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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Robust Distribution System Load Restoration With Time-Dependent Cold Load Pickup

Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. Here, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗
DOE OSTI2022

TECHNICAL BACKGROUND FOR THE UPDATE AND EXTENSION OF THE TIME-DEPENDENT ALLOWABLE STRESSES OF TYPE 304H AND 316H STAINLESS STEELS

Type 304H and 316H stainless steels are codified in the ASME Boiler and Pressure Vessel Code for Section III, Division 5, Class A construction for up to 1500F (816C) and 300,000 hours. Extension of the design lifetimes to 500,000 hours has been undertaken by various research projects and by the ASME Section III, Division 5 Code Committees. Due to a long-standing issue related to non-classical creep behavior on the use of the time to the onset of tertiary creep as one of the time-dependent allowable stress criteria, little progress was made in the extension of the time-dependent allowable stresses for Type 304H and 316H stainless steels. A recent effort by Dabrow and Nestell (Impact of Tertiary Creep on Time Dependent Allowable Stresses for Type 304H and 316H Stainless Steels, Report 0300-0003-RPT-001, MPR Associates, Alexandria, VA, 2020) has provided a rational method for the treatment of the highly variable data for the time to onset of tertiary creep. In this paper, the background formulas for determining the time-dependent allowable stress values of Type 304H and 316H stainless steels, as assembled from relevant project work, are presented. These updates and extensions are being recommended to the ASME Code committees for approval, and are subject to change upon feedback from ASME Section III Code committees.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Modified Sand’s Time Incorporating Li-Ion Transport Across the SEI: Basis for Understanding Li Dendrite Formation and Li-Metal Battery Electrolyte Selection

Abstract Understanding the initiation of lithium dendrites remains elusive, largely due to the intricate role of the solid electrolyte interphase (SEI) which forms on the Li surface during electrodeposition. Many studies have utilized the classical Sand’s equation to estimate the onset time when lithium dendrites begin to form. The Sand’s equation provides the time when the cation (Li+) concentration at the electrode-electrolyte interface approaches zero under diffusion-limited conditions in galvanostatic Li electrodeposition. However, recent experimental studies have revealed that the observed lithium dendrite onset time deviates considerably from the Sand’s time. Here, we show that this deviation from classical theory is likely due to the transport of Li+ ions through the SEI - a transport limitation that is much more dominant in controlling dendrite formation. We develop a ‘modified’ Sand's equation, incorporating the SEI layer and the diffusional transport across it to predict Li dendrite onset times. To validate this approach, we conducted Li electrodeposition experiments at various current densities using two distinct organic electrolytes. Analysis of the results demonstrates that the modified Sand's equation provides a more accurate prediction of dendrite onset times, highlighting the importance of incorporating SEI into transport models of Li plating in next-generation rechargeable Li-metal batteries.

Ma, Yuanman (ORCID:0000000200444811)↗
DOE OSTI2022

Time-Based CAN IDS Paper Results Code

Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these “distribution-agnostic” based methods outperform “distribution-based” methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.

Moriano, Pablo [Oak Ridge National Lab. (ORNL), Oa↗
DOE OSTI2021

Evaluating the Lagrangian Evolution of Subtropical Low Clouds in GCMs Using Observations: Mean Evolution, Time Scales, and Responses to Predictors

In this work, a Lagrangian framework is developed to show the daily-scale time evolution of low clouds over the eastern subtropical oceans. An identical framework is applied to two general circulation models (GCMs): the CAM5 and UKMET and a set of satellite observations. This approach follows thousands of parcels as they advect downwind in the subtropical trade winds, comparing cloud evolution in time and space. This study tracks cloud cover, in-cloud liquid water path (CLWP), droplet concentration $N_d$, planetary boundary layer (PBL) depth, and rain rate as clouds transition from regions with predominately stratiform clouds to regions containing mostly trade cumulus. The two models generate fewer clouds with greater $N_d$ relative to observations. Models show stronger Lagrangian cloud cover decline and greater PBL deepening when compared with observations. In comparing frequency distributions of cloud variables over time, it is seen that models generate increasing frequencies of nearly clear conditions at the expense of overcast conditions, whereas observations show transitions from overcast to cloud amounts between 50% and 90%. Lagrangian decorrelation time scales ($\mathcal{e}$-folding time $\tau$) of cloud cover and CLWP are between 11 and 19 h for models and observations, although they are a bit shorter for models. A Lagrangian framework applied here resolves and compares the time evolution of cloud systems as they adjust to environmental perturbations in models and observations. Increasing subsidence in the overlying troposphere leads to declining cloud cover, CLWP, PBL depth, and rain rates in models and observations. Modeled cloud responses to other meteorological variables are less consistent with observations, suggesting a need for continuing mechanical improvements in GCMs.

