Search NASA⌕ Search

SEARCH · Search NASA

Results for “Computing, Instrumentation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report: Updated in 2016

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is observationally based, and quantifying the uncertainty of its measurements is critically important. With over 300 widely differing instruments providing over 2,500 datastreams, concise expression of measurement uncertainty is quite challenging. ARM currently provides data and supporting metadata (information about the data or data quality) to its users through several sources. Because the continued success of the ARM Facility depends on the known quality of its measurements, ARM relies on Instrument Mentors and the ARM Data Quality Office to ensure, assess, and report measurement quality. Therefore, an easily accessible, well-articulated estimate of ARM measurement uncertainty is needed. This report is a continuation of the work presented by Campos and Sisterson (2015) and provides additional uncertainty information from instruments not available in their report. As before, a total measurement uncertainty has been calculated as a function of the instrument uncertainty (calibration factors), the field uncertainty (environmental factors), and the retrieval uncertainty (algorithm factors). This study will not expand on methods for computing these uncertainties. As before, it will focus on the practical identification, characterization, and inventory of the measurement uncertainties already available to the ARM community through the ARM Instrument Mentors and their ARM instrument handbooks. This study continues the first steps towards reporting ARM measurement uncertainty as: (1) identifying how the uncertainty of individual ARM measurements is currently expressed, (2) identifying a consistent approach to measurement uncertainty, and then (3) reclassifying ARM instrument measurement uncertainties in a common framework.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Integration of scanning probe microscope with high-performance computing: Fixed-policy and reward-driven workflows implementation

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements toward operationalization of the automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for scientific discovery. Here, we build a Python interface library that enables controlling an SPM from either a local computer or a remote high-performance computer, which satisfies the high computation power need of machine learning algorithms in autonomous workflows. We further introduce a general platform to abstract the operations of SPM in scientific discovery into fixed-policy or reward-driven workflows. Furthermore, our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Power API Prototype

The software serves two purposes. The first purpose of the software is to prototype the Sandia High Performance Computing Power Application Programming Interface Specification effort. The specification can be found at http://powerapi.sandia.gov . Prototypes of the specification were developed in parallel with the development of the specification. Release of the prototype will be instructive to anyone who intends to implement the specification. More specifically, our vendor collaborators will benefit from the availability of the prototype. The second is in direct support of the PowerInsight power measurement device, which was co-developed with Penguin Computing. The software provides a cluster wide measurement capability enabled by the PowerInsight device. The software can be used by anyone who purchases a PowerInsight device. The software will allow the user to easily collect power and energy information of a node that is instrumented with PowerInsight. The software can also be used as an example prototype implementation of the High Performance Computing Power Application Programming Interface Specification.

Laros III, James↗
DOE OSTI2014

Power API Prototype

The software serves two purposes. The first purpose of the software is to prototype the Sandia High Performance Computing Power Application Programming Interface Specification effort. The specification can be found at http://powerapi.sandia.gov . Prototypes of the specification were developed in parallel with the development of the specification. Release of the prototype will be instructive to anyone who intends to implement the specification. More specifically, our vendor collaborators will benefit from the availability of the prototype. The second is in direct support of the PowerInsight power measurement device, which was co-developed with Penguin Computing. The software provides a cluster wide measurement capability enabled by the PowerInsight device. The software can be used by anyone who purchases a PowerInsight device. The software will allow the user to easily collect power and energy information of a node that is instrumented with PowerInsight. The software can also be used as an example prototype implementation of the High Performance Computing Power Application Programming Interface Specification.

Source record↗
DOE OSTI2024

Proof-of-Concept for Sensor Modeling in MOOSE for the Design of Autonomous Nuclear Reactor Control

Autonomous operation is essential for the deployment of microreactors and fission batteries, both in terrestrial and space applications. However, prototypes of microreactors and fission batteries do not exist yet, and even the design space has not been narrowed down conclusively, making the instrumentation and control system design difficult. For this reason, there is a need for flexible computational capabilities to create a numerical stand-in of potential microreactor and fission battery designs. The latter can be used to design and test control strategies to support autonomous operations. In this paper, we describe the initial implementation of a pluggable sensor system for the easy implementation of realistic sensor models in the multiphysics object-oriented simulation environment (MOOSE) framework. This new capability will enable MOOSE users to create a numerical stand-in of microreactors and fission batteries, ultimately allowing them to easily test new control algorithms, and instrumentation strategies for advanced systems in the design phase

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modeling and simulation study for the design of the Fuel Interrogation and Examination using Submersible Tomography Analysis Mk II instrument

