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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High Dose Rate Irradiations of Enduray Vision System for Nuclear Inspections

Higher radiation-hardened video cameras are needed in the operation and remote handling of equipment in nuclear reactor inspection and refueling applications. Vega Wave Systems, Inc. has developed a radiation-hardened vision system for nuclear energy applications. This vision system has been developed under several small business innovative research programs (SBIRs) from the U.S. Department of Energy, and the previous GAIN voucher program at Argonne National Laboratory (ANL) was successful in demonstrating that a prototype of the camera is radiation-hard up to at least 525 kGy (5.25 × 106 rad, Si equivalent) at dose rates of 10 kGy/hr with no measurable degradation in image quality and no measurable radiation-induced noise (RIN). Vega Wave Systems has developed a new version of the camera with more than 3X the resolution using a new design and new components, and this new design requires radiation-hardness qualification for marketplace acceptance. The program described in this report provided high radiation-hardness testing of this redesigned high-resolution vision system using the Argonne Low-Energy Accelerator Facility (LEAF). This report presents the results of irradiation tests performed on Vega Wave System’s redesigned high resolution vision system at a dose rate of 9.3 kGy/hr and up to total doses of 1823 kGy. This was an accumulation of 197 hours of irradiation. The results were excellent, providing proof of the redesigned high-resolution vision system’s immunity to high levels of radiation.

42 ENGINEERING↗
DOE OSTI2015

Single-molecule-sensitive fluorescence resonance energy transfer in freely-diffusing attoliter droplets

Fluorescence resonance energy transfer (FRET) from individual, dye-labeled RNA molecules confined in freely-diffusing attoliter-volume aqueous droplets is carefully compared to FRET from unconfined RNA in solution. The use of freely-diffusing droplets is a remarkably simple and high-throughput technique that facilitates a substantial increase in signal-to-noise for single-molecular-pair FRET measurements. We show that there can be dramatic differences between FRET in solution and in droplets, which we attribute primarily to an altered pH in the confining environment. We also demonstrate that a sufficient concentration of a non-ionic surfactant mitigates this effect and restores FRET to its neutral-pH solution value. At low surfactant levels, even accounting for pH, we observe differences between the distribution of FRET values in solution and in droplets which remain unexplained. Our results will facilitate the use of nanoemulsion droplets as attoliter volume reactors for use in biophysical and biochemical assays, and also in applications such as protein crystallization or nanoparticle synthesis, where careful attention to the pH of the confined phase is required.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

Gas and liquid measurements in air-water bubbly flows

Local measurements of gas- and liquid-phase flow parameters are conducted in an air-water two-phase flow loop. The test section is a vertical pipe with an inner diameter of 50 mm and a height of 3.2 m. The measurements are performed at z/D = 10. The gas-phase measurements are performed using a four-sensor conductivity probe. The data taken from this probe are processed using a signal processing program to yield radial profiles of the void fraction, bubble velocity, and interfacial area concentration. The velocity measurements of the liquid-phase are performed using a state-of-the-art Particle Image Velocimetry (PIV) system. The raw PIV images are acquired using fluorescent particles and an optical filtration device. Image processing is used to remove noise in the raw PIV images. The statistical cross correlation is introduced to determine the axial velocity field and turbulence intensity of the liquid-phase. Measurements are currently being performed at z/D = 32 to provide a more complete data set. These data can be used for computational fluid dynamic model development and validation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

