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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Forensic Signature Detection of Yersinia Pestis Culturing Practices Across Institutions Using a Bayesian Network

The field of bioforensics is focused on the analysis of evidence from a biocrime. Existing laboratory analyses can identify the specific strain of an organism in the evidence, as well signatures of the specific culture batch of organisms, such as low-frequency contaminants or indicators of growth and processing methods. To link these disparate types of physical data to potential suspects, investigators may need to identify institutions or individuals whose access to strains and culturing practices match those identified from the evidence. In this work we present a Bayesian statistical network to fuse different types of analytical measurements that predict the production environment of a Yersinia pestis sample under investigation with automated test processing of scientific publications to identify institutions with a history of growing Y. pestis under similar conditions. Furthermore, the textual and experimental signatures were evaluated recursively to determine the overall sensitivity of the network across all levels of false positives. We illustrate that institutions associated with several specific culturing practices can be accurately selected based on the experimental signature from only a few analytical measurements. These findings demonstrate that similar Bayesian networks can be generated generically for many organisms of interest and their deployment is not prohibitive due to either computational or experimental factors.

Bayesian networks↗
DOE OSTI2019

Studies of the FBK Low-Gain Avalanche Detectors for the CMS Endcap Timing Layer

The CMS MIP Timing Detector (MTD) will bring precision timing information as part of the Phase II upgrade program to prepare CMS for the HL-LHC. The MTD will provide hermetic timing coverage up to a pseudo-rapidity of |η| = 3, with time resolution better than 40 ps. In the high-radiation forward region from |η|=1.6 and 3.0, this achieved with the Endcap Timing Layer (ETL), based on silicon low gain avalanche detectors (LGADs). An extensive LGAD R&D program has been ongoing to characterize sensor performance to develop LGADs suitable for ETL. We discuss the details of the automated test beam DAQ environment developed for efficient characterization of prototype LGAD sensors at the Fermilab Test Beam Facility (FTBF), and the latest results for sensors produced by Fondazione Bruno Kessler (FBK) with a focus on characterization of radiation hardness and uniformity.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

WIPP Certification of the Retrieval Box Assay System at the Advanced Mixed Waste Treatment Plant, Idaho - 16241

The Retrieval Box Assay System (RBAS) at the Advanced Mixed Waste Treatment Plant (AMWTP) is an Imaging Passive Active Neutron system supplemented with a High Purity Germanium (HPGe) gamma system for the quantification of Pu-239 Fissile Gram Equivalent (FGE) and transuranic (TRU) alpha activity of waste containers of various sizes up to 249 cm x 149 cm x 198 cm (Length x Width x Height). The system was originally calibrated in 2002 (with a range of surrogate matrices and radioactive sources in a 213 cm x 122 cm x 122 cm FRP box) and has been operational for over a decade. As of August 2015, the RBAS has measured approximately 18,000 boxes (50,000 m3 of waste) which has subsequently been fed into the facility's treatment process. Its success, and the wide envelope of waste that it can characterize, has led AMWTP to extend the RBAS mission to include WIPP certification. As part of this new project, the instrument must be capable of meeting WIPP's Waste Acceptance Criteria (WAC) which include reporting activities and masses of the 10 WIPP-tracked radionuclides. The system will be required to assay sludge and debris waste streams, shredded waste and large metal items. The container size includes Standard Waste Box (SWBs), Fiberglass Reinforced Plywood (FRPs) and large Shredder Boxes. Sludge matrices will be loaded into 210-liter (55-gallon) drums and placed inside an SWB. After assay, boxes will be over-packed into SLB-II's for shipment to WIPP. The target waste streams will contain mixtures of Weapons Grade plutonium, Heat Source plutonium (high in Pu-238 content) and Mixed Oxide (MOX). The activity of the waste is expected to encompass a wide dynamic range of activity from low-level waste (LLW) to TRU with up to several hundred grams of plutonium. Some packages will have high gamma activity associated with fission and activation products such as Cs-137 and Co-60. The existing RBAS hardware (detectors, electronics, assay chamber etc.) was retained for this project. Two lead filters were provided and installed on the existing filter wheels to attenuate the gamma ray flux from the highest activity boxes to avoid overload of the HPGe detectors. The new software suite includes PC-FRAM (Version 5), which is used for the isotopic analysis of the gamma spectra. Integration of FRAM and neutron results is performed using a software package known as RBAS WIPP Analysis Reporting Software (RWARS). This package also performs matrix dependent background adjustments. Other upgrades provided include automated tests that identify when assay parameters fall outside a predetermined range and a new Quality Checking (QC) application. Minimum Detectable Activity (MDA) values were determined for the active and passive neutron modes as a function of measured matrix correction indices. The resulting Minimum Detectable Concentration (MDC) has been demonstrated to be less than 3700 Bq/g alpha activity (100 nCi/g). Modifications were performed to update the system TMU parameters to accommodate assay of non-standard size boxes and a wider range of matrix materials. A series of calibration confirmation, measurements were performed on site in 2014 using a representative range of surrogate boxes and radioactive sources including Pu. The WIPP WAC performance criteria were successfully demonstrated up to 157 g Pu and the system passed its first Performance Demonstration Program (PDP) cycle in the Spring of 2015. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

