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At least 1,027 records · Page 57

Innovative Use of Cr(VI) Plume Depictions and Pump-and-Treat Capture Analysis to Estimate Risks of Contaminant Discharge to Surface Water at Hanford Reactor Areas

The Hanford Site nuclear reactor operations required large quantities of high-quality cooling water, which was treated with chemicals including sodium dichromate dihydrate for corrosion control. Cooling water leakage, as well as intentional discharge of cooling water to ground during upset conditions, produced extensive groundwater recharge mounds consisting largely of contaminated cooling water and resulted in wide distribution of hexavalent chromium (Cr[VI]) contamination in the unconfined aquifer. The 2013 Cr(VI) groundwater plumes in the 100 Areas cover approximately 6 km2 (1500 acres), primarily in the 100-HR-3 and 100-KR-4 groundwater operable units (OUs). The Columbia River is a groundwater discharge boundary; where the plumes are adjacent to the Columbia River there remains a potential to discharge Cr(VI) to the river at concentrations above water quality criteria. The pump-and-treat systems along the River Corridor are operating with two main goals: 1) protection of the Columbia River, and 2) recovery of contaminant mass. An evaluation of the effectiveness of the pump-and-treat systems was needed to determine if the Columbia River was protected from contamination, and also to determine where additional system modifications may be needed. In response to this need, a technique for assessing the river protection was developed which takes into consideration seasonal migration of the plume and hydraulic performance of the operating well fields. Groundwater contaminant plume maps are generated across the Hanford Site on an annual basis. The assessment technique overlays the annual plume and the capture efficiency maps for the various pump and treat systems. The river protection analysis technique was prepared for use at the Hanford site and is described in detail in M.J. Tonkin, 2013. Interpolated capture frequency maps, based on mapping dynamic water level observed in observation wells and derived water levels in the vicinity of extraction and injection wells, are developed initially. Second, simulated capture frequency maps are developed, based on transport modelling results. Both interpolated and simulated capture frequency maps are based on operation of the systems over a full year. These two capture maps are then overlaid on the plume distribution maps for inspection of the relative orientation of the contaminant plumes with the capture frequency. To quantify the relative degree of protection of the river from discharges of Cr(VI) (and conversely, the degree of threat) at any particular location, a systematic method of evaluating and mapping the plume/capture relationship was developed. By comparing the spatial relationship between contaminant plumes and hydraulic capture frequency, an index of relative protectiveness is developed and the results posted on the combined plume/capture plan view map. Areas exhibiting lesser degrees of river protection are identified for remedial process optimization actions to control plumes and prevent continuing discharge of Cr(VI) to the river.

Miller, Chuck W.↗

PROBLEM DEPENDENT DOPPLER BROADENING OF CONTINUOUS ENERGY CROSS SECTIONS IN THE KENO MONTE CARLO COMPUTER CODE

For many Monte Carlo codes cross sections are generally only created at a set of predetermined temperatures. This causes an increase in error as one moves further and further away from these temperatures in the Monte Carlo model. This paper discusses recent progress in the Scale Monte Carlo module KENO to create problem dependent, Doppler broadened, cross sections. Currently only broadening the 1D cross sections and probability tables is addressed. The approach uses a finite difference method to calculate the temperature dependent cross-sections for the 1D data, and a simple linear-logarithmic interpolation in the square root of temperature for the probability tables. Work is also ongoing to address broadening theS (alpha , beta) tables. With the current approach the temperature dependent cross sections are Doppler broadened before transport starts, and, for all but a few isotopes, the impact on cross section loading is negligible. Results can be compared with those obtained by using multigroup libraries, as KENO currently does interpolation on the multigroup cross sections to determine temperature dependent cross-sections. Current results compare favorably with these expected results.

Monte Carlo↗

Sandia Higher Order Elements (SHOE) v 0.5 alpha

SHOE is research code for characterizing and visualizing higher-order finite elements; it contains a framework for defining classes of interpolation techniques and element shapes; methods for interpolating triangular, quadrilateral, tetrahedral, and hexahedral cells using Lagrange and Legendre polynomial bases of arbitrary order; methods to decompose each element into domains of constant gradient flow (using a polynomial solver to identify critical points); and an isocontouring technique that uses this decomposition to guarantee topological correctness. Please note that this is an alpha release of research software and that some time has passed since it was actively developed; build- and run-time issues likely exist.

