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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Slow dynamics in a single bead with mechanical conditioning and transient heating

The contact stiffness of an aluminum bead confined between two slabs diminishes upon mechanical conditioning, and then recovers like log(t) after the conditioning ceases. Here that structure is evaluated for its response to transient heating and cooling, with and without accompanying conditioning vibrations. It is found that, under heating or cooling alone, stiffness changes are mostly consistent with temperature dependent material moduli; there is little or no slow dynamics. Hybrid tests in which vibration conditioning is followed by heating or cooling lead to recoveries that begin like log(t) and then become more complex. On subtracting the known response to heating or cooling alone we discern the influence of higher or lower temperatures on slow dynamic recovery from vibrations. It is found that heating accelerates the initial log(t) recovery, but by an amount more than predicted by an Arrhenius model of thermally activated barrier penetrations. Furthermore, transient cooling has no discernable effect, in contrast to the Arrhenius prediction that it slows recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rodeo Algorithm for Quantum Computing

We present a stochastic quantum computing algorithm that can prepare any eigenvector of a quantum Hamiltonian within a selected energy interval $\ [E-\epsilon, E+\epsilon]$. In order to reduce the spectral weight of all other eigenvectors by a suppression factor δ, the required computational effort scales as $\ O[|\log \delta|/(p \epsilon)]$, where p s the squared overlap of the initial state with the target eigenvector. The method, which we call the rodeo algorithm, uses auxiliary qubits to control the time evolution of the Hamiltonian minus some tunable parameter E . In this manner, we converge to the target eigenvector with exponential accuracy in the number of measurements. In addition to preparing eigenvectors, the method can also compute the full spectrum of the Hamiltonian. We illustrate the performance with several examples. For energy eigenvalue determination with error $\epsilon$, the computational scaling is $\ O[(\log \epsilon)^2/(p \epsilon)]$. For eigenstate preparation, the computational scaling is $\ O(\log \Delta/p)$, where $\Delta$ is the magnitude of the orthogonal component of the residual vector. The speed for eigenstate preparation is exponentially faster than that for phase estimation or adiabatic evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗
DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗
DOE OSTI2019

Combining Tensor Decompositions and Graph Analytics to Provide Cyber Situational Awareness at HPC Scale

This paper describes MADHAT (Multidimensional Anomaly Detection fusing HPC, Analytics, and Tensors), an integrated workflow that demonstrates the applicability of HPC resources to the problem of maintaining cyber situational awareness. MADHAT combines two high-performance packages: ENSIGN for large-scale sparse tensor decompositions and HAGGLE for graph analytics. Tensor decompositions isolate coherent patterns of network behavior in ways that common clustering methods based on distance metrics cannot. Parallelized graph analysis then uses directed queries on a representation that combines the elements of identified patterns with other available information (such as additional log fields, domain knowledge, network topology, whitelists and blacklists, prior feedback, and published alerts) to confirm or reject a threat hypothesis, collect context, and raise alerts. MADHAT was developed using the collaborative HPC Architecture for Cyber Situational Awareness (HACSAW) research environment and evaluated on structured network sensor logs collected from Defense Research and Engineering Network (DREN) sites using HPC resources at the U.S. Army Engineer Research and Development Center DoD Supercomputing Resource Center (ERDC DSRC). To date, MADHAT has analyzed logs with over 650 million entries.

Cyber security, Tensor decomposition, graph analyt↗
DOE OSTI2020

Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer

Designing dependable supercomputers begins with an understanding of errors in real-world, large-scale systems. The Titan supercomputer at Oak Ridge National Laboratory provides a unique opportunity to investigate errors when an actual system is actively used by multiple concurrent users and workloads from diverse domains at varying scales. This study presents a thorough analysis of 6, 908, 497 hardware errors from 18, 688 compute nodes of Titan for 312, 215 user jobs over a 3-year time period. Through careful joining of two system logs – the Machine Check Architecture (MCA) log and the job scheduler log – we show the correlated pattern of hardware errors for each job and user, in addition to individual descriptive statistics of errors, jobs, and users. Since the majority of hardware errors are memory errors, this study also shows the importance of error correcting in memory systems.