MY EXES and EDM for Automated Remediation Data Quality Assessments - 19053

MY Electronic data exchange and Evaluation System (EXES) is a new web-based technology providing external admin access and full control to the Web-based EXES tool developed by GD for EPA for automated environmental remediation data quality assessments. EXES replaces most manual assessment processes, reducing remediation data review time and costs and ensuring that data are of known and documented quality. This tool is available from EPA to federal agencies and remediation firms and has successfully been used to support over 190 site investigations, 105 Remedial investigations and over 20 compliance monitoring efforts. The new MY EXES functionality has been developed for project managers and decision makers to setup projects, track receipt of environmental remediation monitoring data, assess data quality, and manage data. It is designed to be flexible and configurable to meet any government agency's data review and data management needs. It is accessible 24/7 through a secure portal. MY EXES efficiently evaluates analytical data regardless of the underlying method and data reporting requirements. It is a centralized project and data assessment tool that is scalable, flexible and configurable; improving data quality while reducing cost through the following: - Provides users with the ability to create a project and to specify the analytical methods corresponding to the data that will be submitted for that project. A project can be modified and managed anytime during the project's life cycle. - Allows users to manage a library of analytical methods that can be made available for association to their projects. - Users can specify the automated tests and assessment that needs to be performed on the analytical data deliverables based on specific requirements in the project's Quality Assurance Project Plan (QAPP). - Users specify: - The format of the incoming data deliverables from the laboratory; - The type and level of review services to be performed; - The assessment deliverables to be generated - output spreadsheets and reports; - Project owner sets up system access and permissions for members of the project team. - A faster (600%) and less expensive (85%) process than the traditional data usability/validation. The EXES Data Manager application (EDM) provides a centralized data repository to view and retrieve generated reports, spreadsheets, and other data deliverables as defined by the client, eliminating the need for data transfer between project team members. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Using the BEopt Automated Residential Simulation Test Suite to Enable Comparative Analysis Between Energy Simulation Engines: Preprint

Verification and validation are crucial software quality control procedures when developing and implementing models. This is particularly important as a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes models that isolate the impacts of specific building components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models; these discrepancies are caused by differences in the models used by the engines or coding errors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Using the Beopt Automated Residential Simulation Test Suite to Enable Comparative Analysis Between Energy Simulation Engines (Preprint)

Verification and validation are crucial software quality control procedures to follow when developing and implementing models. This is particularly important because a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes building models that isolate the impacts of specific components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models. These discrepancies are caused by differences in the algorithms used by the engines or coding errors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Improved Throughput and Analysis of Scratch Test Results via Automation and Machine Learning