Here, the design of a submersible, gamma-ray tomography system for imaging irradiated nuclear fuel is described. The system—named Fuel Interrogation and Examination using Submersible Tomography Analysis (FIESTA) Mk. II—is a variation on a previous Mk. I I design, which was developed to non-destructively image fuel capsules irradiated in the Advanced Test Reactor at the Idaho National Laboratory. The FIESTA system uses a combination of transmission computed tomography and emission computed tomography to image the restructuring and fission product migration at different points of burnup. Changes made to FIESTA Mk. I reflect the revised design requirements and a need to reduce background noise, largely originating from downscattered photons from fuel and transmission source. The computational design and radiation transport simulations are described.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2011

Thermoelectric powered wireless sensors for spent fuel monitoring

This paper describes using thermoelectric generators to power wireless sensors to monitor spent nuclear fuel during dry-cask storage. OrigenArp was used to determine the decay heat of the spent fuel at different times during the service life of the dry-cask. The Engineering Equation Solver computer program modeled the temperatures inside the spent fuel storage facility during its service life. The temperature distribution in a thermoelectric generator and heat sink was calculated using the computer program Finite Element Heat Transfer. From these temperature distributions the power produced by the thermoelectric generator was determined as a function of the service life of the dry-cask. In addition, an estimation of the path loss experienced by the wireless signal can be made based on materials and thickness of the structure. Once the path loss is known, the transmission power and thermoelectric generator power requirements can be determined. This analysis estimates that a thermoelectric generator can produce enough power for a sensor to function and transmit data from inside the dry-cask throughout its service life. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×-5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.

GMRES↗
DOE OSTI2015

The Effects of Maintenance Actions on the PFDavg of Spring Operated Pressure Relief Valves

The safety integrity level (SIL) of equipment used in safety instrumented functions is determined by the average probability of failure on demand (PFDavg) computed at the time of periodic inspection and maintenance, i.e., the time of proof testing. The computation of PFDavg is generally based solely on predictions or estimates of the assumed constant failure rate of the equipment. However, PFDavg is also affected by maintenance actions (or lack thereof) taken by the end user. This paper shows how maintenance actions can affect the PFDavg of spring operated pressure relief valves (SOPRV) and how these maintenance actions may be accounted for in the computation of the PFDavg metric. The method provides a means for quantifying the effects of changes in maintenance practices and shows how these changes impact plant safety.

42 ENGINEERING↗
DOE OSTI2011

Multi-comparative systems biology analysis reveals time-course biosignatures of in vivo bovine pathway responses to B. melitensis, S. enterica Typhimurium and M. avium paratuberculosis

Background: To decipher the complexity and improve the understanding of host-pathogen interactions, biologists must adopt new system level approaches in which the hierarchy of biological interactions and dynamics can be studied. This paper presents the application of systems biology for the cross-comparative analysis and interactome modeling of three different infectious agents, leading to the identification of novel, unique and common molecular host responses (biosignatures). Methods: A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Salmonella enterica Typhimurium (STM) and Mycobacterium avium paratuberculosis (MAP). A bovine ligated ileal loop biological model was employed to capture the host gene expression response at four time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a systematic comparative analysis of pathway and Gene Ontology category perturbations. Results: A cross-comparative assessment of 219 pathways and 1620 gene ontology (GO) categories was performed on each pathogen-host condition. Both unique and common pathway and GO perturbations indicated remarkable temporal differences in pathogen-host response profiles. Highly discriminatory pathways were selected from each pathogen condition to create a common system level interactome model comprised of 622 genes. This model was trained with data from each pathogen condition to capture unique and common gene expression features and relationships leading to the identification of candidate host-pathogen points of interactions and discriminatory biosignatures. Conclusions: Our results provide deeper understanding of the overall complexity of host defensive and pathogen invasion processes as well as the identification of novel host-pathogen interactions. The application of advanced computational methods for developing interactome models based on DBN has proven to be instrumental in conducting multi-conditional cross-comparative analyses. Further, this approach generates a fully simulateable model with capabilities for predictive analysis as well as for diagnostic pattern recognition. The resulting biosignatures may represent future targets for identification of emerging pathogens as well as for development of antimicrobial drugs, immunotherapeutics, or vaccines for prevention and treatment of diseases caused by known, emerging/re-emerging infectious agents.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Diffraction properties of cylindrically bent KAP crystals in energy range of 2.3–7.5 keV using synchrotron radiation

Verification of physics models and computer simulations are heavily reliant upon the accuracy of experimental measurements. Calibration of instrument responses becomes an important step to achieve this goal. This paper presents systematic studies of bent potassium acid phthalate (KAP) crystals using Lawrence Berkeley National Laboratories, Advanced Light Source, beamline 9.3.1 in the energy range of 2.3 to 7.5 keV. A set of KAP crystals, gradually bent from flat up to a 50.8 mm cylindrical curvature. The measured integrated reflectivity for this set of KAP crystals shows good agreement with the X-ray Oriented Program (XOP) calculations when adjusting the Debye–Waller temperature factor and using the multilamellar model in the calculations. Significant differences in rocking curve profiles were observed between experimental measurements and theory. A forward convolution model and software code were developed to include experimental parameters, allowing the investigation of the difference between measurements and calculations. After considering the experimental parameters, good agreements were obtained for the rocking curve profiles for all bending radii with a unique set of parameters. Our results show that XOP can be a useful and reliable tool to predict performance of cylindrically bent KAP crystals in this energy range.

