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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Overcoming challenges to support US resumption of high specific activity cobalt-60

Domestic production of high specific activity 60 Co was halted after a target rupture in 2012 at the Advanced Test Reactor (ATR). The Isotope Program (IP) within the US Department of Energy (DOE) Office of Science tasked a multilaboratory team of researchers and managers from Oak Ridge and Idaho National Laboratories with the redesign the radioisotope capsule. The objective of this effort was to create a more robust and reliable design, compared to the pre-2012 target. The team successfully completed this task to produce the DOE-IP cobalt (Co) production capsule design. Furthermore, 66 capsules were successfully fabricated by Oak Ridge National Laboratory (ORNL) and delivered to Idaho National Laboratory (INL) for irradiation in the ATR between January 2014 and October 2016. This paper describes the efforts of the team to prepare and disposition the two initial DOE-IP Co production capsules that were processed in March 2020. These efforts include performing accurate production predictions, experimentally validating predictions with assay measurements, shipping with the Orano-furnished Battelle Energy Alliance Research Reactor shipping package, and disassembling capsules at the isotope vendor site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An Internet of Things Approach to Electrical Power Monitoring and Outage Reporting

The so-called Internet of Things concept has captured much attention recently as ordinary devices are connected to the Internet for monitoring and control purposes. One enabling technology is the proliferation of low-cost, single board computers with built-in network interfaces. Some of these are capable of hosting full-fledged operating systems that provide rich programming environments. Taken together, these features enable inexpensive solutions for even traditional tasks such as the one presented here for electrical power monitoring and outage reporting.

Internet of Things↗
DOE OSTI2017

Addressing Global Data Dependencies in Heterogeneous Asynchronous Runtime Systems on GPUs

Large-scale parallel applications with complex global data dependencies beyond those of reductions pose significant scalability challenges in an asynchronous runtime system. Internodal challenges include identifying the all-to-all communication of data dependencies among the nodes. Intranodal challenges include gathering together these data dependencies into usable data objects while avoiding data duplication. This paper addresses these challenges within the context of a large-scale, industrial coal boiler simulation using the Uintah asynchronous many-task runtime system on GPU architectures. We show significant reduction in time spent analyzing data dependencies through refinements in our dependency search algorithm. Multiple task graphs are used to eliminate subsequent analysis when task graphs change in predictable and repeatable ways. Using a combined data store and task scheduler redesign reduces data dependency duplication ensuring that problems fit within host and GPU memory. Furthermore, these modifications did not require any changes to application code or sweeping changes to the Uintah runtime system. We report results running on the DOE Titan system on 119K CPU cores and 7.5K GPUs simultaneously. Our solutions can be generalized to other task dependency problems with global dependencies among thousands of nodes which must be processed efficiently at large scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Managing code transformations for better performance portability

Code optimization is an intricate task that is getting more complex as computing systems evolve. Managing the program optimization process, including the implementation and evaluation of code variants, is tedious, inefficient, and errors are likely to be introduced in the process. Moreover, because each platform typically requires a different sequence of transformations to fully harness its computing power, the optimization process complexity grows as new platforms are adopted. To address these issues, systems and frameworks have been proposed to automate the code optimization process. They, however, have not been widely adopted and are primarily used by experts with deep knowledge about underlying architecture and compiler intricacies. This article describes the requirements that we believe necessary for making automatic performance tuning more broadly used, especially in complex, long-lived high-performance computing applications. Besides discussing limitations of current systems and strategies to overcome these, we describe the design of a system that is able to semi-automatically generate efficient platform-specific code. In the proposed system, the code optimization is programmer-guided, separately from application code, on an external file in what we call optimization programming. The language to program the optimization process is able to represent complex collections of transformations and, as a result, generate efficient platform-specific code. A database manages different optimized versions of code regions, providing a pragmatic approach to performance portability, and the framework itself has separate components, allowing the optimized code to be used on systems without installing all of the modules required for the code generation. We present experiments on two different platforms to illustrate the generation of efficient platform-specific code that performs comparable to hand-optimized, vendor-provided code.

Computer Science↗
DOE OSTI2019

O(N) Quantum Molecular Dynamics (QMD) Algorithms, Code Requirements, Release Notes, and Library Deployment

