This study investigates the effectiveness of data assimilation focused on Performance Influence Factors (PIFs) by using process data obtained from plant simulator experiments. Modern Human Reliability Analysis (HRA) methods such as IDHEAS-G incorporate PIF impact into Human Error Probability (HEP) estimation, but the limited availability of empirical data has hindered the quantitative characterization of PIF impact. Previous studies primarily relied on binary success/failure outcomes for entire tasks, resulting in extremely sparse data. To address this limitation, this study introduces a data assimilation framework based on Bayesian inference that incorporates richer process data, including step-wise success or failure and cognitive function-based classification. Plant simulator experiments were conducted using a Macro-Physics Simulator under three accident scenarios and PIF states involving reduced visibility, staffing reduction, and interruption. Observed errors were classified into four cognitive functions defined in IDHEAS-G (Detection, Understanding, Decision making, and Action execution) and error probabilities for each cognitive function were estimated through Bayesian updating. HEP for each scenario was then computed by aggregating posterior error probabilities. As a result, when staffing was reduced and visibility was degraded, decision-making errors increased to more than three times that in the normal state. Compared with using only overall task outcomes, the process data based approach yielded HEP more consistent with observed tendencies, attributed to the significantly increased effective data volume. These findings indicate that incorporating process information enhances the sensitivity and reliability of PIF impact estimation.

A screening criterion is proposed to prevent fuel melting during unprotected transient overpower (UTOP) events in sodium-cooled fast reactors. The criterion is derived from an asymptotic reactivity balance and enables estimation of equilibrium power and peak fuel temperature while considering the temperature dependence of fuel thermal conductivity. Three feedback models were examined: a first-order approximation, a second-order approximation, and a logarithmic model. Comparisons with Monju transient simulations of control-rod withdrawal indicated that the second-order and logarithmic models reproduced peak temperatures within about 40 K of reference solutions, whereas the first-order model showed deviations of similar to 60 K. Neglecting thermal conductivity correction significantly increased the error, exceeding 120 K in the first-order case. These results demonstrate that incorporating the conductivity effect is essential for reliable peak-temperature prediction and provide a practical criterion for rapid core design assessment using steady-state analyses.

This study derives a reactivity balance equation and criteria for preventing core melting during an Unprotected Transient Overpower (UTOP) accident in fast reactors using the assumption of the asymptotic state. In fast reactor design, it is necessary to perform transient analyses that account for potential accidents to ensure core safety. On the other hand, a simplified approach can also be used to evaluate core safety by applying static nuclear parameters, such as reactivity coefficients, based on the reactivity balance equation in the asymptotic state. While this simplified method is valuable for preliminary core design evaluations, the assumptions used in the derivation have not been fully discussed. Therefore, this study clarifies the derivation of the reactivity balance equation in the asymptotic state, considering the fuel temperature, coolant temperature, and axial and radial expansions. Using this equation, criteria are established for avoiding both coolant boiling and core melting during UTOP conditions. A key approximation made in this derivation is that the shape of the power distribution remains unchanged through the transient event.

Considering computational costs, it is practical to use collapsed energy group structures with less than several tens of groups of the core analysis of High-Temperature Gas-cooled Reactors (HTGRs). This study evaluates the performance of several existing energy group structures and newly optimized 15-group and 25-group structures for prismatic HTGRs with uranium fuel. Both multi-element and two-dimensional core geometries were used to account for neutron spectrum interference effects caused by the presence of control rods, differences in graphite temperature, and variations in the amount of surrounding graphite. The optimization calculations were performed using Genetic algorithm and Particle swarm optimization. Among the group structures with around 15 groups, the newly optimized 15-group structure showed relatively good agreement with the reference solution. For the group structures with around 25 groups, while the newly optimized 25-group structure showed slightly better performance under certain conditions, the existing 26-group structure consistently demonstrated stable and good performance.

We performed americium transmutation in uranium fuel with a transuranic generation reduction fuel, which uses BWR fuel and increases the 235U enrichment within the range of High-Assay Low-Enriched Uranium (HALEU). We evaluated the relationship between the total decay heat of 241Am and 244Cm. The increase in decay heat from 244Cm when the 235U enrichment is 3.8 wt%, which is the example case of LEU application as that of existing fuel. The generation of 244Cm comes from a smaller mass number of TRU nuclides decrease as the neutron flux and neutron capture reactions decrease with increasing enrichment. As a result, in the range where the enrichment exceeds about 7.5 wt%, and the ratio of the decrease in the weight fraction of 241Am to the increase in the weight fraction of 244Cm decreases below 4.1 %, and the total decay heat of the two nuclides is lower than it would be in no-transmutation.