Wu, Ming↗
DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗
DOE OSTI2014

THE EFFECTS OF MAINTENANCE ACTIONS ON THE PFDavg OF SPRING OPERATED PRESSURE RELIEF VALVES

The safety integrity level (SIL) of equipment used in safety instrumented functions is determined by the average probability of failure on demand (PFDavg) computed at the time of periodic inspection and maintenance, i.e., the time of proof testing. The computation of PFDavg is generally based solely on predictions or estimates of the assumed constant failure rate of the equipment. However, PFDavg is also affected by maintenance actions (or lack thereof) taken by the end user. This paper shows how maintenance actions can affect the PFDavg of spring operated pressure relief valves (SOPRV) and how these maintenance actions may be accounted for in the computation of the PFDavg metric. The method provides a means for quantifying the effects of changes in maintenance practices and shows how these changes impact plant safety.

42 ENGINEERING↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Opportunities for retrieval and tool augmented large language models in scientific facilities

Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Fiber Optic Instrumentation in High Temperature Irradiation Environments

The extremely harsh conditions of advanced reactor designs pose serious challenges for nuclear fuels and materials. Traditional instrumentation (thermocouples, strain gauges, etc.) are not well suited for extended operation in such a harsh environment. This work discusses the potential for using fiber optic-based instrumentation in high temperature irradiation experiments. The primary limitation of fiber optic instrumentation in irradiation experiments is signal darkening due to attenuation in the fiber material. A computational model has been developed to predict broadband optical attenuation in fused silica fiber materials as a function of time, temperature, and dose. Preliminary results obtained using this model are shown for one cycle of irradiation in the high flux isotope reactor at various temperatures. An irradiation campaign has been initiated to provide temperature-dependent optical attenuation data at high dose in order to validate the predictive model. Demonstration of the safety and reliability of new and enhanced nuclear fuels and materials is essential for improving the safety and reliability of existing nuclear power plants and for the licensing and operation of advanced nuclear reactor technologies. Experimental validation of fuel performance codes requires high fidelity measurements during instrumented irradiation experiments. Therefore, a clear need exists for sensors of unprecedented accuracy, resolution, time/space/energy spectrum dependence, reduced size, and, perhaps most importantly, performance in harsh environments. The harsh environment during accelerated irradiation testing could include temperatures from 300 deg. C up to 2600 deg. C, and radiation damage levels ranging from 1 to greater than 100 dpa. Optical fiber-based sensors are a promising candidate for instrumentation in high temperature irradiation environments. Optical fibers are small, inexpensive, chemically inert, immune to electromagnetic interference, and made of high temperature radiation-hard materials. The ability to make distributed measurements of temperature or strain using a single inexpensive optical fiber currently exists for non-extreme environments as commercially available technology. Other advanced sensing technologies such as laser ultrasound, borescopes, and laser-induced breakdown spectroscopy use fiber optic light delivery as a critical component of the sensor design. Some potential applications for optical fiber-based sensors in instrumented irradiation experiments include in-situ measurements of thermal conductivity, ultrasonic measurement of elastic constants (with fiber optic delivery of signal for generation and detection of ultrasonic wave), and distributed measurements of temperature and/or strain (i.e., swelling). The primary limitation for the use of optical technologies for harsh environment (e.g., high neutron flux reactor environments) instrumentation is the attenuation of the light signal due to the effects of temperature and/or irradiation. This work summarizes initial efforts towards developing a predictive model of temperature-dependent radiation-induced attenuation in fused silica optical fibers at high dose. If there is adequate transmission in the fibers, fiber optic-based instrumentation could provide highly accurate distributed measurements during instrumented fuel/material irradiation experiments. Preliminary results show attenuation on the order of 5- 10 dB/m in the wavelength range of 750-900 nm at temperatures of 300 deg. C and below after one HFIR cycle (24 days). At higher temperatures (600 and 900 deg. C), the attenuation is reduced below 5 dB/m in the same wavelength range. This amount of attenuation is acceptable for most fiber optic based sensor systems with a dynamic range on the order of 20-50 dB for a reasonable length (1-2 meters) of fiber in the high flux region. Many optical components use a wavelength of 850 nm, which lies in the low attenuation window. In order to refine and ultimately validate the predictive model of optical fiber attenuation, a reactor irradiation campaign has been initiated. Rabbit irradiation capsules have been designed to irradiate optical fiber material (low and high OH fused silica, as well as single crystal sapphire) specimens in the HFIR at temperatures ranging from 100 to 1200 deg. C. (authors)

42 ENGINEERING↗