X-ray diagnostic developments in the perspective of DEMO

Soft X-ray diagnostics at present are not adequate for a burning plasma experiment, neither in term of hardware nor as diagnostic conception. Detectors have to be radiation tolerant, easily shielded, with low sensitivity to neutrons and gammas and with energy discrimination. Layout and viewing capability should be more flexible, thanks to the use also of optical devices, going toward a configuration intermediate between discrete tomography and pure imaging. The general conception of these diagnostics should therefore evolve in the direction of pattern recognition for a real time feedback. This work is focused on the diagnostic developments undertaken at the ENEA- Frascati X-ray Laboratory, following in particular three directions: gas detector for fast and advanced high density tomography, C-MOS solid state imaging detectors for slow control and X-ray polycapillary optics. GEM gas detectors in photon counting mode (noise free) were developed in the range 1-30 keV having high efficiency, high time resolution (up to microseconds), energy discrimination in bands and optical flexibility. Discrimination of X-rays, neutrons and gammas has been demonstrated, thanks to the combination of intrinsic gain and discrimination thresholds, at neutron fluxes (10{sup 7} n/s*cm{sup 2}) comparable with the expected ones at the ports of ITER. GEM detectors are also extremely flexible in the design, allowing optimization of the measurements and solutions for shielding or minimization of the effect of background radiation. Two solid state C-MOS imagers working in photon counting mode, one based on Si semiconductor (Medipix-2, range 5-30 keV) and the other one having a CdTe sensor (Pixirad, range 2-100 keV) have been characterized in laboratory. C-MOS imagers have features and performances thoroughly complementary to the GEM detector and, thanks to their higher pixel density, could be used as remote imaging detectors coupled to optics. X-ray polycapillary lenses have been therefore studied in the laboratory both as imaging optical device (full lens) or to define a line of sight (cylinder lens); the preliminary results are encouraging toward the goal of using these lenses to transport X-ray radiation far from the reactor. Reflective or diffractive X-ray optics can be also an option for tomography. A GEM detector has been installed at KSTAR and in the next future hopefully the other approaches will be tested there: once their feasibility will be demonstrated, the issue of the improvement of the radiation tolerance will be faced and the development of algorithms for data analysis as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Using quantum noise correlation analysis to measure ion temperature

Quantum noise correlation analysis was tested at the proof-of-concept level as a technique to measure ion temperature in a plasma. If eventually successful, this technique could enable a compact, inexpensive, and robust ion temperature diagnostic suitable for a burning plasma environment. Ion temperature is a key parameter determining the fusion performance of a burning plasma, as the fusion cross-section has a strong dependence on ion temperature. This ion temperature diagnostic would require only a small optical view of the plasma through a port to passively record impurity line emission. The instrumentation would be remote from the reactor behind the neutron and bio-shielding. The technique relies solely on quantum correlations of the photons emitted by a plasma impurity to measure ion temperature; there is no grating dispersion of an emission line-width or pulse-height analysis of photon energy. This measurement innovation was tested with instrumentation consisting of two single-photon detectors with high timing resolution, a time-tagging unit, and simple light collection optics. This instrumentation measures the second-order correlation between the light intensity falling on the two detectors. The next steps beyond the proof-of-concept level will be development of diagnostic designs for application of this technique to high-temperature and burning plasmas. Arrays of single-photon avalanche detectors to multiplex measurements of photon correlation will be required to reduce signal integration time to an acceptable duration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1995

Performance and optimization of a combustion interface for isotope ratio monitoring gas chromatography/mass spectrometry

Conditions and systems for on-line combustion of effluents from capillary gas chromatographic columns and for removal of water vapor from product streams were tested. Organic carbon in gas chromatographic peaks 15 s wide and containing up to 30 nanomoles of carbon was quantitatively converted to CO2 by tubular combustion reactors, 200 x 0.5 mm, packed with CuO or NiO. No auxiliary source of O2 was required because oxygen was supplied by metal oxides. Spontaneous degradation of CuO limited the life of CuO reactors at T > 850 degrees C. Since NiO does not spontaneously degrade, its use might be favored, but Ni-bound carbon phases form and lead to inaccurate isotopic results at T < 1050 degrees C if gas-phase O2 is not added. For all compounds tested except CH4, equivalent isotopic results are provided by CuO at 850 degrees C, NiO + O2 (gas-phase mole fraction, 10(-3)) at 1050 degrees C and NiO at 1150 degrees C. The combustion interface did not contribute additional analytical uncertainty, thus observed standard deviations of 13C/12C ratios were within a factor of 2 of shot-noise limits. For combustion and isotopic analyses of CH4, in which quantitative combustion required T approximately 950 degrees C, NiO-based systems are preferred, and precision is approximately 2 times lower than that observed for other analytes. Water must be removed from the gas stream transmitted to the mass spectrometer or else protonation of CO2 will lead to inaccuracy in isotopic analyses. Although thresholds for this effect vary between mass spectrometers, differential permeation of H2O through Nafion tubing was effective in both cases tested, but the required length of the Nafion membrane was 4 times greater for the more sensitive mass spectrometer.

