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

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

MO-G-304-01: FEATURED PRESENTATION: Expanding the Knowledge Base for Data-Driven Treatment Planning: Incorporating Patient Outcome Models

Purpose: To extend the capabilities of knowledge-based treatment planning beyond simple dose queries by incorporating validated patient outcome models. Methods: From an analytic, relational database of 684 head and neck cancer patients, 372 patients were identified having dose data for both left and right parotid glands as well as baseline and follow-up xerostomia assessments. For each existing patient, knowledge-based treatment planning was simulated for by querying the dose-volume histograms and geometric shape relationships (overlap volume histograms) for all other patients. Dose predictions were captured at normalized volume thresholds (NVT) of 0%, 10%, 20, 30%, 40%, 50%, and 85% and were compared with the actual achieved doses using the Wilcoxon signed-rank test. Next, a logistic regression model was used to predict the maximum severity of xerostomia up to three months following radiotherapy. Baseline xerostomia scores were subtracted from follow-up assessments and were also included in the model. The relative risks from predicted doses and actual doses were computed and compared. Results: The predicted doses for both parotid glands were significantly less than the achieved doses (p < 0.0001), with differences ranging from 830 cGy ± 1270 cGy (0% NVT) to 1673 cGy ± 1197 cGy (30% NVT). The modelled risk of xerostomia ranged from 54% to 64% for achieved doses and from 33% to 51% for the dose predictions. Relative risks varied from 1.24 to 1.87, with maximum relative risk occurring at 85% NVT. Conclusions: Data-driven generation of treatment planning objectives without consideration of the underlying normal tissue complication probability may Result in inferior plans, even if quality metrics indicate otherwise. Inclusion of complication models in knowledge-based treatment planning is necessary in order to close the feedback loop between radiotherapy treatments and patient outcomes. Future work includes advancing and validating complication models in the context of knowledge-based treatment planning. This work is supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Developing a human factors toolkit to cope with the multi-project situation - 346

Beside of the challenge from technology improvement and stricter safety review in the area of human factors engineering and integrated human system interface resources design, the pressure from the engineering efficiency and quality continues increasing nowadays while 'one-design-several-sites' is becoming more and more common for the nuclear energy industrial in China. A toolkit based on relational database technology was developed to support the whole process of HFE analysis for designer. A through requirement analysis was conducted. Beside of requirements form technical view of point, the considerations from engineering process, quality management, computer technology and data interface were also involved as a whole. During the implementation, resolutions were developed to solve problems like multi-project, multi-group and so on. Lessons learned during the design and development process are summarized as references for similar projects. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Web Based Monitoring in the CMS Experiment at CERN

The Compact Muon Solenoid (CMS) is a large and complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To this end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to the experimenters, including data such as beam conditions, luminosity, trigger rates, detector conditions, and many others, allowing for flexibility on the user side. This paper describes the WBM system architecture and describes how the system was used during the first major data taking run of the LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2009

Event Driven Messaging with Role-Based Subscriptions

Event Driven Messaging with Role-Based Subscriptions (EDM-RBS) is a framework integrated into the Service Management Database (SMDB) to allow for role-based and subscription-based delivery of synchronous and asynchronous messages over JMS (Java Messaging Service), SMTP (Simple Mail Transfer Protocol), or SMS (Short Messaging Service). This allows for 24/7 operation with users in all parts of the world. The software classifies messages by triggering data type, application source, owner of data triggering event (mission), classification, sub-classification and various other secondary classifying tags. Messages are routed to applications or users based on subscription rules using a combination of the above message attributes. This program provides a framework for identifying connected users and their applications for targeted delivery of messages over JMS to the client applications the user is logged into. EDMRBS provides the ability to send notifications over e-mail or pager rather than having to rely on a live human to do it. It is implemented as an Oracle application that uses Oracle relational database management system intrinsic functions. It is configurable to use Oracle AQ JMS API or an external JMS provider for messaging. It fully integrates into the event-logging framework of SMDB (Subnet Management Database).

