital service, and community healthcare service. On 14 May 2021, Conti ransomware encrypted 80 percent of the HSE’s Information Technology (IT) infrastructure across corporate, hospital, community, and electronic health record services. Conti is a ransomware-as-a-service operation that encrypts local files, uses double extortion against victims, and is facilitated by many intrusion tools. The attack forced the HSE to shut down its entire IT infrastructure to contain the ransomware, forcing employees to revert to pen and paper recordkeeping and leading to the cancellation of many appointments and procedures. The adversary also exfiltrated 700 GB of data, compromising the confidentiality of patients’ protected health information. Had the adversary targeted the COVID-19 cloud systems or operational technology assets, such as Internet of Medical Things medical devices or smart building management systems, the impact of the attack would almost certainly have been far more severe. Researchers and analysts identified 21 unique techniques (used in a sequence of 23 steps) likely utilized during the attack with a total of 1,185 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-one of the identified techniques used during the attack on the HSE were precursors to the triggering event. Analysis identified 1,086 observables associated with these precursor techniques, 850 of which were assessed to have an increased likelihood of being perceived in the 57 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗
DOE OSTI2014

Development of Automated Software Program for the Analysis of Alzheimer's Disease Scans: Evaluation of PET imaging with PBR-111 in HV and AD subjects

Study goal: A Phase 1 evaluation of the kinetics, clearance and cerebral distribution of one novel peripheral benzodiazepine receptors(PBR)positron emission tomography (PET) imaging agent, 18F-PBR-111 following intravenous administration in healthy volunteers and Alzheimer's disease (AD) patients. Short title: Evaluation of PET imaging with PBR-111 in HV and AD subjects Proof of Mechanism. Primary Objective: To evaluate the cerebral distribution of PBR-111 positron emission tomography (PET) for detection/exclusion of microglial activation in patients with Alzheimer's disease subjects compared to healthy volunteers. Secondary objectives: - To assess the dynamic uptake and washout of [18F]PBR-111, a potential imaging bio-marker for inflammatory changes in brain, using positron emission tomography in subjects with Alzheimer's disease (AD) and healthy volunteers (HV). - To perform blood metabolite characterization of [18F]PBR-111 in subjects with AD and HV to determine the nature of metabolites in assessment of [18F]-PBR-111 as a PET brain imaging agent. Name of radioactive drug substance: PBR-111 Dose(s): The applied PBR-111 radioactive dose will be up to 5.0 mCi, diluted in a maximum of 10 ml of saline. The radioligand will be administered as a slow intravenous bolus injection (i.e., 6 sec/ml) into a large vein (e.g., antecubital vein). Route of administration: Intravenous injection Duration of treatment: Single administration of a diagnostic agent Indication: PBR-111 positron emission tomography (PET) imaging has the potential to detect microglial activation. In the presence of PBR-111 uptake (representative of microglial activation), inflammation in the brain can be detected. Diagnosis and main criteria for inclusion: Study participants will be HVs and patients diagnosed with probable AD. HVs must be 18 years of age (at least four subjects 50 years of age) and have no evidence of cognitive impairment or other neurologic disease by medical history. The lack of cognitive impairment will also be based on a Clinical Dementia Rating (CDR) of 0. Patients with probable AD must be 50 years of age and must fulfill the National Institute of Neurological and Communicative Disorders and Stroke, Alzheimer's Disease and Related Disorders Association [NINCDS-ADRDA] criteria for probable AD. The CDR score must be 1.0 and 2.0 and have a modified Hachinski of 4. All HVs and all patients with probable AD must be able to comply with all study procedures. Study design: This is a Phase 1, open-label, single-center, non-randomized single dose study to assess the kinetics, clearance and cerebral distribution of PBR-111 PET imaging in detecting microglial activation in the brain in patients with probable AD compared to HVs. All aspects related to image acquisition, processing, and visual as well as quantitative evaluation will be developed, optimized, and validated (where required). Each subject will be required to visit the study center during the screening phase and on the PBR-111 PET imaging day (baseline). A telephone follow-up visit will be performed 7 days (± 3 days) after PBR-111 PET administration. At the screening visit, each subject (or caregiver in the case of AD subjects) will be asked to provide written informed consent or assent. During the screening phase (maximum duration of 60 days) subject medical, neurological, and surgical history, clinical assessments, and a neuro-psychiatric evaluation will be performed on all eligible subjects. Subjects will be allowed to leave the center after all evaluations have been completed. During this period an MRI of the brain will be performed during the screening period. If an MRI of the brain has been performed within six months of the imaging visit using the methods described in the protocol, and there has been no medically significant events in the interim, the previous MRI may be used. During the PBR-111 PET imaging day, all subjects will receive a single intravenous injection of PBR-111 and scanning will be performed over a 3.5 hour period. Each subject will have a telephone follow-up 7 days (± 3 days) thereafter to assess for adverse events. Methodology: - Assessments to provide clinical characterization of the AD subjects will be performed. - After administration of PBR-111, images will be generated with state-of-the-art PET imaging. Images will be assessed quantitatively for the presence of microglial activation by a nuclear physician blinded to clinical data. - Total radioactivity and estimation of the fraction of radioactivity associated to the un-metabolized tracer will be determined. In addition, the metabolite patterns of PBR-111 are determined in venous plasma and arterial samples based on high-performance liquid chromatography (HPLC) analyses. - Arterial sampling will be acquired in the initial two AD and two HV subjects and modeling will be assessed to determine if additional arterial sampling is necessary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Modeling the thermal deformation of TATB-based explosives. Part 1: Thermal expansion of “neat-pressed” polycrystalline TATB