Source record↗

Development and application of a standardized flow measurement uncertainty analysis framework to various low-head short-converging intake types across the United States federal hydropower fleet

Turbine discharges at low-head short converging intakes are difficult to measure accurately. The proximity of the measurement section to the intake entrance admits large uncertainties related to asymmetry of the velocity profile, swirl, and turbulence. Existing turbine performance codes [10, 24] do not address this special case and published literature is largely silent on rigorous evaluation of uncertainties associated with this measurement context. The American Society of Mechanical Engineers (ASME) Committee investigated the use of Acoustic transit time (ATT), Acoustic scintillation (AS), and Current meter (CM) in a short converging intake at the Kootenay Canal Generating Station in 2009. Based on their findings, a standardized uncertainty analysis (UA) framework for velocity-area method (specifically for CM measurements) is presented in this paper given the fact that CM is still the most fundamental and common type of measurement system. Typical sources of systematic and random errors associated with CM measurements are investigated, and the major sources of uncertainties associated with turbulence and velocity fluctuations, numerical velocity integration technique (bi-cubic spline), and the number and placement of current meters are being considered for an evaluation. Since the velocity measurements in a short converging intake are associated with complex nonlinear and time varying uncertainties (e.g., Reynolds stress in fluid dynamics), simply applying the law of propagation of uncertainty is known to overestimate the measurement variance while the Monte Carlo method does not. Therefore, a pseudo-Monte Carlo simulation method (random flow generation technique [8]) which was initially developed for the purpose of establishing upstream or initial conditions in the Large-Eddy Simulation (LES) and the Direct Numerical Simulation (DNS) is used to statistically determine uncertainties associated with turbulence and velocity fluctuations. This technique is then combined with a bi-cubic spline interpolation method which converts point velocities into a continuous velocity distribution over the measurement domain. Subsequently the number and placement of current meters are simulated to investigate the accuracy of the estimated flow rates using the numerical velocity-area integration method outlined in ISO 3354 [12]. The authors herein consider that statistics on generated flow rates processed with bi-cubic interpolation and sensor simulations are the combined uncertainties which already accounted for the effects of all those three uncertainty sources. A preliminary analysis based on the current meter data obtained through an upgrade acceptance test of a single unit located in a mainstem plant has been presented.

Smith, Brennan T↗

Optimal Temperature Grid for Accurate Doppler Kernel Reconstruction

For computational efficiency, both Monte Carlo and deterministic neutron transport codes often rely on pre-tabulated cross section sets and simple interpolation schemes to represent the Doppler broadening of the cross sections at a needed temperature. Accurate accounting of Doppler effects is of paramount importance for reactor analysis since it impacts the power distribution and the reactor response during transients. Temperature interpolation methods for Doppler broadening have traditionally been physically motivated engineering curve-fits, selected upon best-performance criteria on important nuclides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Guaranteed Quality Conformal Mesh Decomposition.

Interface-conforming elements generated by the conformal decomposition finite element method can have arbitrarily poor quality due to the arbitrary intersection of the base triangular or tetrahedral mesh with material interfaces. This can have severe consequences for both the solvability of linear systems and for the interpolation error of fields represented on these meshes. The present work demonstrates that snapping the base mesh nodes to the interface whenever the interface cuts close to a node results in conforming meshes of good quality. Theoretical limits on the snapping tolerance are derived, and even conservative tolerance choices result in limiting the stiffness matrix condition number to within a small multiple of that of the base mesh. Interpolation errors are also well controlled in the norms of interest. In 3D, use of node-to-interface snapping also permits a simpler and more robust vertex ID-based element decomposition algorithm to be used with no serious detriment to mesh quality.

