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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Positron stopping in multilayer materials

Positron annihilation spectroscopy provides a sensitive toolset for defect characterization. In beam based studies of single-layer targets, the form of implantation profiles is well established, depending on the kinetic energy and angle of incident positrons relative to the target surface and the density and average atomic number of the target. For multilayer systems, the difference in density and across the layers makes derivation of an analytical form difficult. To date, the determination of positron stopping profiles in multilayer targets has primarily involved Monte Carlo simulations. We present here an alternative approach that estimates the energy distribution dN/dE of those positrons transmitted past each layer boundary, by fitting the remaining tail of the stopping profile after each layer with a basis set comprised of calculated stopping profiles in the same material they are transmitted through. The stopping profile in the next layer is then found by summing a series of stopping profiles in the new medium in proportion to the determined distribution dN/dE. The results of our model are compared with simulation results in a system of alternating layers of Al and Au and find reasonable agreement in the predicted profile and excellent agreement in the predicted mean implantation depth. Finally, we derived a simple formula-based approach for the calculation of the mean implantation depth in two-layer systems that provides results in excellent agreement with the full model.

Jones, A. C. L. [Arizona State University, Tempe, ↗
DOE OSTI2021

Assessment of filtered cameras for quantitative 2D analysis of divertor conditions during detachment in JET L-mode plasmas

We report that estimates for 2D distributions of electron temperature, T e , electron density, n e , and atomic deuterium density, n o , in the JET divertor volume have been inferred from deuterium Balmer line intensity ratios obtained from tomographic reconstructions of divertor camera measurements. This enables also investigation of ionization, S ion , and recombination, S rec , rates. The analysis shows a decrease of T e to 0.5–1.0 eV throughout the outer divertor during detachment in low-confinement (L-mode) plasmas. Simultaneously, the high-n e region and the n 0 distribution in the outer divertor are observed to elongate and shift from the outer strike point towards the X-point. The observations are in qualitative agreement and follow the same sequence with modelling predictions of EDGE2D-EIRENE simulations of a density scan. While the method was found to provide good representation of the evolution of volumetric recombination during detachment, in agreement with the simulations, the movement of the ionization front upstream could not be followed due to lack of spatial overlap between the ionization region and the necessary emission distributions. Consequently, the representation of the ionization conditions and the particle balance in the detached outer divertor are compromised.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Prospects for future studies using deep imaging: analysis of individual Galactic cirrus filaments

The presence of Galactic cirrus is an obstacle for studying both faint objects in our Galaxy and low surface brightness extragalactic structures. With the aim of studying individual cirrus filaments in Sloan Digital Sky Survey (SDSS) Stripe 82 data, we develop techniques based on machine learning and neural networks that allow one to isolate filaments from foreground and background sources in the entirety of Stripe 82 with a precision similar to that of the human expert. Our photometric study of individual filaments indicates that only those brighter than 26 mag arcsec −2 in the SDSS r band are likely to be identified in SDSS Stripe 82 data by their distinctive colours in the optical bands. We also show a significant impact of data processing (e.g. flat-fielding, masking of bright stars, and sky subtraction) on colour estimation. Analysing the distribution of filaments’ colours with the help of mock simulations, we conclude that most filaments have colours in the following ranges: 0.55 ≤g − r ≤ 0.73 and 0.01 ≤ r − i ≤ 0.33. Our work provides a useful framework for an analysis of all types of low surface brightness features (cirri, tidal tails, stellar streams, etc.) in existing and future deep optical surveys. For practical purposes, we provide the catalogue of dust filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dark energy survey year 3 results: likelihood-free, simulation-based w CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow –1 < w < –$\frac{1}{3}$⁠, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Ω m = 0.283$^{+0.020}_{–0.027}$⁠, S 8 = 0.804$^{+0.025}_{–0.017⁠}$, and w < –0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Ω⁠ DE , w⁠) precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Non-Gaussian estimates of tensions in cosmological parameters