Lim, Seung-Hwan↗
DOE OSTI2016

PATHA: Performance Analysis Tool for HPC Applications

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Salmonella Inactivation During Extrusion of an Oat Flour Model Food

Abstract Little research exists on Salmonella inactivation during extrusion processing, yet many outbreaks associated with low water activity foods since 2006 were linked to extruded foods. The aim of this research was to study Salmonella inactivation during extrusion of a model cereal product. Oat flour was inoculated with Salmonella enterica serovar Agona, an outbreak strain isolated from puffed cereals, and processed using a single‐screw extruder at a feed rate of 75 kg/h and a screw speed of 500 rpm. Extrudate samples were collected from the barrel outlet in sterile bags and immediately cooled in an ice–water bath. Populations were determined using standard plate count methods or a modified most probable number when populations were low. Reductions in population were determined and analyzed using a general linear model. The regression model obtained for the response surface tested was Log ( N R / N O ) = 20.50 + 0.82 T − 141.16a w – 0.0039 T 2 + 87.91 a w 2 ( R 2 = 0.69). The model showed significant ( p < 0.05) linear and quadratic effects of a w and temperature and enabled an assessment of critical control parameters. Reductions of 0.67 ± 0.14 to 7.34 ± 0.02 log CFU/g were observed over ranges of a w (0.72 to 0.96) and temperature (65 to 100 °C) tested. Processing conditions above 82 °C and 0.89 a w achieved on average greater than a 5‐log reduction of Salmonella . Results indicate that extrusion is an effective means for reducing Salmonella as most processes commonly employed to produce cereals and other low water activity foods exceed these parameters. Thus, contamination of an extruded food product would most likely occur postprocessing as a result of environmental contamination or through the addition of coatings and flavorings.

Anderson, Nathan M.↗
DOE OSTI2015

Biofilm Detection in a Model Well-Bore Environment Using Low-Field NMR

This research addresses the challenges of the lack of non-invasive methods and poor spatiotemporal resolution associated with monitoring biogeochemical activity central to bioremediation of subsurface contaminants. Remediation efforts often include growth of biofilm to contain or degrade chemical contaminants, such as nitrates, hydrocarbons, heavy metals, and some chlorinated solvents. Previous research indicates that nuclear magnetic resonance (NMR) is sensitive to the biogeochemical processes of biofilm accumulation. The current research focuses on developing methods to use low-cost NMR technology to support in situ monitoring of biofilm growth and geochemical remediation processes in the subsurface. Biofilm was grown in a lab-scale radial flow bioreactor designed to model the near wellbore subsurface environment. The Vista Clara Javelin NMR logging device, a slim down-the-borehole probe, collected NMR measurements over the course of eight days while biofilm was cultivated in the sand-packed reactor. Measured NMR mean log T 2 relaxation times decreased from approximately 710 to 389 ms, indicating that the pore environment and bulk fluid properties were changing due to biofilm growth. Destructive sampling employing drop plate microbial population analysis and scanning electron and stereoscopic microscopy confirmed biofilm formation. Here our findings demonstrate that the NMR logging tool can detect small to moderate changes in T 2 distribution associated with environmentally relevant quantities of biofilm in quartz sand.