The Exascale Computing Project (ECP) Co-design Center for Particle Applications (CoPA) is addressing the challenges for particle applications to run on upcoming exascale computing architectures. This includes short- and long-range molecular dynamics (MD), particle-in-cell (PIC), and quantum molecular dynamics (QMD). This document addresses $\mathcal{O}(N)$ QMD. The goal of this CoPA team is to develop $\mathcal{O}(N)$ linear scaling methods for QMD optimized for new and next generation architectures. This will provide the capability to simulate larger systems and run for longer timeframes than is possible today. Focus is initially on the density matrix construction. This requires efficient matrix formats and linear algebra operations for distributed architectures. A significant reduction in the wallclock time for an MD timestep is necessary to achieve practical large scale QMD. Equally challenging is to develop scalable distributed implementations. This requires the exploration of efficient data formats (dense, sparse, etc.), data decomposition and distribution across compute nodes using block- and graph-based methods. Traditional programming models such as MPI/OpenMP, hybrid MPI/OpenMP/Accelerator, as well as asynchronous task-based models will be explored to achieve maximum parallelism. Parallelism at the level of a matrix operation, solver, and/or application needs to be explored to gain the most benefit on new and emerging architectures. This report serves as a “living document” of the additions and enhancements throughout the ECP CoPA project for $\mathcal{O}(N)$ QMD. The following sections address the applications we are working with, the quantum chemistry libraries (BML and PROGRESS), and our co-design exploration through the use of a proxy application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

National Technology & Engineering Solutions of Sandia, LLC Technical Assistance With Dine College (Final CTAP Report)

Under the CTAP Statement of Work, Sandia was tasked with providing technical assistance to Dine College to create a testing program to determine hazardous contaminant levels in donated hand sanitizer. Sandia will loan instrumentation, provide a procedure, and act as technical advisor. The challenge for on-site testing lies in a balance of testing capability/speed, complexity, and cost of operations. Instruments that allow fastest and least expensive operation will be validated for performance for this sample problem (hand sanitizer w/ poisonous methanol or 1-propanol). The objective of this project is to enable Dine College personnel to perform on-site testing.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Modeling Radionuclide Vaporization from Sodium Pools for SFR Mechanistic Source Term Analysis

To assist both the advanced reactor industry and U.S. Nuclear Regulatory Commission (NRC) in the pursuit of reactor design and licensing, the U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has established a mechanistic source term (MST) research project under the Multiphysics Applications technical area. As part of this effort, an MST mod/sim development pathway was developed in FY21 under the NEAMS program, which outlines the high-level objectives and near-term tasks necessary to achieve the project objectives. One such recommended task was the assessment of a previously developed thermodynamic database to model radionuclide vaporization from liquid sodium pools (specifically in the context of MST analyses), which is the focus of this topic report. As such, a thermodynamic database was created in FactSage for liquid sodium pools containing oxygen and relevant elements which represent radionuclides pertinent to MST analyses. The database was demonstrated in calculating vapor fraction curves for each element in the system at concentrations relevant to SFR MST.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Online System ID for Predicting Power Plant Performance Throughout Cycling Operations

This presentation represents a review of the background research conducted by NETL to apply artificial intelligence, i.e. auto-recursive algorithms and data analytics to detect leaks in utility scale boilers and laboratory power systems. The new project being funded by the Advanced Sensors and Controls Program is part of the Field Work Proposal funded in EY21 as Task 53 to demonstrate the application of these techniques on a utility scale power system.

Shadle, Lawrence↗
DOE OSTI2016

Data Acquisition with GPUs: The DAQ for the Muon $g$-$2$ Experiment at Fermilab

Graphical Processing Units (GPUs) have recently become a valuable computing tool for the acquisition of data at high rates and for a relatively low cost. The devices work by parallelizing the code into thousands of threads, each executing a simple process, such as identifying pulses from a waveform digitizer. The CUDA programming library can be used to effectively write code to parallelize such tasks on Nvidia GPUs, providing a significant upgrade in performance over CPU based acquisition systems. The muon $g$-$2$ experiment at Fermilab is heavily relying on GPUs to process its data. The data acquisition system for this experiment must have the ability to create deadtime-free records from 700 $\mu$s muon spills at a raw data rate 18 GB per second. Data will be collected using 1296 channels of $\mu$TCA-based 800 MSPS, 12 bit waveform digitizers and processed in a layered array of networked commodity processors with 24 GPUs working in parallel to perform a fast recording of the muon decays during the spill. The described data acquisition system is currently being constructed, and will be fully operational before the start of the experiment in 2017.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Brilliant Execution of Smart Labs: Employing Best Practices to Improve Safety and Reduce Energy for Sustainable Labs: Preprint