We conducted an online survey of 1953 members of the general population (valid response rate: 65.1%) and 384 radiological technologists (valid response rate: 100%) to examine the relationship between radiation knowledge and concerns. The mean knowledge score (maximum: 50) was 28.7 in the general population and 40.2 among radiological technologists. The mean concern scores (maximum: 50) were 25.0 and 17.1, respectively. Both scores differed significantly between the groups (Mann–Whitney U test, P < .01). In the general population, the relationship between knowledge and concern scores varied according to age. In those aged < 30 years, the correlation was weak (R, −0.411 to −0.412), whereas in those aged ≥ 30 years, it was stronger (R, −0.541 to −0.546), suggesting that knowledge reduces concerns. No significant age-based differences were observed among the technologists. These findings suggest that increasing knowledge about radiation may help alleviate concerns.

This paper presents a method for calculating reactivity changes caused by uniform thermal expansion in sodium-cooled fast reactors using reactivity coefficients. The reactivity changes due to both Z-axis and radial expansion are separated into two effects: the shape change effect and the macroscopic cross section change effect. These effects are expressed using the reactivity coefficients of materials in the reactor core. The reactivity change due to Z-axis expansion considers the expansion of the fuel, cladding, and wrapper tube, while the radial expansion considers the fuel pin, structural materials, and reactor core support structures. To confirm the accuracy of this approach, calculations were performed for simplified reactor geometry with different height-to-diameter ratios. The results show that reactivity changes behave almost linearly for expansions of up to 2%. Additionally, the difference between the expansion reactivity obtained by using reactivity coefficients and those by direct calculations considering core expansion is within a few percent.

Abstract This study investigates the appropriate thermal cut-off energy for neutron transport calculations in the High Temperature Engineering Test Reactor (HTTR). Using the Monte Carlo calculation code MVP3.0, the impact of changing thermal cut-off energy on the multiplication factor was evaluated for the single fuel element geometry of HTTR, focusing on variations in fuel and moderator temperatures at the beginning of life (BOL) and end of life (EOL). In the default model of MVP3.0, resonance scattering is approximated by the free-monatomic-gas model with constant cross section. Therefore, the impact of using the exact model for resonance scattering was additionally examined. In the free-monatomic-gas model, a thermal cut-off energy of 30 eV is at least required to maintain the multiplication factor error within approximately ±50 pcm for both BOL and EOL. In addition, the results show that the impact of using the exact model instead of the free-monatomic-gas model on the multiplication factor is more than 200 pcm in the 30 to 40 eV range where U-238 has large resonance at 37 eV, and the impact becomes less than 50 pcm above 40 eV. These results indicate that a thermal cut-off energy of at least 30 eV is necessary without considering the effects of the exact model, and the energy range up to the 37 eV resonance needs to be considered in the case of applying the exact model to obtain the saturated results on multiplication factor for HTTR.

Neutronics characteristics are examined by the MCNP6.2 code with ENDF/B-VII.1 for a light-water-moderated and graphite-reflected core with highly enriched uranium fuel at the University Teaching and Research Reactor in Kindai University (UTR-KINKI), demonstrating the meaningful degree of computational accuracies of the criticality, the reactivity, and the reaction rates. The eigenvalue calculations, and the uncertainty analyses for criticality and reactivity are performed using the KENO-VI, the TSUNAMI-3D, and the TSAR modules of the SCALE code system, respectively. The eigenvalue calculations with MCNP6.2 and KENO-VI show a discrepancy between experimental and numerical results of the effective multiplication factor (keff) in the UTR-KINKI core. Regarding TSUNAMI-3D calculations, the uncertainty of keff is found to be attributable mainly to those of a series of uranium-235 cross-section data related to fission reactions with the support of uncertainty analyses of reactivity by TSAR.

For EUV high NA lithography, current conventional tri-layer and tetra-layer process might face the critical issue both for EUV lithographic performance and pattern etch transfer. Especially since the latest EUV PR including CAR and MOR is very low film thickness around 10nm after development, the bottom under layer such as Si containing hard mask (Si-HM) or EUV under layer should be around 5nm FTK. In this case, it is too difficult to transfer to SOC or bottom hard mask layer. In order to prevent this critical issue, we propose new functional surface treatment process and primers (FSTP) on the conventional CVD and spin on hard mask. This FSTP is a spin coating material. However it is almost single molecular type ultra-thin primer (~1nm) for all of the CVD and spin on hard mask (SiON, SiN, TiN, SiO2, SiHM, SOG and so on) not to bother fine pitch pattern transfer. In our recent experimental, one of the FSTP has high universality to EUV PR CAR and MOR to achieve high patterning performance in EUVL. Moreover, the other one of the FSTP specially optimized for MOR process showed 20~30% dose reduction on inorganic substrate. Therefore FSTP has big advantage and potential in EUV lithographic process and pattern etch transfer enhancement for next generation High NA EUV process.