58 GEOSCIENCES↗
DOE OSTI2023

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗
DOE OSTI2025

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc↗
DOE OSTI2014

The use of strain tensor to estimate thoracic tumors deformation

Purpose: Respiration-induced kinematics of thoracic tumors suggests a simple analogy with elasticity, where a strain tensor is used to characterize the volume of interests. The application of the biomechanical framework allows for the objective determination of tumor characteristics. Methods: Four-dimensional computed tomography provides the snapshots of the patient's anatomy at the end of inspiration and expiration. Image registration was used to obtain the displacement vector fields and deformation fields, which allows one for the determination of the strain tensor. Its departure from the identity matrix gauges the departure of the medium from rigidity. The tensorial characteristic of each GTV voxel was determined and averaged. To this end, the standard Euclidean matrix norm as well as the Log-Euclidean norm were employed. Tensorial anisotropy was gauged with the fractional anisotropy measure which is based on the normalized variance of the tensors eigenvalues. Anisotropy was also evaluated with the geodesic distance in the Log-Euclidean framework of a given strain tensor to its closest isotropic counterpart. Results: The averaged strain tensor was determined for each of the 15 retrospectively analyzed thoracic GTVs. The amplitude of GTV motion varied from 0.64 to 4.21 with the average of 1.20 cm. The GTV size ranged from 5.16 to 149.99 cc with the average of 43.19 cc. The tensorial analysis shows that deformation is inconsiderable and that the tensorial anisotropy is small. The Log-Euclidean distance of averaged strain tensors from the identity matrix ranged from 0.06 to 0.31 with the average of 0.19. The Frobenius distance from the identity matrix is similar and ranged from 0.06 to 0.35 with the average of 0.21. Their fractional anisotropy ranged from 0.02 to 0.12 with the average of 0.07. Their geodesic anisotropy ranged from 0.03 to 0.16 with the average of 0.09. These values also indicate insignificant deformation. Conclusions: The tensorial framework allows for direct measurements of tissue deformation. It goes beyond the evaluation of deformation via comparison of shapes. It is an independent and objective determination of tissue properties. This methodology can be used to determine possible changes in lung properties due to radiation therapy and possible toxicities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-A-9A-10: Prostate SBRT Delivery with Flattening-Filter-Free Mode: Benefit and Accuracy

Purpose: Flattening-filter-free (FFF) beam mode offered on TrueBeam™ linac enables delivering IMRT at 2400 MU/min dose rate. This study investigates the benefit and delivery accuracy of using high dose rate in the context of prostate SBRT. Methods: 8 prostate SBRT patients were retrospectively studied. In 5 cases treated with 600-MU/min dose rate, continuous prostate motion data acquired during radiation-beam-on was used to analyze motion range. In addition, the initial 1/3 of prostate motion trajectories during each radiation-beam-on was separated to simulate motion range if 2400-MU/min were used. To analyze delivery accuracy in FFF mode, MLC trajectory log files from an additional 3 cases treated at 2400-MU/min were acquired. These log files record MLC expected and actual positions every 20ms, and therefore can be used to reveal delivery accuracy. Results: (1) Benefit. On average treatment at 600-MU/min takes 30s per beam; whereas 2400-MU/min requires only 11s. When shortening delivery time to ~1/3, the prostate motion range was significantly smaller (p<0.001). Largest motion reduction occurred in Sup-Inf direction, from [−3.3mm, 2.1mm] to [−1.7mm, 1.7mm], followed by reduction from [−2.1mm, 2.4mm] to [−1.0mm, 2.4mm] in Ant-Pos direction. No change observed in LR direction [−0.8mm, 0.6mm]. The combined motion amplitude (vector norm) confirms that average motion and ranges are significantly smaller when beam-on was limited to the 1st 1/3 of actual delivery time. (2) Accuracy. Trajectory log file analysis showed excellent delivery accuracy with at 2400 MU/min. Most leaf deviations during beam-on were within 0.07mm (99-percentile). Maximum leaf-opening deviations during each beam-on were all under 0.1mm for all leaves. Dose-rate was maintained at 2400-MU/min during beam-on without dipping. Conclusion: Delivery prostate SBRT with 2400 MU/min is both beneficial and accurate. High dose rates significantly reduced both treatment time and intra-beam prostate motion range. Excellent delivery accuracy was confirmed with very small leaf motion deviation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

SU-E-I-58: Experiences in Setting Up An Online Fluoroscopy Tracking System in a Large Healthcare System