NASA Discipline Exobiology↗
DOE OSTI2016

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy's Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II and C) pathway of the program aims to increase the role of advanced II and C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies. The development of a prompt system entailed significant performance optimization, including the use of parallel processing, parallel communication, modularity, noise filtering, and frequency tuning. A robust system was achieved by enforcing a persistent continuous data exchange that automatically detects and conveys a failure of any link or component in any part of the system, and that automatically restores the communication once the link or component is restored. An expandable topology was enabled by modularity and load sharing. The number of servers, mobile devices, and field instruments is not limited from a system structure point of view. The system interoperability was achieved by enforcing the independence of the field communication application from the mobile device application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Prediction on Underestimation of Statistical Uncertainty in Monte Carlo Eigenvalue Calculation for Two-dimensional Heterogeneous Color Set Geometry

In a Monte Carlo calculation, statistical uncertainty is inevitably included in the result. The statistical uncertainty is commonly estimated by the central limit theorem without considering correlation among generations. The statistical uncertainty is usually expected to decrease at the inverse square root of the number of neutron histories. However, in a Monte Carlo eigenvalue calculation in a large geometry whose dominance ratio is close to unity, the central limit theorem would not be valid and thus the statistical uncertainty of fission source distribution can be significantly underestimated when inter-cycle correlation is not appropriately taken into account. The true statistical uncertainty can be calculated by statistical processing of the results obtained by multiple Monte Carlo runs using different initial random seeds, but this approach has a drawback of large calculation cost. Therefore, prediction of true statistical uncertainty by alternate approach is desirable. One of the solutions for this issue is an evaluation method of statistical uncertainty based on the eigenfunction expansion and the Autoregressive model (AR model). In this method, the true statistical uncertainty is theoretically derived by applying the AR model to behavior of expansion coefficients of eigenfunction in fission source distribution during cycles. Underestimation ratio of statistical uncertainty of fission source distribution can be predicted by this method. Note that the underestimation ratio of statistical uncertainty is defined by the ratio of estimated error by a Monte Carlo calculation to the true statistical error. In the previous study, the proposed method was verified in a simple condition such as one energy group, one dimensional homogeneous slab geometry. Contributions of this summary are as follows. Firstly, expression of the noise term that is appeared in the AR model is theoretically derived. Secondly, prediction on underestimation ratio of statistical uncertainty is carried out in a more general case, i.e., flux of each fuel cell in 2 x 2 heterogeneous assembly geometry taken from the C5G7 benchmark problem. Through the present study, applicability of the theoretical prediction for underestimation of statistical uncertainty in practical problems will be verified. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Characterization of Used Nuclear Fuel with Multivariate Analysis for Process Monitoring

