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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-T-142: Automatic Linac Log File: Analysis and Reporting

Purpose: End to end QA for IMRT/VMAT is time consuming. Automated linac log file analysis and recalculation of daily recorded fluence, and hence dose, distribution bring this closer. Methods: Matlab (R2014b, Mathworks) software was written to read in and analyse IMRT/VMAT trajectory log files (TrueBeam 1.5, Varian Medical Systems) overnight, and are archived on a backed-up network drive (figure). A summary report (PDF) is sent by email to the duty linac physicist. A structured summary report (PDF) for each patient is automatically updated for embedding into the R&V system (Mosaiq 2.5, Elekta AG). The report contains cross-referenced hyperlinks to ease navigation between treatment fractions. Gamma analysis can be performed on planned (DICOM RTPlan) and treated (trajectory log) fluence distributions. Trajectory log files can be converted into RTPlan files for dose distribution calculation (Eclipse, AAA10.0.28, VMS). Results: All leaf positions are within +/−0.10mm: 57% within +/−0.01mm; 89% within 0.05mm. Mean leaf position deviation is 0.02mm. Gantry angle variations lie in the range −0.1 to 0.3 degrees, mean 0.04 degrees. Fluence verification shows excellent agreement between planned and treated fluence. Agreement between planned and treated dose distribution, the derived from log files, is very good. Conclusion: Automated log file analysis is a valuable tool for the busy physicist, enabling potential treated fluence distribution errors to be quickly identified. In the near future we will correlate trajectory log analysis with routine IMRT/VMAT QA analysis. This has the potential to reduce, but not eliminate, the QA workload.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-184: Clinical VMAT QA Practice Using LINAC Delivery Log Files

Purpose: To evaluate the accuracy of volumetric modulated arc therapy (VMAT) treatment delivery dose clouds by comparing linac log data to doses measured using an ionization chamber and film. Methods: A commercial IMRT quality assurance (QA) process utilizing a DICOM-RT framework was tested for clinical practice using 30 prostate and 30 head and neck VMAT plans. Delivered 3D VMAT dose distributions were independently checked using a PinPoint ionization chamber and radiographic film in a solid water phantom. DICOM RT coordinates were used to extract the corresponding point and planar doses from 3D log file dose distributions. Point doses were evaluated by computing the percent error between log file and chamber measured values. A planar dose evaluation was performed for each plan using a 2D gamma analysis with 3% global dose difference and 3 mm isodose point distance criteria. The same analysis was performed to compare treatment planning system (TPS) doses to measured values to establish a baseline assessment of agreement. Results: The mean percent error between log file and ionization chamber dose was 1.0%±2.1% for prostate VMAT plans and −0.2%±1.4% for head and neck plans. The corresponding TPS calculated and measured ionization chamber values agree within 1.7%±1.6%. The average 2D gamma passing rates for the log file comparison to film are 98.8%±1.0% and 96.2%±4.2% for the prostate and head and neck plans, respectively. The corresponding passing rates for the TPS comparison to film are 99.4%±0.5% and 93.9%±5.1%. Overall, the point dose and film data indicate that log file determined doses are in excellent agreement with measured values. Conclusion: Clinical VMAT QA practice using LINAC treatment log files is a fast and reliable method for patient-specific plan evaluation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A clinically observed discrepancy between image-based and log-based MLC positions

Purpose: To present a clinical case in which real-time intratreatment imaging identified an multileaf collimator (MLC) leaf to be consistently deviating from its programmed and logged position by >1 mm. Methods: An EPID-based exit-fluence dosimetry system designed to prevent gross delivery errors was used to capture cine during treatment images. The author serendipitously visually identified a suspected MLC leaf displacement that was not otherwise detected. The leaf position as recorded on the EPID images was measured and log-files were analyzed for the treatment in question, the prior day’s treatment, and for daily MLC test patterns acquired on those treatment days. Additional standard test patterns were used to quantify the leaf position. Results: Whereas the log-file reported no difference between planned and recorded positions, image-based measurements showed the leaf to be 1.3 ± 0.1 mm medial from the planned position. This offset was confirmed with the test pattern irradiations. Conclusions: It has been clinically observed that log-file derived leaf positions can differ from their actual position by >1 mm, and therefore cannot be considered to be the actual leaf positions. This cautions the use of log-based methods for MLC or patient quality assurance without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trust log-file records. Intratreatment EPID imaging provides a method to capture departures from MLC planned positions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-172: A Method for Log File QA On An IBA Proteus System for Patient Specific Spot Scanning Quality Assurance