Bui, Tung↗
DOE OSTI2017

The web based monitoring project at the CMS experiment

The Compact Muon Solenoid is a large a complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To the end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to the experimenters, including data such as beam conditions, luminosity, trigger rates, detector conditions, and many others, allowing for flexibility on the user’s side. This paper describes the WBM system architecture and describes how the system has been used from the beginning of data taking until now (Run1 and Run 2).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-T-679: Retrospective Analysis of the Sensitivity of Planar Dose Measurements To Gamma Analysis Criteria

Purpose: IMRT QA using planar dose measurements is still a widely used method for checking the accuracy of treatment plans. A pass/fail judgment is made using gamma analysis based on a single endpoint. Using more stringent criteria is a way to increase the sensitivity to planning and delivery errors. Before such implementation, it is necessary to understand how the sensitivity to different gamma criteria settings affects gamma passing rates (GPR). Methods: 752 IMRT QA measurements were re-analyzed with varying distance to agreement (DTA) and dose difference (DD) percentages using a Matlab program. Other quantifying information such as the mean dose difference in the treatment target (defined as points that are greater than 80% of maximal dose) were stored in a relational database for retrospective analysis. Results: The average and standard deviation of GPR (%) fell from 99.84 ± (0.43) to 89.61 ± (6.08) when restricting DD from 5 − 1% respectively, as compared to a drop from 99.15 ± (1.19) to 95.00 ± (4.43), when restricting the DTA from 5 − 1 mm respectively. The mean dose difference (%) in the treatment target between measured and calculated dose was −1.96 ± (0. 83), −0.09 ± (0.98), and 1.44 ± (0. 86) for each of our institution’s three matched linear accelerators (LINAC 1, 2, and 3 respectively). For plans that are approximately 2.7 sigma below the mean GPR, an average of 78.4% of those plans were measured on LINAC 1 or 3, while only 48% of the total plans were run on those machines. Conclusion: The data demonstrates that when restricting gamma criterion, such as the DD, the greatest indicator of reduced GPR in our institution is which matched LINAC the plan was measured on. While small, these differences manifest themselves to levels comparable to other treatment related differences and possibly confound the gamma analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗
DOE OSTI2020

A Comprehensive Scientific Survey of Excipients Used in Currently Marketed, Therapeutic Biological Drug Products

The steady development of biotechnology-derived therapeutic biologics over the last few decades has generated drugs that are now standard medical treatments for a range of indications. While the development of protein products has surged in recent years, the formulation and delivery of these complex molecules have relied on drug-specific studies and, in some instances, data from non-proteinaceous drug products. The commonalities, trends, and gaps in excipient technologies used to support the development of therapeutic proteins largely remain unexplored due to the drug-specific nature of many formulations. Using a comprehensive and relational database approach, we aimed to provide a scientific survey of all approved or licensed biotechnology-derived drug products with the goal of providing evidence-based information on common attributes and trending features in protein product excipients. We examined 665 formulations, and 395 unique formulations based on having unique excipients within them, that supported 211 therapeutic proteins as of June 2020. We report the prevalence of each excipient class and excipient chemical used in eight different drug types including monoclonal antibodies, antibody conjugates, cytokines and growth factors, enzymes, polypeptide hormones, pulmonary surfactants, recombinant fusion proteins, and toxins. We also report the prevalence by excipient type among all therapeutic proteins, in the context of each drug’s recommended pH range, concentration ranges for excipients, and route of administration. The results of our analyses indicate certain excipients common to monoclonal antibodies, cytokines, and polypeptide hormones. We also report on excipients unique to protein drug products, such as amino acids, solubilizers, and lyoprotectants. Overall, our report summarizes the current landscape of excipients used in marketed biotechnology-derived therapeutic biologic products.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis

Abstract The present article introduces a new software, Microstructure Evaluation Tool for Interface Statistics (METIS), that performs high-throughput microstructure statistical analysis from electron backscatter diffraction maps. Emphasis is placed on the detection of twin domains in hexagonal close-packed metals. The numerical framework on which METIS is built leverages graph theory, group structures, and associated numerical algorithms to automatically detect twins and unravel both their intrinsic characteristics features and those pertaining to their interactions. The proposed graphical interface allows for the detection and correction of unlikely twin/parent associations rendering the approach applicable to highly deformed microstructures. Twin statistics and microstructural data are classified and saved in a relational database that can be interrogated via either GUI or SQL requests to reveal a wide spectrum of features of the microstructure. Illustration of the approach is performed in the case of zirconium.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An automated multiplexed turbidometric and data collection system for measuring growth kinetics of anaerobes dependent on gaseous substrates