The Multi-Isotope Process (MIP) Monitor combines gamma spectroscopy and multivariate analysis to detect anomalies in various process streams in a nuclear fuel reprocessing system. Measured spectra are compared to models of nominal behavior at each measurement location to detect unexpected changes in system behavior. In order to improve the accuracy and specificity of process monitoring, fuel characterization may be used to more accurately train subsequent models in a full analysis scheme. This paper presents initial development of a reactor-type classifier that is used to select a reactor-specific partial least squares model to predict fuel burnup. Nuclide activities for prototypic used fuel samples were generated in ORIGEN-ARP and used to investigate techniques to characterize used nuclear fuel in terms of reactor type (pressurized or boiling water reactor) and burnup. A variety of reactor type classification algorithms, including k-nearest neighbors, linear and quadratic discriminant analyses, and support vector machines, were evaluated to differentiate used fuel from pressurized and boiling water reactors. Then, reactor type-specific partial least squares models were developed to predict the burnup of the fuel. Using these reactor type-specific models instead of a model trained for all light water reactors improved the accuracy of burnup predictions. The developed classification and prediction models were combined and applied to a large dataset that included eight fuel assembly designs, two of which were not used in training the models, and spanned the range of the initial 235U enrichment, cooling time, and burnup values expected of future commercial used fuel for reprocessing. Error rates were consistent across the range of considered enrichment, cooling time, and burnup values. Average absolute relative errors in burnup predictions for validation data both within and outside the training space were 0.0574% and 0.0597%, respectively. The errors seen in this work are artificially low, because the models were trained, optimized, and tested on simulated, noise-free data. However, these results indicate that the developed models may generalize well to new data and that the proposed approach constitutes a viable first step in developing a fuel characterization algorithm based on gamma spectra.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

PEDOT:PSS-based Multilayer Bacterial-Composite Films for Bioelectronics

Abstract Microbial electrochemical systems provide an environmentally-friendly means of energy conversion between chemical and electrical forms, with applications in wastewater treatment, bioelectronics, and biosensing. However, a major challenge to further development, miniaturization, and deployment of bioelectronics and biosensors is the limited thickness of biofilms, necessitating large anodes to achieve sufficient signal-to-noise ratios. Here we demonstrate a method for embedding an electroactive bacterium, Shewanella oneidensis MR-1, inside a conductive three-dimensional poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) matrix electropolymerized on a carbon felt substrate, which we call a multilayer conductive bacterial-composite film (MCBF). By mixing the bacteria with the PEDOT:PSS precursor in a flow-through method, we maintain over 90% viability of S. oneidensis during encapsulation. Microscopic analysis of the MCBFs reveal a tightly interleaved structure of bacteria and conductive PEDOT:PSS up to 80 µm thick. Electrochemical experiments indicate S. oneidensis in MCBFs can perform both direct and riboflavin-mediated electron transfer to PEDOT:PSS. When used in bioelectrochemical reactors, the MCBFs produce 20 times more steady-state current than native biofilms grown on unmodified carbon felt. This versatile approach to control the thickness of bacterial composite films and increase their current output has immediate applications in microbial electrochemical systems, including field-deployable environmental sensing and direct integration of microorganisms into miniaturized organic electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

LOITA: Lunar Optical/Infrared Telescope Array

LOITA (Lunar Optical/Infrared Telescope Array) is a lunar-based interferometer composed of 18 alt-azimuth telescopes arranged in a circular geometry. This geometry results in excellent uv coverage and allows baselines up to 5 km long. The angular resolution will be 25 micro-arcsec at 500 nm and the main spectral range of the array will be 200 to 1100 nm. For infrared planet detection, the spectral range may be extended to nearly 10 mu m. The telescope mirrors have a Cassegrain configuration using a 1.75 m diameter primary mirror and a 0.24 m diameter secondary mirror. A three-stage (coarse, intermediate, and fine) optical delay system, controlled by laser metrology, is used to equalize path lengths from different telescopes to within a few wavelengths. All instruments and the fine delay system are located within the instrument room. Upon exiting the fine delay system, all beams enter the beam combiner and are then directed to the various scientific instruments and detectors. The array instrumentation will consist of CCD detectors optimized for both the visible and infrared as well as specially designed cameras and spectrographs. For direct planet detection, a beam combiner employing achromatic nulling interferometry will be used to reduce star light (by several orders of magnitude) while passing the planet light. A single telescope will be capable of autonomous operation. This telescope will be equipped with four instruments: wide field and planetary camera, faint object camera, high resolution spectrograph, and faint object spectrograph. These instruments will be housed beneath the telescope. The array pointing and control system is designed to meet the fine pointing requirement of one micro-arcsec stability and to allow precise tracking of celestial objects for up to 12 days. During the lunar night, the optics and the detectors will be passively cooled to 70-80 K temperature. To maintain a continuous communication with the earth a relay satellite placed at the L4 libration point will be used in conjunction with the Advanced Tracking and Data Relay Satellite System (ATDRSS). Electrical power of about 10 kW will be supplied by a nuclear reactor based on the SP-100 technology. LOITA will be constructed in three phases of six telescopes each. The total mass of the first operational phase is estimated at 58,820 kg. The cost of the fully operational first phase of the observatory is estimated at $8.9 billion. LOITA's primary objectives will be to detect and characterize planets around nearby stars (up to ten parsec away), study physics of collapsed stellar objects, solar/stellar surface features and the processes in nuclear regions of galaxies and quasars. An interferometric array such as LOITA will be capable of achieving resolutions three orders of magnitude greater than Hubble's design goal. LOITA will also be able to maintain higher signal to noise ratios than are currently attainable due to long observation times available on the moon.