We detail a modeling approach to simulate the anisotropic thermal expansion of polycrystalline (1,3,5-triamino-2,4,6-trinitrobenzene) TATB-based explosives that utilizes microstructural information including porosity, crystal aspect ratio, and processing-induced texture. This report, the first in a series, focuses on nonlinear thermal expansion of “neat-pressed” polycrystalline TATB specimens which do not contain any binder; additional complexities related to polymeric binder and irreversible ratcheting behavior are briefly discussed, however detailed investigation of these aspects are deferred to subsequent reports. In this work we have, for the first time, developed a mesoscale continuum model relating the thermal expansion of polycrystal TATB specimens to their microstructural characteristics. A self-consistent homogenization procedure is used to relate macroscopic thermoelastic response to the constitutive behavior of single-crystal TATB. The model includes a representation of grain aspect ratio, porosity, and crystallographic texture attributed to the consolidation process. A quantitative model is proposed to describe the evolution of preferred orientation of graphitic planes in TATB during consolidation and an algorithm constructed to develop a discrete representation of the associated orientation distribution function. Analytical and numerical solutions using this model are shown to produce textures consistent with previous measurements and characterization for isostatic and uniaxial “die-pressed” specimens. Predicted thermal strain versus temperature for textured specimens are shown to be in agreement with corresponding experimental measurements. Using the developed modeling approach, several simulations have been run to investigate the influence of microstructure on macroscopic thermal expansion behavior. Results from these simulations are used to identify qualitative trends. Implications of the identified trends are discussed in the context of thermal deformation of engineered components whose consolidation process is generally more complex than isostatic or die-pressed specimens. Finally, an envisioned application of the modeling approach to simulating thermal expansion of weapon systems and components is outlined along with necessary future work to introduce the effects of binder and ratcheting behavior. Key conclusions from this work include the following. Both porosity and grain aspect ratio have an influence on the thermal expansion of polycrystal TATB considering realistic material variability. Thepreferred orientation of the single crystal TATB [001] poles within a polycrystal gives rise to pronounced anisotropy of the macroscopic thermal expansion. The extent of this preferred orientation depends on the magnitude of deformation, and consequently, is expected to vary spatially throughout manufactured components much like porosity. The modeling approach presented here has utility toward bringing spatially variable microstructural features into macroscale system engineering modelsAbstract Not Provided

36 MATERIALS SCIENCE↗
DOE OSTI2022

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Mathematical Modelling of Gas–Liquid, Two-Phase Flows in a Ladle Shroud

Differential and macroscopic models of argon–steel flows in ladle shroud have been developed. In this, argon–steel, two-phase flow phenomena have been formulated via a transient, three dimensional, turbulent flow model, based on the volume of fluid (VOF) calculation procedure. While realizable k–ε turbulence model has been applied to map turbulence, commercial, CFD software ANSYS-Fluent™ (Version 18), has been applied to carry out numerical calculations. Predictions from the model have been directly assessed against experimental measurements across the range of shroud dimensions and volumetric flow rates typically practiced in the industry. It is demonstrated that the two-phase turbulent flow model captures the general features of gas–liquid flows in ladle shroud providing estimates of free jet length and threshold gas flow rates (required to halt air ingression) which are in agreement with corresponding experimental measurements. In the absence of differential solutions, a macroscopic model has been worked out through dimensional analysis embodying multiple non-linear regression. It is shown that dimensionless free jet length in bloom and slab casting shrouds can be estimated reasonably accurately from the following correlation (in SI unit), viz., ((L{sub jet})/(D{sub CN}))=2.8×10{sup −2}(((Q{sub G})/(Q{sub L}))){sup 1.14}(((gD{sub CN}{sup 5})/(Q{sub L}{sup 2}))){sup 0.8}(((σD{sub CN}{sup 3})/(ρ{sub L}Q{sub L}{sup 2}))){sup −0.9}(((D{sub sh})/(D{sub CN}))){sup 2.0}(((ρ{sub G})/(ρ{sub L}))){sup −0.30}in which, L{sub jet} is the free liquid jet length (m), Q{sub G} is the gas flow rate (m{sup 3}/s), Q{sub L} is the liquid flow rate (m{sup 3}/s), D{sub sh} is shroud diameter (m), D{sub CN} is the collector nozzle diameter (m), σ is the interfacial tension (N/m), and ρ{sub G} as well as ρ{sub L} are respectively density of gas and liquid (kg/m{sup 3}). It is demonstrated that the proposed correlation is consistent with the laws of physical modeling and leads to estimates that are in good agreement with predictions from the differential models, for both air-water as well as argon–steel systems. Numerical simulations as well as macroscopic modeling have indicated that thermo-physical properties of the gas–liquid system are important and exert some influences on the gas–liquid, two-phase, flow in ladle shrouds, albeit not to a large extent. Despite dissimilar thermo-physical properties, full scale water modeling appears to be sufficiently predictive and provides reasonable macroscopic descriptions of the two-phase flow phenomena in industrial ladle shroud systems.