Pattern collapse emerges as a key factor leading to the failure of photoresist patterns in high-resolution extreme ultraviolet lithography (EUVL). Its significance escalates as feature sizes decrease and pitches become smaller, transitioning to high-numerical aperture extreme ultraviolet, potentially leading to challenges with regard to resolution. Pattern collapse arises from capillary forces acting on the resist surface during wafer drying. Consequently, the optimal strategy to mitigate pattern collapse involves eliminating any drying steps post-lithography processing. We introduce the organic dry development rinse (O-DDR) process for spin-on metal oxide resist, effectively eliminating capillary force and eradicating the pattern collapse issue without tone inversion. This involves dispensing O-DDR material instead of employing a spin-drying developer, without introducing any extra processing steps. After the dry etching process, we observe that the resist patterns, such as pitch 32-nm pillars and pitch 28-nm line and space, appear to have mostly no collapse at small pitches or low doses. Furthermore, we analyze the O-DDR process, intending to expand the window for a failure-free process with pitch 32-nm pillars and pitch 28-nm line and space in EUVL.

In order to reduce Minor Actinides (MA), the transmutation of MA in a fast reactor has been studied in Japan. In the transmutation in the fast reactor, MAs are mixed in the ordinary MOX fuel and they are burned up. For the design of a fast reactor with inherent safety characteristics, it is necessary to secure negative void reactivity and cooling via a natural convection under the situation of the severe accident. Therefore, this study aims to fundamentally design the fast reactor for the MA transmutation with inherent safety characteristics. First, in order to clarify the design range of the core design parameter, the parametric study was conducted using four design parameters determining the core configuration. As the result of this parametric study, the feasible combination of each four parameters satisfying the negative void reactivity was clarified. Among parameters satisfying the negative void reactivity, the condition that results in the maximum reduction of MA amount was obtained. Secondly, the CFD simulation focused on the sodium coolant channel between fuel pins was conducted. In this CFD simulation, as the first step for the design activity, the confirmation of the occurrence condition of a natural convection due to the decay heat after shifting to the transient situation was confirmed. Temperature and velocity distribution were evaluated. And the heat transfer efficiency was summarized using Ra number and Nu number.

In this paper, formulas for evaluating expansion reactivity based on reactivity coefficients in sodium-cooled fast reactors are derived, and the approximation errors used in the derivation are also evaluated. This research provides formulas for both Z-axis expansion reactivity and radial expansion reactivity. These reactivities are separated into the effect of change in geometric shape and that of change in the cross-section. Since the major approximation in the present derivation is the separation of effects due to geometric shape changes and cross-sectional area changes, the approximation error due to this separation was evaluated using results of neutron transport calculations for fast reactor. This evaluation was performed for two geometries with different ratios of the reactor core's height to diameter. The results show that the approximation error is less than 20 pcm. Therefore, it can be expected that expansion reactivity can be accurately evaluated using reactivity coefficients.

An improved sampling method for flight distance is proposed for Monte Carlo analysis of TRISO fuel particles using the statistical geometry (STG) method. The statistically uniform distribution of fuel particles, which is usually assumed as a default sampling method of flight distance of a neutron between fuel particles, shows considerable bias on k-infinity when coating layers of a TRISO fuel particle are homogenized with a graphite matrix. The proposed new sampling method almost resolves the difference between the no-coating-layer model (coating layers are homogenized with a graphite matrix) and the explicit-coating-layer model (explicitly considers coating layers, reference). By adopting the present method, the no-coating-layer model can be used without significant loss of accuracy in the STG method of a Monte Carlo analysis. The computation time with a continuous energy Monte Carlo code for a typical fuel compact cell of a high-temperature gas-cooled reactor is reduced to one-seventh of the explicit-coating-layer model when the no-coating-layer model is used.

The aim of this study was to establish an e-learning training system for radiation disaster management in order to effectively train and secure personnel for radiation disasters, independent of regional characteristics such as the presence or absence of nuclear facilities. An educational management tool was used to enable verification of the educational effects through on-demand videos and pre- and post-training tests based on standardized textbooks created by the government. This training was conducted for radiological technologists affiliated with the National Hospital Organization. The educational effects were analyzed based on the results of the pre- and post-training tests. The developed e-learning training system included on-demand videos, provision of PDF materials, implementation of pre- and post-tests, confirmation of attendance, and performance management. Of the 65 trainees, 59 completed all the lectures and tests. The correct answer rate of the pre-training test was 57.8 ± 19.0%, while that of the post-training test was 85.9 ± 12.5%. This study established the first-of-its-kind e-learning training system for radiation disaster management in Japan and participants received effective literacy education on radiation disaster management. The results showed that training can be conducted regardless of location, thereby facilitating effective training and securing of personnel.