42 ENGINEERING↗

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of machine learning (ML), specifically neural networks, has grown significantly and has spurred research in its applicability to digital instrumentation and control systems (DI&C). While ML models have shown promise in operational contexts, the trustworthiness of using such algorithms has not been adequately assessed. Failures of ML integrated systems are not well understood, and the lack of comprehensive risk modeling can degrade the trustworthiness in these systems. In recent reports by the National Institute for Standards and Technology (NIST) [1] and the Nuclear Regulatory Commission (NRC) [2], they indicate that trustworthiness in ML is a critical barrier and will play a vital role in the safe, accountable, and secure operation of intelligent systems. Thus, in this work, we demonstrate a dynamic model-agnostic method to quantify the relative reliability of AI/ML predictions by incorporating out-of-distribution (OOD) detection on the training dataset. It is well documented that most ML algorithms excel at interpolation (or near-interpolation) tasks but experience significant performance degradation at extrapolation. The method, referenced as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets which can used to the relative reliability of AI/ML predictions. LADDR is then demonstrated on a feedforward neural network based digital twin used for the prediction of safety significant factors during a loss-of-flow transient. LADDR is used to demonstrate how training data can be used as evidence to support the relative reliability of ML/AI predictions enhancing the overall trustworthiness of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gated truncated readout system

A gated truncated readout system for position sensitive or imaging detectors that improves resolution over traditional readout systems. The readout system includes two or more amplifiers that receive a multichannel output analog data from the detector. Analog gates control circuitry, included in the readout circuit, receives the signals from the amplifiers, determines a fractional value of the sum-integral of the signals, and enables analog gates operation around an area of interest, disabling all other channels where noise dominates the signal value and thereby improving interpolation accuracy of the signals centroid position and the detector resolution. Filtered signals are transmitted to a centroid interpolation signal processing device for computation of the centroid position. As a result disabling all channels where noise dominates the signal value, the gated truncated readout system provides better accuracy improved detector resolution.

Popov, Vladimir↗

Innovative use of Cr(VI) plume depictions and pump-and-treat capture analysis to estimate risks of contaminant discharge to surface water at Hanford reactor areas - 15315

The Hanford Site nuclear reactor operations required large quantities of high-quality cooling water, which was treated with chemicals including sodium dichromate dihydrate for corrosion control. Cooling water leakage, as well as intentional discharge of cooling water to ground during upset conditions, produced extensive groundwater recharge mounds consisting largely of contaminated cooling water and resulted in wide distribution of hexavalent chromium (Cr[VI]) contamination in the unconfined aquifer. The 2013 Cr(VI) groundwater plumes in the 100 Areas cover approximately 6 km{sup 2} (1500 acres), primarily in the 100-HR-3 and 100-KR-4 groundwater operable units (OUs). The Columbia River is a groundwater discharge boundary; where the plumes are adjacent to the Columbia River there remains a potential to discharge Cr(VI) to the river at concentrations above water quality criteria. The pump-and-treat systems along the River Corridor are operating with two main goals: 1) protection of the Columbia River, and 2) recovery of contaminant mass. An evaluation of the effectiveness of the pump-and-treat systems was needed to determine if the Columbia River was protected from contamination, and also to determine where additional system modifications may be needed. In response to this need, a technique for assessing the river protection was developed which takes into consideration seasonal migration of the plume and hydraulic performance of the operating well fields. Groundwater contaminant plume maps are generated across the Hanford Site on an annual basis. The assessment technique overlays the annual plume and the capture efficiency maps for the various pump and treat systems. The river protection analysis technique was prepared for use at the Hanford site and is described in detail in M.J. Tonkin, 2013. Interpolated capture frequency maps, based on mapping dynamic water level observed in observation wells and derived water levels in the vicinity of extraction and injection wells, are developed initially. Second, simulated capture frequency maps are developed, based on transport modelling results. Both interpolated and simulated capture frequency maps are based on operation of the systems over a full year. These two capture maps are then overlaid on the plume distribution maps for inspection of the relative orientation of the contaminant plumes with the capture frequency. To quantify the relative degree of protection of the river from discharges of Cr(VI) (and conversely, the degree of threat) at any particular location, a systematic method of evaluating and mapping the plume/capture relationship was developed. By comparing the spatial relationship between contaminant plumes and hydraulic capture frequency, an index of relative protectiveness is developed and the results posted on the combined plume/capture plan view map. Areas exhibiting lesser degrees of river protection are identified for remedial process optimization actions to control plumes and prevent continuing discharge of Cr(VI) to the river. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Probability of Pinching Failure in PWR SNF after Long-Term Storage