We discuss how to efficiently and reliably estimate the level of agreement and disagreement on parameter determinations from different experiments, fully taking into account non-Gaussianities in the parameter posteriors. We develop two families of scalable algorithms that allow us to perform this type of calculations in increasing number of dimensions and for different levels of tensions. One family of algorithms rely on kernel density estimates of posterior distributions while the other relies on machine learning modeling of the posterior distribution with normalizing flows. We showcase their effectiveness and accuracy with a set of benchmark examples and find both methods agree with each other and the true tension within 0.5σ in difficult cases and generally to 0.2σ or better. This allows us to study the level of internal agreement between different measurements of the clustering of cosmological structures from the Dark Energy Survey and their agreement with measurements of the Cosmic Microwave Background from the Planck satellite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

An iterative reconstruction algorithm for pole figure inversion using total variation regularization

This paper describes a new discrete method for inverting X-ray pole figures to estimate the orientation distribution function (ODF). The method employs the equal-volume `cubochoric' representation for uniform discretization of orientation space, SO(3). The forward-projection model is combined with an anisotropic total variation term to iteratively determine the ODF. Here, the efficacy of the new method is evaluated with both model and experimental data and compared with existing discrete and series expansion methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Boundary-Aware Adversarial Learning Domain Adaption and Active Learning for Cross-Sensor Building Extraction

The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained models at scale in real-world scenarios remains a challenging task. The main barrier is that certain new labels are still needed to compensate for domain shifting between the labeled data and new images that potentially cover new geographic locations or that are from a different sensor. In this article, we propose to add informatively labeled samples from a new image pool under the paradigm of active learning. To select the most useful samples based on model uncertainty, we first tackle the problem of uncalibrated uncertainty estimation due to distribution shifting by adapting feature extractors with boundary-based adversarial learning. Calibrated uncertainty is used as the query criterion in the active learning process, where the most uncertain samples are selected for annotation and included for model retraining. The proposed workflow was tested with three data pairs in which each workflow represents a scenario often encountered in real-world applications, including adapting pretrained models to new images collected with different sensors or to new geographic areas where appearances and types of buildings are very different. Compared to several baselines, including random sampling, temperature scaling (a well-known uncertainty calibration technique), different query strategies, and active domain adaptation methods, the proposed workflow shows that strategically querying a smaller set of samples for labeling achieves comparable or better building extraction performance. The proposed method reduces the number of labeled samples required to achieve sufficient model accuracy, thus significantly reducing hundreds of person-hours for labeled data creation. In addition, we include a few considerations when deploying this workflow in a GPU cluster that can be easily adapted to achieve operational building extraction model retraining.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Chemical speciation correlated with microstructural heterogeneity of interdicted uranium materials

Two uranium powders seized by law enforcement in Victoria, Australia, have been characterized by established nuclear forensic methods in a previously published study. Here, in this work, the results of further characterization by a scanning transmission x-ray microscope (STXM) operating in the soft x-ray regime are reported. STXM images are used to estimate the elemental distribution in micrometer-scale particles of each powder, and oxygen K-edge absorption spectra are used to determine the chemical state of uranium. The results of the current study are consistent with the previous analysis; the first powder is found to be a potassium-uranium hydrate, while the second powder is determined to be a mixture of uranium oxides primarily consisting of UO 3 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

Study of the Effective Refractive Index Profile in Self-Assembling Nanostructured ITO Films

The optical characteristics and structural features of self-assembling nanostructured indium–tin oxide (ITO) films deposited onto substrates heated above 400°C are studied. Estimations of the distribution profiles of the material and effective refractive index in the films under study are obtained by computer simulation of a medium having spectral dependences of light transmission and reflection coefficients closest to those observed in the experiment. These results are in good agreement with scanning electron microscopy data for these films and make it possible to not only confirm the gradient character of such coatings but also restore some of its features. The further overgrowth of voids in self-assembling nanostructured films by means of the deposition of an additional material amount by magnetron sputtering at room temperature leads to a variation in the effective refractive index profile in them. Thus, it is possible to form transparent conductive films with an efficient refractive index profile adjusted for specific tasks. Adjustment of the refractive index profile in self-assembled ITO films acquires a special value for designing coatings with specified properties by virtue of a limited set of transparent conductive materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nonparametric Inference for the Reproductive Rate in Generalized Compartmental Models