Source record↗
NASA NTRS1992

PARAS program: Phased array radio astronomy from space

An orbiting radio telescope is proposed which, when operated in a Very Long Baseline Interferometry (VLBLI) scheme, would allow higher (than currently available) angular resolution and dynamic range in the maps, and the ability of observing rapidly changing astronomical sources. Using a passive phases array technology, the proposed design consists of 656 hexagonal modules forming a 150 meter diameter dish. Each observatory module is largely autonomous, having its own photovoltaic power supply and low-noise receiver and processor for phase shifting. The signals received by the modules are channeled via fiber optics to the central control computer in the central bus module. After processing and multiplexing, the data is transmitted to telemetry stations on the ground. The truss frame supporting each observatory pane is a hybrid structure consisting of a bottom graphite/epoxy tubular triangle and rigidized inflatable Kevlar tubes connecting the top observatory panel and bottom triangle. Attitude control and stationkeeping functions are performed by a system of momentum wheels in the bus and four propulsion modules located at the compass points on the periphery of the observatory dish. Each propulsion module has four monopropellant thrusters and six hydrazine arcjets, the latter supported by a nuclear reactor. The total mass of the spacecraft is 22,060 kg.

Jakubowski, Antoni K.↗
DOE OSTI2025

Neural network-based classification and regression of magnetohydrodynamic modes in tokamaks

We present a machine learning-based magnetohydrodynamic (MHD) classifier and regressor that utilizes real or complex-valued 3D magnetic sensor array data to determine neoclassical tearing mode (NTM) onset times in tokamaks with millisecond accuracy. The input dataset consists of poloidal profiles of complex Fourier amplitudes with an n = 1 toroidal mode number from 144 human-labeled ITER Baseline Scenario discharges in the DIII-D tokamak, spanning both tearing-dominated and sawtooth-dominated regimes. Since m, n = 2,1 NTMs frequently emerge alongside sawteeth at the same frequency in this scenario, the focus is on isolating the m = 1 and m = 2 components of the n = 1 MHD mode near the tearing onset. To improve model regularization and prediction stability, singular value decomposition was applied to balance the sawtooth and tearing datasets. The enriched datasets facilitated training neural networks that learn the key distinguishing features of sawtooth and tearing modes in the poloidal profiles of their magnetic amplitude and phase. When the modes occur independently, the networks achieve perfect classification due to the modes’ distinct characteristics and low measurement noise. In the more experimentally relevant case where both modes coexist, the networks maintain exceptional performance across key metrics. Tests on synthetic data with known ground truth demonstrate the superior accuracy of the neural network trained on complex-valued input compared to models using real amplitude, phase, or pseudo-complex data, achieving both a mean time delay and standard deviation below 1 ms. Notably, standard linear regression methods fitting the dominant singular modes to the data closely match the neural network’s performance. Applying these methods across a broad range of H-mode scenarios will enable future studies to systematically identify dominant NTM triggers as scenario-specific variables, paving the way for more effective tearing mode avoidance strategies in future fusion reactor designs.