A probabilistic assessment was performed on pinching failure of PWR SNF rod cladding under accidental SNF cask transport conditions. a set of 3,000 rod pinching scenarios was analyzed, with different geometrical, material, and loading parameters, using a Latin Hypercube Sampling (LHS). The investigated accidents include train derailments leading to cask collisions or cask drops. Pinching failure was related to cladding offset strain, defined as the plastic deformation interval in radial cladding direction normalized with respect to the outer cladding diameter. Finite element (FE) models were used to compute SNF rod deformations and the offset strain demand OSD in each of the assessed pinching scenarios. The numerical models account for the contribution of the degraded fuel pellets to rod pinching stiffness. The offset strain capacity OSC was computed using regression and interpolation models based on ring compression (RCT) test results, and account for hydride-related effects on cladding ductility. The results show a low probability of pinching failure. Hydride-related cladding embrittlement affects the structural integrity of PWR SNF rods after long-term dry storage of up to 300 years. Radial hydride patterns or large amounts of circumferentially oriented hydrides reduce the cladding ductile deformation capability when pinched at low material temperatures. The probability of hydride-related pinching failure of PWR cladding is estimated after long-term dry storage to address: How do PWR SNF rod conditions like hydrogen content, vacuum drying peak cladding hoop stress σ{sub θ}, and cladding material temperature affect cladding ductility? Is hydride-related cladding embrittlement a material degradation mechanism that affects the structural integrity of PWR SNF rods under pinching loading? What are the controlling parameters for deformation demands in PWR SNF rods under pinching loading? Is the pinching load amplitude an important parameter that controls the probability of pinching failure? How do parameters like pellet-cladding gap or fuel pellet degradation affect the pinching loading capacity of PWR SNF rods? Statistical modelling of PWR SNF rod conditions in U.S. inventory: A pseudo rod database was generated based on EIA database. Analysis of train accident scenarios: a probability density function (pdf) of a pinching load distribution P{sub 9m} of a 9-m cask drop is linearly scaled to generate a more representative: distribution P{sub AS}. The new distribution considers train collision velocities, cask drops for on- and off-bridge accidents, and cask impact orientation. LHS generates 3,000 rod pinching scenarios based on nine independent geometrical, material, and loading parameters. Probabilistic FE Analysis: The LHS realizations are used to generate 3,000 FE models. The FE analysis is conducted for P{sub 9m}, and P{sub AS}. The workflow is automatized. The OSC is computed with regression and interpolation models, as a function of the hydrogen content C{sub H}, vacuum drying peak σ{sub θ}, and SNF temperature T{sub FR}: The regression data was obtained in RCTs on PWR cladding. The OSD is derived from the cladding deformations in the FE models. Cladding failure was identified via a comparison of OSC and OSD. A 300 and a 30 years-of-dry-storage duration is investigated: The dry-storage period affects the expected SNF temperature and consequently, the OSC and the OSD. The material temperature LHS population is adapted to account for a SNF temperature variation. The probability of hydride-related, ductile cladding failure during a severe transportation accident is not significantly affected by the pinching load amplitude: The probability is slightly reduced from a range of less than 0.0333% to 0.1667% for P{sub 9m}, to a range of less than 0.0333% to 0.1333% for P{sub AS}, depending on the vacuum drying peak cladding hoop stress modelling assumptions. Further, the SNF dry-storage duration does not significantly affect the probability of ductile pinching failure. Based on available train accidents data, the pinching failure probability for a 5,000 km long transportation route ranges from less than 1.62 E-7 to a value of 6.47 E-7, depending on the vacuum drying peak cladding hoop stress modelling assumptions. The pinching load amplitude is not a controlling parameter for the probability of ductile cladding pinching failure, and does not control the cladding deformations once pellet-cladding contact is established, The pellet-cladding gap width, however, plays a key role. Fuel pellet degradation only affects the deformation capacity, if the pellet stiffness is significantly reduced (more than 90%). Only highly embrittled cladding is likely to fail. The deformation demands on the cladding under pinching loading are small.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗

Detection of Lung Contour with Closed Principal Curve and Machine Learning

Radiation therapy plays an essential role in the treatment of cancer. In radiation therapy, the ideal radiation doses are delivered to the observed tumor while not affecting neighboring normal tissues. In three-dimensional computed tomography (3D-CT) scans, the contours of tumors and organs-at-risk (OARs) are often manually delineated by radiologists. The task is complicated and time-consuming, and the manually delineated results will be variable from different radiologists. We propose a semi-supervised contour detection algorithm, which firstly uses a few points of region of interest (ROI) as an approximate initialization. Then the data sequences are achieved by the closed polygonal line (CPL) algorithm, where the data sequences consist of the ordered projection indexes and the corresponding initial points. Finally, the smooth lung contour can be obtained, when the data sequences are trained by the backpropagation neural network model (BNNM). We use the private clinical dataset and the public Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset to measure the accuracy of the presented method, respectively. To the private dataset, experimental results on the initial points which are as low as 15% of the manually delineated points show that the Dice coefficient reaches up to 0.95 and the global error is as low as 1.47 × 10{sup −2}. The performance of the proposed algorithm is also better than the cubic spline interpolation (CSI) algorithm. While on the public LIDC-IDRI dataset, our method achieves superior segmentation performance with average Dice of 0.83.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Numerical Method for Fractional Advection-Diffusion Equation with Heredity

We propose a method of construction of difference schemes for fractional partial differential equations with delay in time. For the fractional equation with two-sided diffusion, fractional transfer in time, and a functional aftereffect, we construct an implicit difference scheme. We use the shifted Grünwald–Letnikov formulas for the approximation of fractional derivatives with respect to spatial variables and the L1-algorithm for the approximation of fractional derivatives in time. Also we use piecewise constant interpolation and extrapolation by extending the discrete prehistory of the model in time. The algorithm is a fractional analog of a purely implicit method; on each time step, it is reduced to the solution of linear algebraic systems. We prove the stability of the method and find its order of convergence.

97 MATHEMATICS AND COMPUTING↗

Development of the Theory of Branched Continued Fractions in 1996–2016

We perform the analysis of investigations in the theory of branched continued fractions carried out for the last 20 years in the directions developed under the general supervision of Prof. V. Ya. Skorobohat’ko (18.07.1927–04.07.1996) including, in particular, the interpolation of functions of several variables by branched continued fractions, the determination of efficient criteria of convergence and computational stability of these fractions, the correspondence between multiple power series and functional branched continued fractions, the investigation of various classes of functional fractions, and the application of branched continued fractions.

97 MATHEMATICS AND COMPUTING↗

The numerical investigation of colliding optical solitons as an all-optical-gate using the method of Lines

The bidirectional propagation and collision of counter-propagating optical solitons in a two-level resonant medium is analyzed. For sufficiently short duration of the pulses and sufficiently high power levels, self-induced transparency allows the pulses to propagate without losses at anomalously low velocities. Here, we use an extended semiclassical approach, called Maxwell–Bloch model. The quantization of the electromagnetic field is neglected, however, a full quantum mechanical formulation is used to describe the behavior of the matter. The numerical simulations are performed by using the method of lines. For improved accuracy, spline interpolation of the fields is introduced. Results are presented to demonstrate the use of soliton collision for all-optical switching, in particular, as OR- and XOR-gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Features of Structure Formation in Chromium-Nickel Steel Manufactured by a Wire-Feed Electron Beam Additive Process

The investigations of the metal macro- and microstructure are performed using the specimens manufactured from the 302 stainless steel via electron-beam additive layer manufacturing in a laboratory setup ensuring 3D printing of articles with circular interpolation. Successive padding of metal results in the formation of a relief representing alternate crests and troughs on the lateral side of the specimen. It is shown by the methods of optical and scanning electron microscopy that the metal of these specimens has a complex heterogeneous dendritic structure containing both relatively coarse grains and subgrains and finer grains. The fine structure of the resulting metal is characterized by a combination of the regions with marked banding and those with nearly regular-shaped grains both in the longitudinal and transverse directions. The grains of more equiaxed shapes are about 5–10 μm in size. It is hypothesized that an application of the additive process would allow manufacturing textured structures with predetermined orientations.

3D PRINTING↗

Inclusion Capture Probability Prediction Model for Bubble Floatation in Turbulent Steel Flow

The turbulent flow around bubbles is simulated for the fixed turbulent kinetic energy. Inclusion motion through the flow field is studied by considering the stochastic effect of turbulence to calculate the capture probability of inclusions with different sizes to a fixed-size individual bubble according to the redefinition. Using the cubic spline interpolation, the capture probability is predicted as functions of the bubble size, inclusion size and turbulent kinetic energy.

36 MATERIALS SCIENCE↗