We develop a tractable nonparametric model for the time-varying reproductive rate of infectious diseases that combines the structure of a deterministic compartmental model and a stochastic model for incidence data. We use Bayesian inference to estimate, with uncertainty, the reproductive rate of the Coronavirus 2019 outbreak in the U.S. states of California, Florida, Michigan, New Mexico, New York, and Texas from January 2020 to March 2022. Employing the inferred reproductive rates, we estimate the posterior distribution of the time-varying reproduction numbers for each state. Compering the time-varying reproduction numbers across the states, we identify some epidemic waves, potentially driven from changes in human behavior and virus mutations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Light element ($$Z=1,2$$) production from spontaneous ternary fission of $$^{252}$$Cf

Abstract The yields of light elements ( $$Z=1,2$$ Z = 1 , 2 ) obtained from spontaneous ternary fission of $$^{252}$$ 252 Cf are treated within a nonequilibrium approach, and the contribution of unstable nuclei and excited bound states is taken into account. These light cluster yields may be used to probe dense matter, and to infer in-medium corrections such as Pauli blocking which is determined by the nucleon density. Continuum correlations are calculated from scattering phase shifts using the Beth-Uhlenbeck formula, and the effect of medium modification is estimated. The relevant distribution is reconstructed from the measured yields of isotopes. This describes the state of the nucleon system at scission and cluster formation, using only three Lagrange parameters which are the nonequilibrium counterparts of the temperature and chemical potentials, as defined in thermodynamic equilibrium. We concluded that a simple nuclear statistical equilibrium model neglecting continuum correlations and medium effects is not able to describe the measured distribution of H and He isotopes. Moreover, the freeze-out concept may serve as an important ingredient to the nonequilibrium approach using the relevant statistical operator concept.

Röpke, G.↗
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 OSTI2024

Plastics Environmental Risk Calculator

SF-24-074 The Plastics Environmental Risk Calculator (PERC) was developed in Microsoft Excel and estimates the environmental distribution and lifetime of new biobased and conventional plastics from commonly measured properties of the plastics. A Random Forest regression model embedded in the calculator calculates plastic degradation rates and lifetimes as a proxy for environmental risk. Model default assumptions may be overwritten by the user.

Beckman, Kevin [Argonne National Laboratory (ANL),↗
DOE OSTI2018

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even with gradient information provided. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this work, we propose a novel Bayesian stochastic inversion methodology, characterized by a tight coupling between a gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). This approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated spatial random field. Moreover, non-Gaussian full posterior probability distribution functions are estimated via an efficient LMCMC method on both the projected low-dimensional feature space and the recovered high-dimensional parameter space. We demonstrate this computational framework by integrating and adapting recent developments such as data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to solve inverse problems in linear elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Methodology for Irradiation Creep Testing of SiC / SiC Composite Cladding

Irradiation creep compliance is a critical parameter for evaluating the stress evolution of silicon carbide (SiC) components during operation in various reactor concepts. Recent instrumented irradiation creep testing of SiC, performed at low dose in the Halden reactor, showed a creep compliance that is orders of magnitude higher than previous un-instrumented bend relaxation experiments performed in the High Flux Isotope Reactor (HFIR). This discrepancy illustrates the need for additional irradiation creep data for SiC. To this end, a novel irradiation capsule design has been developed to test miniature SiC tensile specimens under loading during irradiation in the HFIR. The experiment design uses the coolant pressure of the HFIR to compress a bellows, which applies the loading on the specimen. Preliminary thermal finite element models were developed to estimate the temperature distribution within the specimen and surrounding capsule components. Similar structural models were developed to evaluate the stress distribution within the specimen. The thermal analyses show that within the gauge section, the specimen temperatures remain within ~10°C of the nominal 300°C design temperature. Similarly, the structural analysis predicts axial stresses within ~10 MPa of the target stress of 100 MPa. These initial analyses show that irradiation creep testing of SiC in the HFIR is feasible and could provide a low-cost, high-throughput vehicle for gathering needed irradiation creep data.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Water-Energy Considerations in California’s Agricultural Sector and Opportunities to Provide Flexibility to California’s Grid