A data analysis automation interface that incorporates machine learning (ML) has been developed to improve productivity, efficiency, and consistency in identifying and defining critical load values (or other values associated with optically identifiable characteristics) of a coating when a scratch test is performed. In this specific program, the machine learning component of the program has been trained to identify the Critical Load 2 (L C2 ) value by analyzing images of the scratch tracks created in each test. An optical examination of the scratch by a human operator is currently used to determine where this value occurs. However, the vagueness of the standard has led to varying interpretations and nonuniform usage by different operators at different laboratories where the test is implemented, resulting in multiple definitions of the desired parameter. Using a standard set of training and validation images to create the dataset, the critical load can be identified consistently amongst different laboratories using the automation interface without requiring the training of human operators. When the model was used in conjunction with an instrument manufacturer's scratch test software, the model produced accurate and repeatable results and defined L C2 values in as little as half of the time compared to a human operator. When combined with a program that automates other aspects of the scratch testing process usually conducted by a human operator, scratch testing and analysis can occur with little to no intervention from a human beyond initial setup and frees them to complete other work in the lab.

36 MATERIALS SCIENCE↗
DOE OSTI2024

MUPPET: An automated OpenMP mutation testing framework for performance optimization

MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at improving program performance. Existing performance optimization techniques, including profiling-based and auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their portability across compilers. MUPPET aims to help HPC developers reason about performance defects and missed opportunities to improve performance at the source code level.

Parasyris, Konstantinos↗
DOE OSTI2025

Microreactor Automated Control System Test Bed Digital Architecture for Real-Time, Hardware-in-the-Loop Simulation

This work describes progress made towards the development of a real-time hardware-in-the-loop (HIL) test bed for non-nuclear testing of microreactor control schemes and failure modes. Non-nuclear testing is a crucial step in developing robust control algorithms for managing microreactor dynamics. The creation of an HIL simulation harnesses the realistic dynamics of physical analogue systems while additionally considering the challenges of variable communication delay. This collaborative effort between Oak Ridge National Laboratory and Idaho National Laboratory has resulted in a LabVIEW-based gRPC communication protocol which couples a TRANSFORM Modelica simulation of nuclear components to the ViBRANT physical hardware for realistic feedback and visual representation of control action in real time. A modular python client structure is developed to manage FMU-based Modelica simulation and real-time gRPC communication. HIL testing suggests that the modeled reactor with natural convection molten salt loop coolant configuration responds well to PID control of drum positioning for modulation of reactor core power, however, future efforts will be made to explore the added thermal inertial delay of system level control and downstream demand changes. Development of this platform with a generalized methodology provides a foundation for exploring a variety of reactor configurations and failure modes in rapid order to provide insight into the most effective avenues of study for further research and development.

McConnell, Jono [ORNL] (ORCID:0000000238984741)↗
DOE OSTI2021

Automated Cyber Security Testing Platform for Industrial Control Systems

Nuclear Power Plants (NPPs) are a complex system of coupled physics controlled by a network of Programmable Logic Controllers (PLCs). These PLCs communicate process data across the network to coordinate control actions with each other and inform the operators of process variables and control decisions. Networking the PLCs allows more effective process control and provides the operator more information which results in more efficient plant operation. This interconnectivity creates new security issues, as operators have more access to the plant controls, so will bad actors. As plant networks become more digitized and encompass more sophisticated controllers, the network surface exposed to cyber interference grows. Understanding the dynamics of these coupled systems of physics, control logic, and network communications is critical to their protection. The research into the cybersecurity of the Operational Technologies of NPPs is developing and requires a platform that can allow high fidelity physics simulations to interact with digital networks of controllers. This will require three main components: a network simulation environment, a physics simulator, and virtual PLCs (vPLC) that represent typical industry hardware. A platform that incorporates these three components to provide the most accurate representation of actual NPP networks and controllers is developed in this paper.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