• Nuclear Engineering and Technology
• /
• v.52 no.12
• /
• pp.2789-2802
• /
• 2020

Small Modular Reactors (SMRs) are attracting wide attention due to their outstanding performance, extensive studies have been carried out for lead-based fast reactors (LFRs) that cooled with Lead or Lead-bismuth (LBE), and small modular natural circulation LFR is one of the promising candidates for SMRs and LFRs development. One of the challenges for the design small modular natural circulation LFR is to master the natural circulation thermal-hydraulic performance in the reactor primary circuit, while the natural circulation characteristics is a coupled thermal-hydraulic problem of the core thermal power, the primary loop layout and the operating state of secondary cooling system etc. Thus, accurate predicting the natural circulation LFRs thermal-hydraulic features are highly required for conducting reactor operating condition evaluate and Thermal hydraulic design optimization. In this study, a thermal-hydraulic analysis code is developed for small modular natural circulation LFRs, which is based on several mathematical models for natural circulation originally. A small modular natural circulation LBE cooled fast reactor named URANUS developed by Korea is chosen to assess the code's capability. Comparisons are performed to demonstrate the accuracy of the code by the calculation results of MARS, and the key thermal-hydraulic parameters agree fairly well with the MARS ones. As a typical application case, steady-state analyses were conducted to have an assessment of thermal-hydraulic behavior under nominal condition, and several parameters affecting natural circulation were evaluated. What's more, two characteristics parameters that used to analyze natural circulation LFRs natural circulation capacity were established. The analyses show that the core thermal power, thermal center difference and flow resistance is the main factors affecting the reactor natural circulation. Improving the core thermal power, increasing the thermal center difference and decreasing the flow resistance can significantly increase the reactor mass flow rate. Characteristics parameters can be used to quickly evaluate the natural circulation capacity of natural circulation LFR under normal operating conditions.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.5
• /
• pp.569-582
• /
• 2023

Lead-acid Battery is the oldest rechargeable battery system and has maintained its position in the rechargeable battery field. The battery causes thermal runaway for various reasons, which can lead to major accidents. Therefore, preventing thermal runaway is a key part of the battery management system. Recently, research is underway to categorize thermal runaway battery cells into machine learning. In this paper, we present a thermal runaway hazard cell detection and verification algorithm using DBSCAN and statistical method. An experiment was conducted to classify thermal runaway hazard cells using only the resistance values as measured by the Battery Management System (BMS). The results demonstrated the efficacy of the proposed algorithms in accurately classifying thermal runaway cells. Furthermore, the proposed algorithm was able to classify thermal runaway cells between thermal runaway hazard cells and cells containing noise. Additionally, the thermal runaway hazard cells were early detected through the optimization of DBSCAN parameters using a grid search approach.

• Nuclear Engineering and Technology
• /
• v.56 no.8
• /
• pp.3286-3297
• /
• 2024

Traditional text-based system engineering, which has been used in the design and application of passive residual heat removal system (PRHRS) for lead-cooled fast reactors, is prone to several problems such as low development efficiency, long iteration cycles, and model ambiguity. This study aims to effectively address the abovementioned problems by adopting a model-based system engineering (MBSE) method, which has been preliminarily applied to meet the design requirements of a PRHRS. The design process has been implemented based on the preliminary design of the system architecture and consists of three stages: top-level requirement analysis, functional requirements analysis, and design requirements synthesis. The results of the top-level requirements analysis and the corresponding use case diagram can determine the requirements, top-level use cases, and scenario flow of the system. During the functional requirements analysis, the sequence, activity, and state machine diagrams are used to develop the system function model and provide early confirmation. By comparing these sequence diagrams, the requirements for omissions and inconsistencies can be effectively checked. In the design requirements synthesis stage, the Analytic Hierarchy Process is used to conduct preliminary trade-off calculations on the system architecture, after which a white box model is established during the system architecture design. Through these two steps, the analysis and design of the system architecture are ultimately achieved. The resulting system architecture ensures the consistency of the design requirements. Ultimately, a functional hazard analysis was conducted for a specific incident to validate case requirements and further refine the system architecture. Future research can further reduce the design risk, improve the design efficiency, and provide a practical reference for the design and optimization of PRHRS in digital lead-cooled fast reactors.