Purpose: The use of log files to perform patient specific quality assurance for both protons and IMRT has been established. Here, we extend that approach to a proprietary log file format and compare our results to measurements in phantom. Our goal was to generate a system that would permit gross errors to be found within 3 fractions until direct measurements. This approach could eventually replace direct measurements. Methods: Spot scanning protons pass through multi-wire ionization chambers which provide information about the charge, location, and size of each delivered spot. We have generated a program that calculates the dose in phantom from these log files and compares the measurements with the plan. The program has 3 different spot shape models: single Gaussian, double Gaussian and the ASTROID model. The program was benchmarked across different treatment sites for 23 patients and 74 fields. Results: The dose calculated from the log files were compared to those generate by the treatment planning system (Raystation). While the dual Gaussian model often gave better agreement, overall, the ASTROID model gave the most consistent results. Using a 5%–3 mm gamma with a 90% passing criteria and excluding doses below 20% of prescription all patient samples passed. However, the degree of agreement of the log file approach was slightly worse than that of the chamber array measurement approach. Operationally, this implies that if the beam passes the log file model, it should pass direct measurement. Conclusion: We have established and benchmarked a model for log file QA in an IBA proteus plus system. The choice of optimal spot model for a given class of patients may be affected by factors such as site, field size, and range shifter and will be investigated further.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Finite element simulations of viscoelastic flow of blade coating using the log-conformation tensor

Previous studies have demonstrated the benefits of the log-conformation formulation to model viscoelastic fluids; it increases stability at high Weissenberg numbers and ensures that the conformation tensor remains positive-definite. Many studies have applied the log-conformation tensor formulation to benchmark cases; however, relatively few studies investigate using the formulation on more complex flows. In this paper, we extend the log-conformation formulation to the manufacturing-relevant flow of blade coating. We first verify the log-conformation formulation on the benchmark problem of flow past a cylinder using the finite element method, and then apply it to the blade-coating process, in which a viscoelastic fluid entrained by a moving substrate passes under a blade at a constant web speed. We investigate various rheological effects and the resulting film thickness for the blade-coating problem, and compare the results from the log-conformation formulation to those of the original stress formulation. To this end, we show that the log-conformation formulation agrees well with other established methods, and also increases the maximum achievable web speed in the blade-coating problem.

36 MATERIALS SCIENCE↗
NASA NTRS2023

Oregon Coast Range Ecological Conservation: Mapping Recent Logging Within Drinking Watersheds of Oregon’s Coastal Range to Support Future Resource Management Policies

Logging operations are widespread across the Oregon Coast Range and conventional logging practices pose a risk of contamination to surface water quality. The NASA DEVELOP Oregon Coast Ecological Conservation team partnered with nonprofit Oregon Wild to quantify the extent of clearcutting and commercial thinning in 80 Coast Range drinking watersheds between 2000 and 2022. This project used all available Landsat data from 1997 through June 2023 in Google Earth Engine. Sensors used include Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Landsat 9 Operational Land Imager-2. The Continuous Change Detection and Classification (CCDC) algorithm was used with Landsat observations to identify clearcutting patches. Percent change in summer median Landsat Normalized Difference Vegetation Index (NDVI) images were used to identify areas of forest disturbance including commercial thinning. The team concluded that logging, including both clearcutting and commercial thinning, impacted 31% of forested area in drinking watersheds and the intensity of logging remained consistent from year to year. Clearcutting occurred primarily on private land while commercial thinning occurred primarily on state and federal lands. This study showed that CCDC effectively identifies clearcutting, and percent change in NDVI successfully identifies disturbances including commercial thinning. Key constraints included the lack of field validation data and the inability to attribute disturbances to logging with certainty. Ultimately, this study identified the drinking watersheds and communities most likely to be impacted by logging activity. These results can inform legislation aimed at balancing the commercial and environmental benefits of forestlands.