Standard methods of monitoring the growth kinetics of anaerobic microorganisms are generally impractical when there is a protracted or indeterminate period of active growth, and when high numbers of samples or replications are required. As part of our studies of the adaptive evolution of a simple anaerobic syntrophic mutualism, requiring the characterization of many isolates and alternative syntrophic pairings, here we developed a multiplexed growth monitoring system using a combination of commercially available electronics and custom designed circuitry and materials. This system automatically monitors up to 64 sealed, and as needed pressurized, culture tubes and reports the growth data in real-time through integration with a customized relational database. The utility of this system was demonstrated by resolving minor differences in growth kinetics associated with the adaptive evolution of a simple microbial community comprised of a sulfate reducing bacterium, Desulfovibrio vulgaris, grown in syntrophic association with Methanococcus maripaludis, a hydrogenotrophic methanogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Development of Streamlined Nuclear Safety Analysis Tool for Spent Nuclear Fuel Applications

To understand the changing nuclear and mechanical characteristics of spent nuclear fuel (SNF) or used nuclear fuel (UNF) and the different storage, transportation, and disposal systems at various stages within the waste management system, different types of analyses are required. These analyses require the use of assorted tools and numerous types of data. Using the appropriate modeling and simulation (M&S) parameters and selecting from the diversity of analytic tools to conduct SNF analyses can be a tedious, error-prone, and time-consuming undertaking for analysts and reviewers alike. A new, integrated data and analysis system was designed to simplify and automate performance of accurate, efficient evaluations for characterizing the input to the overall U.S. nuclear waste management system—the UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database has been assembled to provide a standard means by which UNF-ST&DARDS can succinctly store and retrieve M&S parameters for specific SNF analysis. A library of various analysis model templates is used to communicate M&S parameters for the most appropriate M&S application. A process manager facilitates performance of actual as-loaded, assembly-specific, and cask-specific evaluations. Interactive visualization capabilities facilitate data analysis and results interpretation. To date, UNF-ST&DARDS has completed (1) explicit depletion and decay analysis of every fuel assembly (~245 000) discharged from commercial U.S. reactors through June 2013, with 13 cooling time steps (results include isotopic compositions for 142 isotopes, and radiation and thermal source terms); (2) SNF radiation dose rate evaluations at 1 m for all the fuel assemblies discharged through June 2013; and (3) criticality, shielding, thermal, and containment analyses of hundreds of loaded casks. In conclusion, UNF-ST&DARDS also provides various automated report generation capabilities with dynamic figure and table update capabilities based on changes to the Unified Database.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Cataloging Legacy Data from the Tritium Systems Test Assembly Program

The Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory, operational from 1984 to 2001, was critical in advancing fusion fuel cycle technologies, including tritium storage, gas separation, and pumping. TSTA’s contributions, particularly in safe tritium operations, have influenced subsequent fusion projects. This paper discusses the ongoing effort to digitize and catalog TSTA’s historical data to create a searchable resource for the fusion research community. While the long-term objective is to develop a relational database for structured data management, the project remains in the early phase, with current efforts focused on scanning and indexing physical documents. Initial plans for database implementations are also presented, outlining key considerations for structure, query indexing, and standardization. As digitization progresses, future discussions will refine these implantation details to ensure an efficient and comprehensive system. This initiative aims to preserve critical legacy data, enhance the design of tritium system facilities, and support the next generation of fusion energy research.

42 ENGINEERING↗
DOE OSTI2018

A scalable new mechanism to store, query and serve the ATLAS detector description through a REST web API

Until now, geometry information for the detector description of the ATLAS experiment was only defined in C++ code, stored in online relational databases integrated into the experiment's frameworks or described in files with text-based markup languages. In all cases, to build and use the complete detector geometry, a full software stack was needed. In this paper, we present a new and scalable mechanism to store the geometry data and to query and serve the detector description data through a web interface and a REST API. This new approach decouples the geometry information from the experiment's framework. Moreover, it provides new functionalities to users, who can now search for specific volumes and get partial detector description, or filter geometry data based on custom criteria. We present two approaches to build a REST API to serve geometry data, based on two different technologies used in other fields and communities: The graph database Neo4j and the search engine ElasticSearch. We describe their characteristics, and we compare them in a HEP context.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