42 ENGINEERING↗
DOE OSTI2020

Assessment of the Griffin Reactor Multiphysics Application Using the Empire Micro Reactor Design Concept

In late 2019, INL and ANL agreed to jointly develop the reactor physics code named Griffin based on the integration of the two code suites, MAMMOTH/Rattlesnake (INL) and MC2 - 3/PROTEUS (ANL). Griffin is being developed based on the MOOSE framework and MOOSE quality assurance procedures. This decision was made to be able to allow DOE-NE to efficiently invest funding to this area and to provide effective and timely support for existing and potential users; the latter includes industry and government organizations who are developing various types of advanced reactors in the near and long term. Since MAMMOTH/Rattlesnake has been developed based on the MOOSE framework, the INL/ANL Griffin development team agreed to build Griffin beginning with a merger of MAMMOTH and Rattlesnake into a single code and moving forward by implementing capabilities from the PROTEUS suite into Griffin. Moving forward, both ANL and INL efforts are equally invested in the Griffin project, with management support, to provide an advanced reactor multiphysics tool to assist in reactor design, optimization, and safety analysis. Much work remains in moving Griffin forward to migrate PROTEUS capabilities and to optimize performance to meet user needs. The main objective of this work is to assess the current status of Griffin capabilities in terms of performance and accuracy, to determine priorities for PROTEUS migration, and to identify capabilities and features to improve for supporting the code integration effort. For this assessment, the Empire micro reactor problem that was developed in the ARPA-E MEITNER program was selected as an advance reactor concept of interest to the technical community. The Empire reactor problem was expanded from its original incomplete specification to be a small heat-pipe-cooled micro reactor core with ~113 cm radius and 70 cm in height, composed of 18 fuel assemblies, 12 control drums, and beryllium radial and axial reflectors. In the current model, using 5 cm axial reflectors specified in the original Empire assembly model, more than 10% of neutrons leak axially and through the empty center safety hole, as well as through heat pipe channels in fuel assembly elements that extend through the top reflector region. Several calculation models of the core were defined for systematic assessment, including 2-D and 3-D fuel assemblies and whole cores with cylindrical boundaries. Cross sections were generated using Serpent 2, and meshes were produced using the Argonne mesh tool or the INL neutronics meshing tools combined with CUBIT. Cross sections and meshes were converted to the ISOXML and Exodus formats, respectively, so that Griffin and PROTEUS could use consistent data for solving the reactor problems. With the prepared cross sections and meshes, PROTEUS was run first to ensure that all input data were correctly generated and input options in terms of angle, mesh, and energy group were accurately determined. Comparisons against Serpent 2 solutions were made in terms of eigenvalue and pin power. The same calculations and comparisons were then conducted using Griffin. For the fuel assembly and whole core problems, the PROTEUS eigenvalues agreed well with reference Serpent 2 solutions within 100 and 30 pcm, respectively, and pin power differences relative to Serpent 2 were overall less than 2.2% and RMS 0.8% for the whole core models. This indicated that all input data were properly prepared. Using the same data, Griffin was run selecting the SAAF-CFEM SN solver with Legendre-Gaussian quadrature and NDA and DSA for acceleration. It was found that the SAAF-CFEM solver of Griffin required finer meshes to achieve eigenvalue and pin power solutions in good agreement with Serpent 2, consequently requiring more memory requirement and longer computation time. On the other hand, the SPH-Diffusion 2-D core calculations performed using Griffin were able to recover the exact eigenvalue from the reference Serpent 2 solutions, resulting in a pin-power distribution with an RMS of 0.6% and maximum absolute difference of less than 1.4%. The runtimes for SPH-Diffusion for the 2-D core were less than 3 minutes on 40 cores. During this evolution of this evaluation, many updates were made in Griffin by the Griffin development team of INL (focusing on software updates) and ANL (reviewing and supporting software updates) to complete this assessment. Observations from the code assessment are presented in the conclusion section of this report, followed by a discussion of recommendations for future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences.

14 SOLAR ENERGY↗