In most fishes, the number of offspring increases with maternal body size. Although this size-fecundity relationship often varies among species as a result of the coevolution of life-history traits, the genetic basis of such size-fecundity relationships remains unclear. We explored the genetic basis underlying this size-fecundity relationship in two small medaka species, Oryzias latipes and O. sakaizumii. Our findings showed that O. sakaizumii has a higher fecundity than O. latipes, and quantitative trait locus analysis using interspecific F2 hybrids showed that chromosome 23 is linked to the size-fecundity relationship. In particular, the genes igf1 and lep-b in this region are known to be associated with life-history traits, including somatic growth, gonad maturation, and progeny numbers in various taxa. Because O. sakaizumii is distributed at higher latitudes and has a shorter spawning season than O. latipes in the wild, we propose that the relatively high fecundity observed in O. sakaizumii is an adaptation to high latitudes. We also discuss the potential ecological ramifications associated with the evolution of increased fecundity in this species.

Pattern collapse emerges as a key factor leading to the failure of photoresist patterns in high-resolution EUV lithography. Its significance escalates as feature sizes decrease and pitches become smaller transitioning to high-NA EUV, potentially leading to challenges with regards to resolution. Collapse arises from capillary forces acting on the resist surface during wafer drying. Consequently, the optimal strategy to mitigate pattern collapse involves eliminating any drying steps post-lithography processing. In this study, we introduce the O-DDR process for spin-on MOR, effectively eliminating capillarity and eradicating the pattern collapse issue without tone inversion. Figure 1 illustrates the O-DDR process, which involves dispensing O-DDR material instead of employing a spin-drying developer, without introducing any extra processing steps. After the dry etching process, we observe that the resist pattern remains intact without any collapse. Furthermore, we conduct an analysis of the O-DDR process, with the goal of expanding the window for a failure-free process with pitch 32nm pillars and pitch 28nm line and space in EUV lithography.

We analyzed the possibility of TRU generation reduction fuel using HALEU as the initial enrichment to reduce the radiotoxicity and decay heat of TRU when using the LWR fuels that can suppress radiotoxicity and decay heat in HLW. Fade-out time was defined as the period required to decay to the level of natural uranium ore, focusing on the radiotoxicity, and decay heat up to one million years, which is generated from the reduced TRU generation type fuel (FORSETI) consisting of uranium fuel of HALEU enrichment. The decay characteristics of TRU nuclides in HLW after plutonium removal by reprocessing and the effect of shortening the fade-out time were mainly discussed. The level of 241Am on both radiotoxicity and decay heat is significant. However, the effect of 239Pu and 240Pu, which are produced as daughter nuclides of 243Am and 244Cm after reprocessing, significantly lengthens the fade-out time to 100,000 years for radiotoxicity and to 40,000 years for decay heat, compared to several thousand years for 241Am alone. When TRU generation reduction fuel is adopted, the production rate of 243Am and 244Cm is reduced by more than 90% when the enrichment is increased from 3.8 wt% to 20 wt%, and the generation of 239Pu and 240Pu as daughter nuclides are also reduced almost correspondingly. As a result, increasing the initial 235U enrichment from 3.8 wt% to 20 wt% reduces the fade-out time of radiotoxicity from 100,000 to 3,000 years and the fade-out time of decay heat from 40,000 to 2,000 years for HLW, respectively by FORSETI-type TRU generation reduction fuel. As described above, it is shown that using TRU generation reduction fuel can significantly accelerate the decay of TRU radiotoxicity and decay heat in HLW without transmutation of TRU.

The human error probabilities (HEP) can be estimated using multipliers that correspond to the level of performance shaping factors (PSFs) in the human reliability analysis (HRA). This paper focuses on the adjustment of multipliers through Bayesian inference based on Monte Carlo techniques using the experimental results from simulators. Markov Chain Monte Carlo (MCMC) and Bayesian Monte Carlo (BMC) are used as Bayesian inference methods based on Monte Carlo techniques. MCMC is utilized to obtain the posterior distribution of the multipliers. BMC is used for the estimation of the moments of the posterior distribution such as the mean and variance. The results obtained by MCMC and that by BMC well agree with the reference results. As a case study, the data assimilation was performed using the results of the simulator experiment of Halden reactor. The results show that the multiplier changes by the result of a particular scenario and HEP of another scenario that uses the same multiplier also changes by data assimilation. Also, in the case study, the correlation between multipliers is obtained by the data assimilation and the correlation contributes to the reduction of uncertainty of HEP.