Logging↗
DOE OSTI2026

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗
DOE OSTI2026

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗
NASA NTRS2020

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗
DOE OSTI2026

Database-Agnostic Log Analysis and Monitoring Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, US, IL; Fermilab]↗
DOE OSTI2019

EGS Collab Experiment 2: Core Logs

Core logs and photos from the EGS Collab project Experiment 2 for the Top Vertical well (TV4100) and the Top Horizontal well (TV 4100) on the 4100 Level of SURF (the Sanford Underground Research Facility). The core logs are stored in a single PDF file with 5-ft run intervals. In the monitoring well IDs, "O" indicates that the well is orthogonal to the anticipated fracture plane, "T" refers to top, and "H" refers to horizontal. A core log CT scan for TV4100 and a layout image of the 4100 wells are included as well. Logs include: experiment number; borehole ID; depth interval; run number; final packed core box number; scribe line (yes/no; red-on-right convention); logging dates; logger initials; as well as sketches of core foliation, folding, and fracturing with additional details and notes on other features of interest. Shift reports include: date, location, personnel, summary of site activity, and field notes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Correction of steel casing effect for density log using numerical and experimental methods in the slim borehole

Density log is widely applied for a variety of fields such as the petroleum exploration, mineral exploration, and geotechnical survey. The logging condition of density log is normally open holes but there are frequently cased boreholes. The primary calibration curve by slim hole logging manufacturer is normally the calibration curves for the variation of borehole diameter. In this study, we have performed the correction of steel casing effects using numerical and experimental methods. We have performed numerical modeling using the Monte Carlo N-Particle (MCNP) code based on Monte Carlo method, and field experimental method from open and cased hole log. In this study, we used the FDGS (Formation Density Gamma Sonde) for slim borehole with a 100 mCi 137Cs source, three inch borehole and steel casing. The casing effect between numerical and experimental method is well matched.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Log-periodic quantum magneto-oscillations and discrete-scale invariance in topological material HfTe 5

Discrete-scale invariance (DSI) is a phenomenon featuring intriguing log-periodicity that can be rarely observed in quantum systems. Here, we report the log-periodic quantum oscillations in the longitudinal magnetoresistivity ( ρ xx ) and the Hall traces ( ρ yx ) of HfTe 5 crystals, which reveal the DSI in the transport-coefficients matrix. The oscillations in ρ xx and ρ yx show the consistent log B -periodicity with a phase shift. The finding of the log B oscillations in the Hall resistance supports the physical mechanism as a general quantum effect originating from the resonant scattering. Combined with theoretical simulations, we further clarify the origin of the log-periodic oscillations and the DSI in the topological materials. This work evidences the universality of the DSI in the Dirac materials and provides indispensable information for a full understanding of this novel phenomenon.

magnetoresistance↗
NASA NTRS2012

Requirements-Driven Log Analysis Extended Abstract

Imagine that you are tasked to help a project improve their testing effort. In a realistic scenario it will quickly become clear, that having an impact is diffcult. First of all, it will likely be a challenge to suggest an alternative approach which is significantly more automated and/or more effective than current practice. The reality is that an average software system has a complex input/output behavior. An automated testing approach will have to auto-generate test cases, each being a pair (i; o) consisting of a test input i and an oracle o. The test input i has to be somewhat meaningful, and the oracle o can be very complicated to compute. Second, even in case where some testing technology has been developed that might improve current practice, it is then likely difficult to completely change the current behavior of the testing team unless the technique is obviously superior and does everything already done by existing technology. So is there an easier way to incorporate formal methods-based approaches than the full edged test revolution? Fortunately the answer is affirmative. A relatively simple approach is to benefit from possibly already existing logging infrastructure, which after all is part of most systems put in production. A log is a sequence of events, generated by special log recording statements, most often manually inserted in the code by the programmers. An event can be considered as a data record: a mapping from field names to values. We can analyze such a log using formal methods, for example checking it against a formal specification. This separates running the system for analyzing its behavior. It is not meant as an alternative to testing since it does not address the important in- put generation problem. However, it offers a solution which testing teams might accept since it has low impact on the existing process. A single person might be assigned to perform such log analysis, compared to the entire testing team changing behavior.

