• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2491-2509
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• 2022

As an important device in the nuclear island, the nuclear coolant pump can continuously provide power for medium circulation. The vane is one of the stationary parts in the nuclear coolant pump, which is installed between the impeller and the casing. The shape of the vane plays a significant role in the pump's overall performance and stability which are the important indicators during the safety serve process. Hence, the bionic concept is firstly applied into the design process of the vane to improve the performance of the nuclear coolant pump. Taking the scaled high-performance hydraulic model (on a scale of 1:2.5) of the coolant pump as the reference, a united bionic design approach is proposed for the unique structure of the guide vane of the nuclear coolant pump. Then, a new optimization design platform is established to output the optimal bionic vane. Finally, the comparative results and the corresponding mechanism are analyzed. The conclusions can be gotten as: (1) four parameters are introduced to configure the shape of the bionic blade, the significance of each parameter is herein demonstrated; (2) the optimal bionic vane is successfully obtained by the optimization design platform, the efficiency performance and the head performance of which can be improved by 1.6% and 1.27% respectively; (3) when compared to the original vane, the optimized bionic vane can improve the inner flow characteristics, namely, it can reduce the flow loss and decrease the pressure pulsation amplitude; (4) through the mechanism analysis, it can be found out that the bionic structure can induce the spanwise velocity and the vortices, which can reduce drag and suppress the boundary layer separation.

• The Journal of Advanced Prosthodontics
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• v.14 no.5
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• pp.324-333
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• 2022

PURPOSE. The purpose of this study is to evaluate translucency and masking ability of translucent zirconia compared to conventional zirconia and lithium disilicate materials. MATERIALS AND METHODS. Three types of zirconia blocks with different yttria contents (3Y, 4Y, 5.5Y) and LS blocks (Rosetta SM) were used. Ten specimens for each group were fabricated with 10 mm diameter, with both 0.8 mm and 1.5 mm thicknesses (± 0.02 mm). All groups of zirconia specimens were sintered and polished according to the manufacturer's instructions. To calculate the translucency parameter (TP), CIELAB value was measured with a spectrophotometer on black and white backgrounds. To investigate the color masking abilities, background shades of A2, normal dentin, discolored dentin, and titanium were used. The color difference (ΔE) was calculated with the CIELAB values of A2 shade background as a reference compared with the values in the various backgrounds. One-way ANOVA and Bonferroni tests were conducted (P < .05). RESULTS. The TP values of zirconia specimens increased as the yttria content increased. All materials used in the study were able to adequately mask normal dentin shade (ΔE < 5.5), but were incapable of masking severely discolored dentin (ΔE > 5.5). On the titanium background, all materials of 1.5 mm thickness were able to mask the background shade, but with a thickness of 0.8 mm, only 3Y-TZP and 4Y-PSZ were able to mask titanium background. CONCLUSION. All zirconia materials and lithium disilicate specimens used in this study were unable to adequately mask the shade of severely discolored dentin. It is recommended to use 3Y-TZP or 4Y-PSZ with a sufficient thickness of 0.8 mm or more to mask titanium.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3403-3414
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• 2022

The purpose of this study is to model and optimize the block-matching and 3D filtering (BM3D) algorithm and to evaluate its applicability in brain single-photon emission computed tomography (SPECT) images using a fan beam collimator. For quantitative evaluation of the noise level, the coefficient of variation (COV) and contrast-to-noise ratio (CNR) were used, and finally, a no-reference-based evaluation parameter was used for optimization of the BM3D algorithm in the brain SPECT images. As a result, optimized results were derived when the sigma values of the BM3D algorithm were 0.15, 0.2, and 0.25 in brain SPECT images acquired for 5, 10, and 15 s, respectively. In addition, when the sigma value of the optimized BM3D algorithm was applied, superior results were obtained compared with conventional filtering methods. In particular, we confirmed that the COV and CNR of the images obtained using the BM3D algorithm were improved by 2.40 and 2.33 times, respectively, compared with the original image. In conclusion, the usefulness of the optimized BM3D algorithm in brain SPECT images using a fan beam collimator has been proven, and based on the results, it is expected that its application in various nuclear medicine examinations will be possible.

• The Journal of Advanced Prosthodontics
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• v.15 no.4
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• pp.179-188
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• 2023

PURPOSE. This in vitro study aimed to evaluate the performance of digital intraoral scanners in a completely edentulous patient with angled and parallel implants. MATERIALS AND METHODS. A total of 6 implants were placed at angulations of 0°, 5°, 0°, 0°, 15°, and 0° in regions #36, #34, #32, #42, #44, and #46, respectively, in a completely edentulous mandibular polyurethane model. Then, the study model created by connecting a scan body on the implants was scanned using a model scanner, and a 3D reference model was obtained. Three different intraoral scanners were used for digital impressions (PS group, TR group, and CS group, n = 10 in each group). The distances and angles between the scan bodies in these measurement groups were measured. RESULTS. While the Primescan (PS) impression group had the highest accuracy with 38 ㎛, the values of 104 ㎛ and 171 ㎛ were obtained with Trios 4 IOSs (TR) and Carestream 3600 (CS), respectively (P = .001). The CS scanner constituted the impression group with the highest deviation in terms of accuracy. In terms of dimensional differences in the angle parameter, a statistically significant difference was revealed among the mean deviation angle values according to the scanners (P < .001). While the lowest angular deviation was obtained with the PS impression group with 0.185°, the values of 0.499° and 1.250° were obtained with TR and CS, respectively. No statistically significant difference was detected among the impression groups in terms of precision values (P > .05). CONCLUSION. A statistically significant difference was found among the three digital impression groups upon comparing the impression accuracy. Implant angulation affected the impression accuracy of the digital impression groups. The most accurate impressions in terms of both distance and angle deviation were obtained with the PS impression group.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4253-4264
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• 2022