Purpose: Transitioning from a paper based to an online system for tracking fluoroscopic case information required by state regulation and to conform to NCRP patient dose tracking suggestions. Methods: State regulations require documentation of operator, equipment, and some metric of tube output for fluoroscopy exams. This information was previously collected in paper logs, which was cumbersome and inefficient for the large number of fluoroscopic units across multiple locations within the system. The “tech notes” feature within Siemens’ Syngo workflow RIS was utilized to create an entry form for technologists to input case information, which was sent to a third party vendor for archiving and display though an online web based portal. Results: Over 55k cases were logged in the first year of implementation, with approximately 6,500 cases per month once fully online. A system was built for area managers to oversee and correct data, which has increased the accuracy of inputted values. A high-dose report was built to automatically send notifications when patients exceed trigger levels. In addition to meeting regulatory requirements, the new system allows for larger scale QC in fluoroscopic cases by allowing comparison of data from specific procedures, locations, equipment, and operators so that instances that fall outside of reference levels can be identified for further evaluation. The system has also drastically improved identification of operators without documented equipment specific training. Conclusion: The transition to online fluoroscopy logs has improved efficiency in meeting state regulatory requirements as well as allowed for identification of particular procedures, equipment, and operators in need of additional attention in order to optimize patient and personnel doses, while high dose alerts improve patient care and follow up. Future efforts are focused on incorporating case information from outside of radiology, as well as on automating processes for increased efficiencies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-266: Development of Evaluation System of Optimal Synchrotron Controlling Parameter for Spot Scanning Proton Therapy with Multiple Gate Irradiations in One Operation Cycle

Purpose: We have developed a gated spot scanning proton beam therapy system with real-time tumor-tracking. This system has the ability of multiple-gated irradiation in a single synchrotron operation cycle controlling the wait-time for consecutive gate signals during a flat-top phase so that the decrease in irradiation efficiency induced by irregular variation of gate signal is reduced. Our previous studies have shown that a 200 ms wait-time is appropriate to increase the average irradiation efficiency, but the optimal wait-time can vary patient by patient and day by day. In this research, we have developed an evaluation system of the optimal wait-time in each irradiation based on the log data of the real-time-image gated proton beam therapy (RGPT) system. Methods: The developed system consists of logger for operation of RGPT system and software for evaluation of optimal wait-time. The logger records timing of gate on/off, timing and the dose of delivered beam spots, beam energy and timing of X-ray irradiation. The evaluation software calculates irradiation time in the case of different wait-time by simulating the multiple-gated irradiation operation using several timing information. Actual data preserved in the log data are used for gate on and off time, spot irradiation time, and time moving to the next spot. Design values are used for the acceleration and deceleration times. We applied this system to a patient treated with the RGPT system. Results: The evaluation system found the optimal wait-time of 390 ms that reduced the irradiation time by about 10 %. The irradiation time with actual wait-time used in treatment was reproduced with accuracy of 0.2 ms. Conclusion: For spot scanning proton therapy system with multiple-gated irradiation in one synchrotron operation cycle, an evaluation system of the optimal wait-time in each irradiation based on log data has been developed. Funding Support: Japan Society for the Promotion of Science (JSPS) through the FIRST Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-664: Radiobiological Modeling of Prophylactic Cranial Irradiation in Mice

Purpose: Prophylactic cranial irradiation (PCI) is a clinical technique used to reduce the incidence of brain metastasis and improve overall survival in select patients with ALL and SCLC, and we have shown the potential of PCI in select breast cancer patients through a mouse model (manuscript in preparation). We developed a computational model using our experimental results to demonstrate the advantage of treating brain micro-metastases early. Methods: MATLAB was used to develop the computational model of brain metastasis and PCI in mice. The number of metastases per mouse and the volume of metastases from four- and eight-week endpoints were fit to normal and log-normal distributions, respectively. Model input parameters were optimized so that model output would match the experimental number of metastases per mouse. A limiting dilution assay was performed to validate the model. The effect of radiation at different time points was computationally evaluated through the endpoints of incidence, number of metastases, and tumor burden. Results: The correlation between experimental number of metastases per mouse and the Gaussian fit was 87% and 66% at the two endpoints. The experimental volumes and the log-normal fit had correlations of 99% and 97%. In the optimized model, the correlation between number of metastases per mouse and the Gaussian fit was 96% and 98%. The log-normal volume fit and the model agree 100%. The model was validated by a limiting dilution assay, where the correlation was 100%. The model demonstrates that cells are very sensitive to radiation at early time points, and delaying treatment introduces a threshold dose at which point the incidence and number of metastases decline. Conclusion: We have developed a computational model of brain metastasis and PCI in mice that is highly correlated to our experimental data. The model shows that early treatment of subclinical disease is highly advantageous.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Development of a video image-based QA system for the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system