58 GEOSCIENCES↗
DOE OSTI2023

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real Time Applications Using Linear State Estimation Technology (RTA/LSE)

Electric Power Group, LLC (EPG) was awarded DOE OE0000849 to design, develop, and demonstrate three real-time applications for monitoring power system stability. The applications use phasor measurements and processing by a linear state estimator (LSE) to improve system visibility and accuracy. These applications leverage the large and expanding phasor measurement systems being deployed by utilities throughout the world, and specifically in the United States. Phasor measurements provide a much more detailed view of the power systems than traditional SCADA systems, so can provide better visibility of events and an early warning of developing problems. These three applications are real-time contingency analysis (RTCA), area angle monitoring (AAM), and a voltage stability index (VSI). The project was fully completed as proposed. All three applications were successfully implemented and demonstrated. There were challenges the caused project delays, however. While the RTCA is based on well-known concepts and readily available tools, its deployment using phasor measurements meant it needed to be adapted to sometimes sparse measurements and limited coverage areas. EPG met these challenges with extensive modeling and testing. The AAM is based on unproven research, so EPG had to deal with a lot of unknowns and develop additional methods for practical implementation. These activities took more time than anticipated, so required extra time for development. In addition, there was difficulty getting adequate measurement locations for successful deployment and utility installation delays. Consequently, the project required a time extension to complete. These three real-time applications, RTCA, AAM, and VSI, use only phasor measurement input. Since they do not require the EMS or other measurement systems, they can serve as a backup and security check for the EMS. Phasor measurements are validated and extended by an LSE. The LSE will always produce an output even when some inputs are impaired, so the RT applications will operate even when the EMS state estimator does not converge and the applications it supports cannot function. Consequently, these RT applications can provide valuable additional reliability for control center operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Innovation Flex Time

The authors examine the problem of how to provide a time code for staff to use in pursuit of innovation. Four potential options are explored ranging from not providing funds for this activity, to charging such efforts against existing or expanded program management and program development funds. One solution that provides funded time without raising laboratory overhead rates is identified and referred to as Innovation Flex Time. This would consist of capturing hours worked in excess of the standard work week but not charged to customers and making those hours available to fund time for exploring new ideas. A brief examination of labor relations laws, and laws regulating laboratory directed research and development suggests that Innovation Flex Time is a viable option for the laboratory. However, implementation of Innovation Flex Time would require NNSA approval and modification of the existing management and operations contract.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2022

Demonstration of <2 ns timing resolution for neutrino interaction in the MicroBooNE detector

The MicroBooNE detector, located in the Booster Neutrino Beamline (BNB) at Fermilab, collected data from 2015 to 2021. MicroBooNE’s Liquid Argon Time Projection Chamber is accompanied by a Photon Detection System consisting of 32 PMTs used to measure the argon scintillation light and determine the timing of the neutrino interactions. This work employs improved analysis techniques combining light signals and reconstructed tracks achieving neutrino interaction timing resolution <2 ns. The result obtained allows MicroBooNE to access the 2 ns neutrino pulse structure of the BNB for the first time. The timing resolution achieved enables significant enhancement of cosmic background rejection for all neutrino analyses. Furthermore, the ns timing resolution opens the door for searching new long-lived-particles (e.g. Heavy Neutral Leptons, Higgs Portal Scalars) in MicroBooNE, as well in future large LArTPC experiments, namely SBN and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Reverse Time Migration of Explosion-generated Infrasound and Ground-Coupled Airwaves

Accurately locating sources of seismic and infrasonic energy is integral to global monitoring of earthquakes and explosions. Infrasound arrivals times can be used to calculate the origins of events that generate acoustic energy. Picking times of emergent infrasound arrivals, however, can be difficult and prone to uncertainty. Reverse time migration (RTM) is a waveform based location method that does not rely on picked arrival times. Here we use RTM to locate a known chemical explosion that generated acoustic and acoustic-to-seismic signals on 26 and 108 receivers, respectively. All location predictions are less than 24 km from the known location with time errors of less than three minutes. We find strong overall agreement between our results and those of existing RTM and arrival time based methods. Our initial results suggest that RTM is a promising method of event location using acoustic arrivals recorded on both infrasound and seismic instrumentation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Guidance for Monitoring Passive Groundwater Remedies Over Extended Time Scales