log analysis↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Coulomb log for conductivity of dense plasmas

The Coulomb log (log Λ) approximation is widely used to approximate electron transport coefficients in dense plasmas. It is a classical approximation to the momentum transport cross section. Here, the accuracy of this approximation for electrical conductivity in dense plasmas is assessed by comparing to fully quantum mechanical calculations for realistic scattering potentials. It is found that the classical approximation is accurate to ±10% when log Λ > 3, irrespective of the plasma species. The thermodynamic regime (density and temperature) for which log Λ > 3 corresponds to does, however, strongly depend on the material. For increasing Z, log Λ is greater than 3 for increasingly high temperatures and lower densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

SU-E-T-473: A Patient-Specific QC Paradigm Based On Trajectory Log Files and DICOM Plan Files

Purpose: To evaluate a remote QC tool for monitoring treatment machine parameters and treatment workflow. Methods: The Varian TrueBeamTM linear accelerator is a digital machine that records machine axis parameters and MLC leaf positions as a function of delivered monitor unit or control point. This information is saved to a binary trajectory log file for every treatment or imaging field in the patient treatment session. A MATLAB analysis routine was developed to parse the trajectory log files for a given patient, compare the expected versus actual machine and MLC positions as well as perform a cross-comparison with the DICOM-RT plan file exported from the treatment planning system. The parsing routine sorts the trajectory log files based on the time and date stamp and generates a sequential report file listing treatment parameters and provides a match relative to the DICOM-RT plan file. Results: The trajectory log parsing-routine was compared against a standard record and verify listing for patients undergoing initial IMRT dosimetry verification and weekly and final chart QC. The complete treatment course was independently verified for 10 patients of varying treatment site and a total of 1267 treatment fields were evaluated including pre-treatment imaging fields where applicable. In the context of IMRT plan verification, eight prostate SBRT plans with 4-arcs per plan were evaluated based on expected versus actual machine axis parameters. The average value for the maximum RMS MLC error was 0.067±0.001mm and 0.066±0.002mm for leaf bank A and B respectively. Conclusion: A real-time QC analysis program was tested using trajectory log files and DICOM-RT plan files. The parsing routine is efficient and able to evaluate all relevant machine axis parameters during a patient treatment course including MLC leaf positions and table positions at time of image acquisition and during treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Advancing subsurface analysis: Integrating computer vision and deep learning for the near real-time interpretation of borehole image logs in the Illinois Basin-Decatur Project

The accurate quantification and mapping of subsurface natural fracture systems using borehole imaging logs are critical for the success of CO 2 sequestration in geologic formations, optimization of engineered geothermal systems, and hydrocarbon production enhancement. However, traditional interpretation processes suffer from time-consuming procedures and human bias. To address these challenges and expedite fracture analysis, we investigated the application of integrated computer vision and DL workflows to automate image log analysis. Specifically, the design of our workflow was crafted to swiftly detect fractures and baffles by using actual electrical resistivity of borehole wall from microresistivity imaging device alongside their binary representation. This novel approach significantly reduces computational time while providing invaluable insights. By incorporating conventional logging and microseismic data, we present a regional subsurface natural fracture mapping technique. Through the minimization of human bias in image log analysis, our automated workflow achieves reduced fracture interpretation time and costs while ensuring robust and reproducible results. We demonstrated the efficacy of our approach by applying the workflow to the Illinois Basin-Decatur Project site. The automated workflow successfully identified major fractured zones, multiple baffles, and an interbedded layer with a high resolution of 0.01 ft or 0.12 in. (0.3 cm) and can be upscaled to any desired resolution. Validation through microseismic and image log interpretations allows for accurate and near-real-time mapping of fractures and baffles, significantly enhancing CO 2 pressure forecasting and postinjection site care. Our approach stands out due to its robustness, consistency, and reduced computational cost compared with alternative feature extraction technologies. It presents exciting possibilities for advancing CO 2 sequestration and engineered geothermal efforts by offering comprehensive and efficient fracture mapping solutions. This technology can contribute significantly to the optimization of CO 2 sequestration projects, facilitating sustainable environmental practices, and combating climate change.

Geochemistry & Geophysics↗