Laboratory buildings often dominate the energy use on research campuses, consuming three to four times the energy of a typical office building. In most cases, these facilities are defined as “mission critical,” with excessive energy use as simply an unfortunate truth that cannot be avoided without compromising safety. However, case studies indicate cost savings opportunities of up to 40% in laboratories (compared to standard practices) by employing energy efficient design strategies that also improve the safety of lab spaces (Better Buildings 2018). To help stakeholders implement improvement measures, the Smart Labs Toolkit describes a proven approach to optimizing performance of laboratories and critical control environments in new or existing facilities. The Toolkit outlines distinct phases for building a successful Smart Labs program that include: Plan, Assess, Optimize, and Manage. Each phase has specific tasks, training videos, and resources to educate users, support the efforts of key stakeholders, and maximize benefits for the organization in implementing high-performance labs. The Toolkit also includes case studies from the 17 Better Buildings Smart Labs Accelerator partners, sharing lessons learned and supporting the Smart Labs approach to safe, efficient world class science. This paper reviews the technology choices for implementing Smart Labs ventilation strategies, controls, and other efficiency measures. Better Building Smart Lab Accelerator partners provide case study examples of safety and energy-savings results of using Smart Labs approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗
DOE OSTI2020

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
DOE OSTI2023

ORNL NCSP Training and Education Support for FY2022 [Slides]

This presentation is on Oak Ridge National Labatory (ORNL) Nuclear Criticality Safety Program (NCSP) training and education support for Fiscal Year 2022. This lecture explains the approved training and education tasks for fiscal year 2022. Additional training developments for 2022 are covered.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Cyberguardians and STEM Warriors (Final Technical Report (FTR))

In the past decade, solar power, with and without energy storage has become the fastest growing source of energy generation in the world. In the U.S., solar employment more than doubled from 105,145 jobs in 2011 to 255,037 jobs in 2021, four times faster than the U.S. job growth rate overall. These factors, combined with technology advancements, creates a skills gap that puts tremendous stress on society to deliver the workers to fill the open job requisitions. The Cyberguardians and STEM Warriors project (Cyberguardians) was designed to address the trained-worker shortage in the energy industry in three ways: 1) by developing educational curriculum that addresses DER technology changes; 2) by delivering curriculum to prospective workers, including military veterans and their families, via universities, community colleges, and vocational training outlets; and 3) introducing individuals who have completed training to employers that can hire them. Cyberguardians exceeded its curriculum goals by producing 27 academic units of university-accredited material (12 total courses) covering energy fundamentals, smart inverters, Distributed Energy Resource (DER) data communication, cybersecurity, standardization, certification, data analytics, and IEEE 1547 standard topics. The North American Board of Certified Energy Practitioners (NABCEP) also accredited the material for use in their credential program. Seven instructors were recruited and trained, and six academic institutions (University of California San Diego, State University of New York, North Carolina State University, Harper Community College, Green Village Academy, and the SunSpec Alliance) were enlisted, meeting program goals. All course material was published under the Creative Commons license and made available royalty free, thus providing a long-lasting public benefit. The program’s outreach program vastly exceeded program goals and incorporated the efforts of 13 outreach partners (11 of which are veteran focused), an advisory board representing 15 companies, webinars and 10’s of thousands of email messages sent to prospective students and hiring managers. Despite these efforts, the global pandemic depressed anticipated program participation by about a third. Still, a total of 396 students enrolled and 289 completed the courses and were accredited. The job applicant task achieved similar results (111 realized vs a 174 goal) but reported job placement was weaker at (9 realized vs. a 51 goal). The Cyberguardians program fills a critical void for cost-effective, royalty-free curriculum and training pertaining to DER technologies and cybersecurity that prospective energy workers must possess to be effective in the 21 st century. On this basis alone, the investment of taxpayer funds will pay dividends for years to come.

14 SOLAR ENERGY↗
DOE OSTI2021

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
DOE OSTI2025

Passive Temperature Sensors for Nuclear Applications

In April 2007, the Department of Energy (DOE) designated the Advanced Test Reactor (ATR) a National Scientific User Facility (NSUF) to advance US leadership in nuclear science and technology. By attracting new users from universities, laboratories, and industry, this program supports basic and applied nuclear research to help address the nation's energy security needs. In support of this program, the Idaho National Laboratory (INL) established in-house capabilities to develop, fabricate, test, and qualify new and enhanced temperature sensors for irradiation testing. This effort is continuing today through the DOE?s Advanced Sensors and Instrumentation (ASI) program. Although most efforts emphasize sensors capable of providing real-time data, selected tasks have been completed to enhance passive sensors for irradiations where instrumentation leads cannot be included. These sensors include silicon carbide (SiC) monitors, melt wires and the sublime temperature monitor. SiC monitors are available to detect peak irradiation temperatures between 200°C and 800°C in reactor locations where instrumentation leads cannot be used. SiC monitors may be evaluated using specialized equipment installed at INL?s Measurement Sciences Laboratory (MSL). A melt wire inventory is also maintained at MSL. This inventory contains wires for specific use in irradiation experiments ranging in temperatures from 30°C to 1500°C. Melt wires and SiC monitors have had decades of research and application. Recent research has produced a passive monitor known as the sublime temperature monitor. This passive sensor has the capability of recording temperature gradients. This paper will discuss passive temperature sensors currently being researched and implemented under the ASI program.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