Passive remediation can be appropriate where natural processes and actions such as institutional controls mitigate exposure to contaminated groundwater, achieving remedial action objectives and protectiveness of human health and the environment. Monitored natural attenuation (MNA) is a prevalent passive remediation strategy supported by a regulatory framework and monitoring design guidance. However, long-term passive remedies are usually selected in combination with at least one active remedy, such as source removal, in situ treatment, or pump-and-treat, functioning as a complementary method for achieving remediation objectives and meeting the applicable statutory and regulatory requirements. However, MNA and existing monitoring guidance primarily target situations where the remedial action objectives are met within a few decades. When time scales for passive remediation extend to many decades (50 years or more), a corresponding change in monitoring strategy is needed to adapt to the extended time scale. This document provides guidance for implementing an extended-scale monitoring (ESM) approach appropriate for long-duration passive remediation. Extended-scale is defined in this document with respect to time (i.e., a long duration of remediation) and a large enough physical scale such that downstream receptors will not be impacted within the remediation timeframe. ESM applies to slow-moving groundwater contaminant plumes and emphasizes monitoring primarily for potential exposure pathways. For this approach, the primary monitoring objective is to demonstrate that the plume diminishes before reaching the receptor zone or point of compliance and/or a receptor does not receive concentrations above the compliance limit. While the overall objectives of protecting human health and the environment are the same as for plumes where remediation can occur over a shorter time period, the time scales between decisions are longer and the dynamics of plume evolution are slower. To this end, a scenario-based strategy is described for different plume and source conditions, defining a containment and receptor zones. The containment zone is the area where the risk of exposure to groundwater contamination can be mitigated (e.g., through institutional controls) during the remediation time period. The receptor zone is defined as the area where exposure to groundwater contamination cannot be mitigated and compliance concentration standards must be met. Within the containment zone, slow plume migration may occur, leading to concentrations that exceed compliance standards. However, where distance to the receptor zone is large relative to plume migration and attenuation rate, this approach can be protective of the receptor zone. Selection of a long-duration passive remedy needs to be based on sufficient understanding of contaminant sources, hydrogeology, and contaminant plumes. A strong technical basis, supported by predictive analysis, is recommended to substantiate that contamination is expected to stay within the containment zone during the active remediation and attainment phase of the remedy, and diminish to meet compliance standards within the extended timeframe prior to reaching the receptor zone (e.g., many decades or even centuries). The ESM approach is based on verification of plume behavior and not on detailed plume dynamics. Monitoring is conducted to confirm expected behavior with an emphasis on exposure pathways to verify that plumes remain contained in areas where the protectiveness objectives can be met. ESM should not be adopted if there is significant risk of the plume extending beyond the containment zone. Given the slow movement within the containment zone, less frequent sampling is required relative to approaches used for conventional-scale remediation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Four Channel Time Multiplexed Photonic Doppler Velocimetry using an Optical Switch

Photonic Doppler Velocimetry (PDV) is a diagnostic commonly used in shock physics and dynamic compression experiments to reliably get velocity information from experiments. In PDV systems, a common method of reducing experimental cost is to use time and frequency multiplexing to increase the number of PDV probes. With time multiplexing, interference between probes is a frequent problem. In this report, we look at using a high-speed optical switch to reduce this interference, including measuring the amount of interference generated to determine if it has the potential to affect experiments and integrating a time multiplexing system into an experiment. We find that, when applied to PDV systems, there is approximately (-23.4 ± 0.9) dB of interference measured in the short time Fourier transform between switch inputs. When an optical switch based time multiplexing system was integrated into a dynamic compression experiment, the system was able to successfully combine the signals from four different PDV probes onto a single optical cable without unacceptable levels of interference in the spectrogram. An optical switch based time multiplexing system appears to be a promising method for reducing the cost of fielding larger numbers of PDV probes in an experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Analyze the real-time performance of the optimized fiber-PTR instrument

An instrument to perform in-reactor, real-time thermal property measurements of nuclear fuels and materials was recently designed, optimized, and tested at Massachusetts Institute of Technology Research Reactor. It was the second insertion experiments of a total of two rounds. Here we report the collection and analysis of the real-time captured thermal diffusivity data on the preloaded SiC. With the optimized design, the instrument temperature had been successfully raised as we expected. Only one probe (the top one) returned real-time thermal diffusivity in a time span of approximately two days. Measured thermal diffusivity of the preloaded SiC was significantly lower than the literature value at the same temperature, indicating a significant influence from the irradiation induced microstructure damage. Meanwhile, the real-time thermal diffusivity value continuously reduced with time, indicating the dynamic microstructure evolution. The possible reasons of the probes that did not return data were hypothesized. The further optimization of the instrument with the objective to improve the measurement accuracy and instrument survivability is also discussed.

36 MATERIALS SCIENCE↗