Purpose: To develop and evaluate a new video image-based QA system, including in-house software, that can display a tracking state visually and quantify the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system. Methods: Sixteen trajectories in six patients with pulmonary cancer were obtained with the ExacTrac in the Vero4DRT system. Motion data in the cranio–caudal direction (Y direction) were used as the input for a programmable motion table (Quasar). A target phantom was placed on the motion table, which was placed on the 2D ionization chamber array (MatriXX). Then, the 4D modeling procedure was performed on the target phantom during a reproduction of the patient’s tumor motion. A substitute target with the patient’s tumor motion was irradiated with 6-MV x-rays under the surrogate infrared system. The 2D dose images obtained from the MatriXX (33 frames/s; 40 s) were exported to in-house video-image analyzing software. The absolute differences in the Y direction between the center of the exposed target and the center of the exposed field were calculated. Positional errors were observed. The authors’ QA results were compared to 4D modeling function errors and gimbal motion errors obtained from log analyses in the ExacTrac to verify the accuracy of their QA system. The patients’ tumor motions were evaluated in the wave forms, and the peak-to-peak distances were also measured to verify their reproducibility. Results: Thirteen of sixteen trajectories (81.3%) were successfully reproduced with Quasar. The peak-to-peak distances ranged from 2.7 to 29.0 mm. Three trajectories (18.7%) were not successfully reproduced due to the limited motions of the Quasar. Thus, 13 of 16 trajectories were summarized. The mean number of video images used for analysis was 1156. The positional errors (absolute mean difference + 2 standard deviation) ranged from 0.54 to 1.55 mm. The error values differed by less than 1 mm from 4D modeling function errors and gimbal motion errors in the ExacTrac log analyses (n = 13). Conclusions: The newly developed video image-based QA system, including in-house software, can analyze more than a thousand images (33 frames/s). Positional errors are approximately equivalent to those in ExacTrac log analyses. This system is useful for the visual illustration of the progress of the tracking state and for the quantification of positional accuracy during dynamic tumor tracking irradiation in the Vero4DRT system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRB-02: An Open-Source Software Analysis Library for Linear Accelerator Quality Assurance

Purpose: Routine linac quality assurance (QA) tests have become complex enough to require automation of most test analyses. A new data analysis software library was built that allows physicists to automate routine linear accelerator quality assurance tests. The package is open source, code tested, and benchmarked. Methods: Images and data were generated on a TrueBeam linac for the following routine QA tests: VMAT, starshot, CBCT, machine logs, Winston Lutz, and picket fence. The analysis library was built using the general programming language Python. Each test was analyzed with the library algorithms and compared to manual measurements taken at the time of acquisition. Results: VMAT QA results agreed within 0.1% between the library and manual measurements. Machine logs (dynalogs & trajectory logs) were successfully parsed; mechanical axis positions were verified for accuracy and MLC fluence agreed well with EPID measurements. CBCT QA measurements were within 10 HU and 0.2mm where applicable. Winston Lutz isocenter size measurements were within 0.2mm of TrueBeam’s Machine Performance Check. Starshot analysis was within 0.2mm of the Winston Lutz results for the same conditions. Picket fence images with and without a known error showed that the library was capable of detecting MLC offsets within 0.02mm. Conclusion: A new routine QA software library has been benchmarked and is available for use by the community. The library is open-source and extensible for use in larger systems.

43 PARTICLE ACCELERATORS↗