machine learning↗
DOE OSTI2015

Sealable femtoliter chamber arrays for cell-free biology

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g. global gene expression, cell division) encountered within living cells. However, such systems, used in conventional macro-scale bulk reactors, often fail to exhibit the dynamic behaviors and efficiencies characteristic of their living micro-scale counterparts. Understanding the impact of internal cell structure and scale on reaction dynamics is crucial to understanding complex gene networks. Here we report a microfabricated device that confines cell-free reactions in cellular scale volumes while allowing flexible characterization of the enclosed molecular system. This multilayered poly(dimethylsiloxane) (PDMS) device contains femtoliter-scale reaction chambers on an elastomeric membrane which can be actuated (open and closed). When actuated, the chambers confine Cell-Free Protein Synthesis (CFPS) reactions expressing a fluorescent protein, allowing for the visualization of the reaction kinetics over time using time-lapse fluorescent microscopy. Lastly, we demonstrate how this device may be used to measure the noise structure of CFPS reactions in a manner that is directly analogous to those used to characterize cellular systems, thereby enabling the use of noise biology techniques to characterize CFPS gene circuits and their interactions with the cell-free environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Development and applications of retro-reflective surfaces for ultrasound in LBE

The Belgian Nuclear Research Centre SCK-CEN is in the process of developing MYRRHA - a fast flux research reactor to replace the aging BR2. MYRRHA is conceptualized as an accelerator driven system cooled by lead bismuth eutectic mixture (LBE). As LBE is opaque to visual light, ultrasonic measurement techniques are employed as the main technology to provide feedback to submerged operations when needed. Conceptually, MYRRHA is a pool type reactor divided in a cold lower plenum and hot upper plenum separated by a diaphragm that forces the main flow through the core. The main flow is cooled by four heat exchangers and driven by two liquid metal pumps. One of the tasks tackled using ultrasound is locating a potentially lost fuel assembly to assist a recovery operation. As all fuel manipulations in MYRRHA are performed in the lower plenum, a potentially lost fuel assembly is located in the lower plenum. Buoyancy will force the lost fuel assembly to float against the diaphragm unless it is still partially inserted in the core. Because of the latter situation, an ultrasonic scan localizing the fuel assembly should be performed from a large distance to avoid a collision with such a partially inserted fuel assembly. Unfortunately, standard machined stainless steel objects, such as a fuel assembly, reflect an ultrasonic pulse in a specular way which induces stringent requirements on the alignment of the ultrasonic sensor with respect to the fuel assembly as we cannot rely on diffuse reflections and/or scattering of the ultrasonic pulse. Moreover, increasing the distance also increases geometric spreading and absorption of the pulse weakening the signal amplitude even faster to noise levels when deviating from perfect alignment. An alternative approach consists in relying on reflections from the known surroundings: a lost fuel assembly will block the line-of-sight to the diaphragm resulting in an anomaly in the reflection - either a shorter than expected time-of-flight of the pulse or a complete absence of a reflection like a shadow. In that way, it suffices to align the sensor with the diaphragm instead of the fuel assembly which is much easier to achieve as the robotics on which the sensor is mounted move parallel with the diaphragm. The alignment requirement in the latter approach can be further relaxed by using a tiling of retro-reflectors on the lower surface of the diaphragm. In that way, alignment becomes less vital and the main source of acoustic energy loss - geometric spread of the beam - is almost completely removed, leaving only absorption losses. In this paper, we present the first results in developing a retro reflectance surface for ultrasound in LBE. We present experimental results for different designs of retro-reflectors in both water and LBE. We discuss both linear and array retro-reflectors of different sizes and investigate the influence of the main relevant ultrasonic parameters such as wavelength and spot size on the strength of the received reflection under different alignment angles. We also demonstrate how retro-reflective surfaces can be exploited when localizing objects using linear and rotating scanning methods. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Data-driven linear time advance operators for the acceleration of plasma physics simulation

In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