This study investigates the crack propagation paths and interaction mechanisms of dual cracks in dissimilar metal welded joints (DMWJs) under material heterogeneity. A phase-field modeling framework was first developed in Abaqus to systematically analyze crack evolution and damage progression across the continuously graded interfacial region. To overcome the limitation of conventional multilayer discontinuous models in capturing the realistic continuous gradient of welded joints, a phase-field scheme coupling user-defined material subroutines and user-defined elements was established. The spatially continuous distribution of material properties was achieved by inversely identifying the yield strength profiles of the base metal, heat-affected zone, and fusion zone from microhardness experiments. By varying the crack spacing and crack length, the competition in crack initiation, path deflection, and coalescence behavior of dual cracks in the SA508-52Mb and 316L-52Mw regions was quantitatively analyzed. The results reveal that mechanical heterogeneity drives cracks to propagate preferentially toward the lower yield strength side and significantly governs the mutual attraction between cracks. Dual cracks in the 316L heat-affected zone tend to coalesce as they approach each other; in SA508-52Mb, short cracks exhibit pronounced deflection whereas longer cracks are inhibited. In 316L-52Mw, coalescence is observed only when the cracks have comparable lengths. This work elucidates the propagation mechanisms of dual cracks in DMWJs and provides theoretical insight for structural integrity assessment of nuclear reactor safe end components.

Similarity analyses, which are used in the selection of experiments for criticality code validation, rely on the evaluation of the integral index c k . The integral index c k provides a quantitative basis for the evaluation of the similarity in eigenvalue uncertainties, due to nuclear data uncertainties, between a single critical experiment relative to an application. Nuclear data uncertainty quantification via statistical sampling, recently implemented into CASMO5, represents a significant leap in the available analytical capabilities in Studsvik’s Core Management System 5. Evaluating integral indices using the statistical sampling method in CASMO5 comprises a new and significant application. This work describes the theory and application of nuclear data uncertainty quantification in the evaluation of integral indices. A verification of the implemented methods is presented against the results from independent tools. Following the verification, numerical results are presented that compare the impact of fuel assembly depletion on similarity c k and relevance j k between conventional fuel designs and the higher enrichment and high burnup (HE/HB) representative fuel. Further similarity and relevance analysis is applied to spent fuel pool applications and critical experiments, as well as HE/HB lattices to critical experiments involving greater than 5 wt% enrichments. Finally, the similarity and relevance of the HE/HB lattices are evaluated relative to a subset of the Haut Taux de Combustion (HTC) critical experiments. These examples illustrate the benefits of the c k and j k indices, demonstrating a new application of CASMO5’s uncertainty quantification feature.

Backscatter imaging is a reliable method of single-sided X-ray imaging where access may pose limitations on traditional transmission X-ray image capture. Because of physical challenges in its implementation, it has traditionally been regarded as unable to do material discrimination, a capability reserved for dual energy and transmission imaging by industry and academia. This research expanded on a novel method developed at the University of Florida, where a material calibration tool was used to calibrate a Viken Detection Nighthawk BTX in backscatter mode for postprocessing material discrimination. Namely, this novel approach identifies materials potentially found in explosive devices, i.e. lead, copper, steel, and plastic, as well as combinations of these materials through a fusion of filters. This research focused on expanding the previous work to determine if the novel approach worked at distances beyond the original use-based tests, as well as if source beam filtering and hardening would improve material resolution.

The study examines the influence of high-density, low-enriched uranium (LEU) on the fuel plate temperature of the International Atomic Energy Agency’s 10-MW materials testing reactor under steady-state conditions using ANSYS FLUENT software. For this purpose, we used high-density LEU fuels currently under development by the Reduced Enrichment for Research and Test Reactors program, specifically U3Si2 and U-10Mo. To attain the required uranium densities while preserving the high-enriched uranium fuel assembly geometry, a mass fraction of 80.9% was necessary, which corresponded to a 49.07% volume fraction of the dispersed phase. The maximum fuel meat temperatures of the U3Si2 and U-10Mo increased with the uranium density, reflecting variations in the fuel thermal conductivity. For U3Si2, the maximum fuel temperatures were 98.39°C, 99.64°C, and 103.34°C for 4.1 gU/cm3, 4.8 gU/cm3, and 5.66 gU/cm3, respectively.

Tsinghua High Flux Reactor (THFR), a wide-spectrum super-high-flux experimental reactor under construction by the Institute of Nuclear and New Energy, Tsinghua University, has some special neutronics design characteristics, including compact and complex geometry, strong neutron currents between regions, and considerable heterogeneity effects. Currently, there is no deterministic physical design calculation method and software available. This paper studied and proposed the on-the-fly two-step method for the neutronics calculation of THFR. The key issues of the methodology, including the overall calculation framework, equivalent homogenization, and three-dimensional whole-core calculation are comprehensively described herein. Numerical tests are presented for simplified THFR three-dimensional models, verifying the applicability and performance of the proposed methods.