Water and energy use on farms are deeply linked, and trends changing the way water is used on farms have implications for the electrical grid, and vice versa. In 2014, California’s agricultural sector accounted for approximately 80% of the state’s water consumption and 5% of its electricity use. The majority of the electricity was for surface conveyance and groundwater pumping. Diminishing surface water availability and increasing reliance on groundwater pumping are likely to increase future energy demand. These trends are coincident with farms embracing new precision irrigation technologies that increase water productivity and crop yield, but may have the potential of other collateral effects, such as increasing energy intensity of irrigation and total electricity use, and thus demand on the grid. The impacts of these technologies and their loads on the electrical grid have been explored only to a limited degree, and the potential grid benefits afforded by these technologies have been studied even less. For example, studies show that California’s increasing adoption of renewable electricity may result in excess generation during certain periods of the day, and that responsive load management (i.e. demand response) may be a cost-effective method to shift loads to utilize this excess generation. The degree to which farms in California do or can provide responsive loads has not been explored. In this paper, we explore whether farms that are adopting technologies and automation for irrigation management can provide co-benefits to the grower and the electrical grid. To do so, we define the characteristics of future grid needs specifically related to responsive load management, explore existing market mechanisms and policies for proving those resources, estimate the temporal distribution of energy use for irrigation in California, and develop scenarios of how irrigation loads might meet these needs. We conclude by exploring potential ancillary service benefits and associated revenues that California’s agricultural industry may provide. Ancillary services include using loads to dynamically adjust demand on the system to alleviate short-run ramps and disturbances at timescales ranging from seconds up to an hour. With higher penetrations of renewable resources, larger quantities of ancillary services will be necessary and may become more valuable to the grid than traditional demand response. Ancillary services from agricultural loads is a nascent topic, and no such analysis has been conducted to quantify its benefits to our knowledge.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios

This NEUP project #15-8205 entitled “Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios”, has investigated important phenomena in the safety of Very High Temperature Reactors (VHTRs) using the experimental facilities at City College of New York (CCNY) and Kansas State University (KSU), in collaboration with the Idaho State University (ISU) and Idaho National Laboratory (INL). The main objectives of this project were to investigate the forced convection and bypass flow phenomena, natural circulation flow and heat transfer, and graphite oxidation due to air ingress which could occur in a Very High Temperature Reactor (VHTR) with a prismatic core. High pressure/high temperature experiments have been conducted to obtain data that could be used for validation of VHTR design and safety analysis codes. The focus of these experiments was on the generation of benchmark data for design and off-design heat transfer for forced and natural circulation in a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions. The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulationin a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions.The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulation(ONC), molecular diffusion plays a significant role in air-ingress, however, at higher temperatures convection currents may be influencing air ingress and in-turn ONC times. Bypass flow experiments faced difficulties in the measurement of gas velocity in the main channel due to the failure of a high temperature Hot Wire Anemometer probe, so an energy balance method was instead employed to estimate the flow distribution between the main and bypass flow channels. In the graphite oxidation experiments conducted at KSU, oxidation was found to increase the thermal diffusivity of nuclear grade graphite. This change is believed to be driven by oxidation decreasing graphite sample density rather than raising the thermal conductivity. Oxidation was also shown to greatly alter graphite emissivity. If large amounts of impurities have built up within the graphite over time and have significantly increased its effective ash content, then air ingress is likely to severely inhibit the radiative heat transfer abilities of the graphite due to the formation of low emissivity, ash layers on its surface. However, if the purity of the graphite at the time of the air ingress is still close to that of its virgin specifications, the oxidation induced roughening of the graphite’s outer surface would have the effect of slightly raising its emissivity. The flow laminarization phenomenon was investigated by INL by examining the results of Direct Numerical Simulations of previous experiments, and by CCNY conducting its own DNS simulations using DOE’s Nek5000 code

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

GADRAS-DRF Version 18 User's Manual

The Gamma Detector Response and Analysis Software Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation and provides analysis on measured spectra. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, estimating source energy distributions from measured spectra, and creating inject data. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