A Conditions Data Management System for HEP Experiments

Conditions data infrastructure for both ATLAS and CMS have to deal with the management of several Terabytes of data. Distributed computing access to this data requires particular care and attention to manage request-rates of up to several tens of kHz. Thanks to the large overlap in use cases and requirements, ATLAS and CMS have worked towards a common solution for conditions data management with the aim of using this design for data-taking in Run 3. In the meantime other experiments, including NA62, have expressed an interest in this cross- experiment initiative. For experiments with a smaller payload volume and complexity, there is particular interest in simplifying the payload storage. The conditions data management model is implemented in a small set of relational database tables. A prototype access toolkit consisting of an intermediate web server has been implemented, using standard technologies available in the Java community. Access is provided through a set of REST services for which the API has been described in a generic way using standard Open API specications, implemented in Swagger. Such a solution allows the automatic generation of client code and server stubs and further allows changes in the backend technology transparently. An important advantage of using a REST API for conditions access is the possibility of caching identical URLs, addressing one of the biggest challenges that large distributed computing solutions impose on conditions data access, avoiding direct DB access by means of standard web proxy solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2012

LCG Persistency Framework (CORAL, COOL, POOL): Status and Outlook in 2012

The LCG Persistency Framework consists of three software packages (CORAL, COOL and POOL) that address the data access requirements of the LHC experiments in several different areas. The project is the result of the collaboration between the CERN IT Department and the three experiments (ATLAS, CMS and LHCb) that are using some or all of the Persistency Framework components to access their data. POOL is a hybrid technology store for C++ objects, using a mixture of streaming and relational technologies to implement both object persistency and object metadata catalogs and collections. CORAL is an abstraction layer with an SQL-free API for accessing data stored using relational database technologies. COOL provides specific software components and tools for the handling of the time variation and versioning of the experiment conditions data. This presentation reports on the status and outlook in each of the three sub-projects at the time of the CHEP2012 conference, reviewing the usage of each package in the three LHC experiments.

Trentadue, R.↗
DOE OSTI2015

The Geant4 physics validation repository

The Geant4 collaboration regularly performs validation and regression tests. The results are stored in a central repository and can be easily accessed via a web application. In this article we describe the Geant4 physics validation repository which consists of a relational database storing experimental data and Geant4 test results, a java API and a web application. Lastly, the functionality of these components and the technology choices we made are also described

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

MetaHCR: a web-enabled metagenome data management system for hydrocarbon resources

The ever-increasing metagenomic data necessitate appropriate cataloguing in a way that facilitates the comparison and better contextualization of the underlying investigations. To this extent, information associated with the sequencing data as well as the original sample and the environment where it was obtained from is crucial. To date, there are not any publicly available repositories able to capture environmental metadata pertaining to hydrocarbon-rich environments. As such, contextualization and comparative analysis among sequencing datasets derived from these environments is to a certain degree hindered or cannot be fully evaluated. The metagenomics data management system for hydrocarbon resources (MetaHCRs) enables the capturing of marker gene and whole metagenome sequencing data as well as over 300 contextual attributes associated with samples, organisms, environments and geological properties, among others. Moreover, MetaHCR implements the Minimum Information about any Sequence–hydrocarbon resource specification from the Genomic Standards Consortium; it integrates a user-friendly web interface and relational database model, and it enables the generation of complex custom search. MetaHCR has been tested with 36 publicly available metagenomic studies, and its modular architecture can be easily customized for other types of environmental and metagenomics studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Automated Indexing of Structured Scientific Metadata Using Apache Solr

Scientific datasets are continuously growing with the amount of raw data being collected worldwide. This amount of data poses the biggest challenge to web search engines on how to retrieve them efficiently. This paper discusses how major scientific data centers are using popular open-source search platforms such as Solr [1] to retrieve structured data stored in data sources such as relational database management systems using its import handler mechanisms [2]. Additionally, we will also focus on how we can configure Solr to serve advanced full-text, faceted search capabilities, along with its key features, which simplify representing and delivering better performance to the scientific search interfaces.

Guntupally, Kavya↗