Deterministic solutions to the Sn radiation transport equation can be computationally expensive to calculate. Reduced-order modeling enables efficient approximation of the full-order model (FOM) solution. We propose a novel method for constructing reduced-order models (ROMs) of the Sn radiation transport equation, offline maximizing minimally invasive (OMMI) proper orthogonal decomposition (POD). POD uses the method of snapshots to create a reduced-order basis for constructing an ROM. Minimally invasive POD leverages the sweep infrastructure existing in deterministic transport codes to create a POD-based ROM, even when infeasible by traditional methods. Offline maximizing minimally invasive proper orthogonal decomposition (OMMI-POD) extends minimally invasive POD by performing sweeps offline, therefore maximizing the potential speedup. OMMI-POD does so by creating a library of reduced systems from a training set. This library of reduced systems is then interpolated to provide a rapid approximate solution of the Sn radiation transport equation. The model is evaluated on a set of test problems, achieving a low error with a 466 times speedup over the FOM. Also presented is a study of the effect of sampling method on the performance of OMMI-POD, specifically comparing naive uniform sampling to the more accurate and computationally expensive greedy sampling.

Modeling and simulation of reactor kinetics under the point model approximation can be roughly divided into two categories: deterministic models, which consider the flux and other state variables (delayed neutrons, temperature, etc.) as time-dependent functions, and stochastic models, which study the flux as a stochastic process. Since the neutron reactions and fission chain are stochastic by nature, the stochastic models are a better reflection of the physical system. On the other hand, due to the complexity of the stochastic models and the large number of reactions, most common analysis is done in the deterministic setting via the widely spread point reactor kinetic (PRK) equation. In the most basic setting, when we assume that all reaction rates are constant in time, the PRK can be generalized to the stochastic setting via the master equation (Chapman–Kolmogorov equation). The resulting model is often implemented in reactor noise experiments and the Feynman-α method, and the interpretation of the deterministic model as a mean field approximation of the stochastic model is very well understood. Once we include nonlinear feedback into the equation (typically due to temperature influence on the cross-sections), the stochastic modeling becomes much more delicate, due to (at least) two issues: First, both energy and temperature are continuous, and thus the applicability of the master equation questionable. Second, in a nonlinear setting, the mean field approximation of the stochastic model is not equivalent to the PRK equation, and the two are unified only if we assume implicitly that the covariance of the power and the temperature is nullified, which is bound to create a systematic error. Thus, modeling and simulation of stochastic fission chains and temperature represent a central topic in reactor control and measurements. One of the most classic studies on stochastic fission chains in a reactor with thermal feedback is that of Harris (1958), where a discretization of the energy bins is performed to allow use of the master equation technique. The outline of the present study is to construct and study the properties of an Ito-type stochastic differential equation (SDE) counterpart to the classic Harris model. The contribution of the study will be divided into three consecutive steps: First, we will explicitly derive from first principles the parameters of the SDE. Then we will compute the covariance between the system variables and prove that the Harris model and the SDE model have a very strong common feature: They share the exact same second-moment equations. Finally, we will demonstrate the applicability of the SDE for a non-analog Monte Carlo scheme for sampling distribution of the different stochastic variables.

This study investigates neutron behavior in an accelerator-driven system (ADS), where the neutron population consists of particles produced through multiple nuclear processes, including fission. An ADS exhibits a distinct neutron energy spectrum that differs from that of a purely fission-driven spectrum, and therefore, affects the neutron efficiency E* for inducing fission reactions in fissionable nuclei. The neutron efficiency E* and the neutron multiplication factor in an ADS, denoted as ks, are interrelated. The factor ks differs from keff, which accounts only for fission neutrons. This analysis examines how parameters such as fuel enrichment, the type and energy of the primary particles, and the fraction of nonfission neutrons influence both E* and ks. The results show that the average number of neutrons released per fission in an ADS νs plays a significant role in system neutronics, affecting the neutron efficiency E*, and consequently, the subcritical multiplication factor ks. The investigation focuses on a graphite-moderated, accelerator-driven molten-salt reactor employing a 233U-232Th fuel mixture. The results are compared with those for a deeply subcritical system operating with a fast neutron spectrum.

This article presents the interpretation of a heat balance experiment conducted at the Transient Reactor Test Facility (TREAT). A reference OpenMC model of TREAT is introduced to evaluate the effects of the control rod positions and temperature variations on the effective multiplication factor (keff) and correction factors. Building on prior work, OpenMC is also used to investigate key hypotheses underlying the signal processing algorithm for reactivity and transient analysis (SPARTA) methodology. A critical hypothesis of SPARTA—that reactivities and correction factors can be obtained by linearly combining individual effects—was validated. However, the temperature effect on the correction factors, previously deemed negligible, was found to be significant, necessitating updates to the SPARTA methodology. By fitting an exponential curve to the mean temperature data, SPARTA’s accuracy and convergence were further enhanced. Finally, an experiment interpretation was performed by comparing the SPARTA and OpenMC results, which demonstrated consistent reactivity removal due to temperature increases. While this study confirmed SPARTA’s capability to interpret complex transients independently of an OpenMC model, it also highlights that simpler methods may be sufficient when the correction factors have minimal impact on reactivity calculations.