Since the implementation of the phosphate project in Bled El-Hadba (BEH) deposit, western region of Tébessa, no detailed study has been conducted to assess the natural radioactivity distribution and the associated radiological risk parameter for this open-pit mine. For the sake of determining a credible premining reference database for the region of interest, 21 samples were collected from different geological layers of the above-mentioned deposit. Gamma Spectrometry was applied for measuring radioactivity using a high resolution HPGe semiconductor detector. The obtained activity results have shown a significant broad variation in the radioactive contents for the different phosphate samples. The total average concentrations (in Bq·kg^-1) for ²²⁶Ra, ²³⁸U, ²³⁵U, ²³²Th and ⁴⁰K computed for the different type of phosphate layers were found to be 570 ± 169, 788 ± 280, 52 ± 18, 66 ± 6 and 81 ± 18 respectively. The mean activity concentrations of the measured radionuclides were compared to other regional and worldwide deposits. The ratios between the detected radioisotopes have been calculated for spatial distribution of natural radionuclides in the study area. Based on the aforementioned activity concentrations, the corresponding radiation hazard parameters were assessed. Correlations between the obtained parameters were drawn and a multivariate statistical analysis (Pearson Correlation, Cluster and Factor analysis) was carried out in order to identify the existing relationships.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.452-459
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• 2023

The core power control is an important issue for the study of dynamic characteristics in China initiative accelerator driven subcritical system (CiADS), which has direct impact on the control strategy and safety analysis process. The CiADS is an experimental facility that is only controlled by the proton beam intensity without considering the control rods in the current engineering design stage. In order to get the optimized operation scheme with the stable and reliable features, the variation of beam intensity using the continuous and periodic control approaches has been adopted, and the change of collimator and the adjusting of duty ratio have been proposed in the power control process. Considering the neutronics and the thermal-hydraulics characteristics in CiADS, the physical model for the core power control has been established by means of the point reactor kinetics method and the lumped parameter method. Moreover, the multi-inputs single-output (MISO) logical structure for the power control process has been constructed using proportional integral derivative (PID) controller, and the meta-heuristic algorithm has been employed to obtain the global optimized parameters for the stable running mode without producing large perturbations. Finally, the verification and validation of the control method have been tested based on the reference scenarios in considering the disturbances of spallation neutron source and inlet temperature respectively, where all the numerical results reveal that the optimization method has satisfactory performance in the CiADS core power control scenarios.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.11-28
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• 2022

This paper considers the combination of cyclic and axial loads to investigate the hysteretic performance of H-section 6061-T6 aluminum alloy members. The hysteretic performance of aluminum alloy members is the basis for the seismic performance of aluminum alloy structures. Despite the prevalence of aluminum alloy reticulated shells structures worldwide, research into the seismic performance of aluminum alloy structures remains inadequate. To address this deficiency, we design and conduct cyclic axial load testing of three H-section members based on a reliable testing system. The influence of slenderness ratios and bending direction on the failure form, bearing capacity, and stiffness degradation of each member are analyzed. The experiment results show that overall buckling dominates the failure mechanism of all test members before local buckling occurs. As the load increases after overall buckling, the plasticity of the member develops, finally leading to local buckling and fracture failure. The results illustrate that the plasticity development of the local buckling position is the main reason for the stiffness degradation and failure of the member. Additionally, with the increase of the slenderness ratio, the energy-dissipation capacity and stiffness of the member decrease significantly. Simultaneously, a finite element model based on the Chaboche hybrid strengthening model is established according to the experiment, and the rationality of the constitutive model and validity of the finite element simulation method are verified. The parameter analysis of twenty-four members with different sections, slenderness ratios, bending directions, and boundary conditions are also carried out. Results show that the section size and boundary condition of the member have a significant influence on stiffness degradation and energy dissipation capacity. Based on the above, the appropriate material constitutive relationship and analysis method of H-section aluminum alloy members under cyclic loading are determined, providing a reference for the seismic design of aluminum alloy structures.

• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.90-99
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• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• Geomechanics and Engineering
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• v.34 no.2
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• pp.155-171
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• 2023

Aiming at the grouting treatment of water inflow in karst conduits, a visualized experiment system for conduit-type grouting blocking was developed. Through the improved water supply system and grouting system, and the optimized multisource information monitoring system, the real-time observation of diffusion and deposition of slurry, and the data acquisition of pressure and velocity during the whole process of grouting were realized, which breaks through the problem that the monitoring element is easy to fail due to slurry adhesion in conventional test system. Based on the grouting experiments in static and flowing water, the diffusion and deposition behavior of the quick-setting slurry under different working conditions were analyzed. The temporal and spatial variation behavior of the pressure and velocity were studied, and the blocking mechanism of the grouting were further revealed. The results showed that: (1) Under the flowing water condition, the counter-flow diffusion distance of slurry was negatively correlated with the flow water velocity and the volume ratio of cement and sodium silicate (C-S ratio), and positively correlated with the grouting volume. The slurry deposition thickness was negatively correlated with the flowing water velocity, and positively correlated with the grouting volume and C-S ratio. (2) The pressure increased slowly before blocking of the flowing water and rapidly after blocking in karst conduits. (3) With the continuous progress of grouting, the flowing water velocity decreased slowly first, then significantly, and finally tended to be stable. According to the research results, some engineering recommendations were put forward for the grouting treatment of the conduit-type water inflow disaster, which has been successfully applied in the treatment project of the China Resources Cement (Pingnan) Limestone Mine. This study provided some guidance and reference for the parameter optimization of grouting for the treatment projects of water inflow in karst conduits.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.