• Journal of Biosystems Engineering
• /
• v.7 no.1
• /
• pp.42-52
• /
• 1982

This study was intended to develop a cost function for the natural air in-bin drying: system which could lead to an optimization of the drying system cost. Based on the cost function developed, a series of simulated drying tests were conducted with 10-year weather data (1970~1979) for 7 different regions by applying an appropriate levels of system factors. System performance factors treated in this study were initial moisture content, airflow rate, bin diameter and grain depth. An optimization procedure to find the least cost system was developed as follows: First, the worst year of the past decade was determined in consideration of the dryiang time and maximum dry matter loss. Second, the minimum airflow rate for a fixed bin diameter and grain depth was determined. Third, the optimum grain depth was found for the minimum airflow rate with different initial moisture contents and bin diameters. The results obtained in this study are summarized as follows: 1. The optimization procedure developed in this study was able to reduce the time and efforts significantly. 2. Optimum values of drying parameters including airflow rate, grain depth, and fan size were determined for different initial moisture contents and bin diameters in each region. The results are shown in Tables 3 to 9. 3. Optimum grain depths decreased as the initial moisture content and airflow rate increased. 4. Drying time for the least cost system should be reduced with higher initial moisture content and lower drying potential to prevent grain spoilage. 5. The fixed cost was 65 to 75 percent of the total system cost and the variable cost was 25 to 35 percent. To reduce the fixed cost it is desirable to use a drying bin 2 or 3 times a year.

• Earthquakes and Structures
• /
• v.19 no.5
• /
• pp.347-359
• /
• 2020

The Mega-Sub Controlled Structure System (MSCSS), an innovative vibration passive control system for building structures, is improved by adding lead rubber bearings (LRBs) on top of the substructure. For the new system, a genetic algorithm is used to optimize the dynamic parameters and distributions of dampers and LRBs. The program uses various seismic performance indicators as optimization objectives, and corresponding results are compared. It is found that the optimization procedure for maximizing the energy dissipation ratio yields the best solutions, and optimized models have consistent seismic performances under different earthquakes. Seismic performances of optimized MSCSS models with and without LRBs, as well as the traditional Mega-Sub Structure model, are evaluated and compared under El Centro wave, Taft wave and 20 other artificial waves. In both elastic and plastic analysis, the model with LRBs shows significantly smaller story drift and horizontal acceleration than those of the other two models, and fewer plastic hinges are developed during severe earthquakes. Energy analysis also shows that LRBs installed in proper locations increase the deformation and energy dissipation of dampers, thereby significantly reduce the kinetic, potential, and hysteretic energy in the structure. However, LRBs do not have to be mounted on all the additional columns. It is also demonstrated that LRBs at unfavorable locations can decrease the energy dissipation for dampers. After LRBs are installed, the optimal damping coefficient and the optimal damping exponent of dampers are reduced to produce the best damping effect.

• Journal of Mechanical Science and Technology
• /
• v.19 no.5
• /
• pp.1072-1079
• /
• 2005

Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.1
• /
• pp.184-192
• /
• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.16 no.4
• /
• pp.345-351
• /
• 2003

Due to increasing legal and market demands for safety in the automotive design process, the design of integrated seat is important more and mote because it should satisfy the conflict between stronger and lower weight for safety and environmental demands. In this study for crash simulations, the numerical simulations have been carried out using the explicit finite element program LS-Dyna according to the FMVSS 210 standard for safety test of seat. Since crash simulations are very time-consuming and a series of simulations that does not lead to a better result is very costly, the optimization method must be both efficient and reliable. As a result of that, statistical approaches such as design of experiments and response surface model have been successfully implemented to reduce time-consuming LS-Dyna simulations and optimize the safety and environmental demands together with nonlinear optimization algorithm. Design of experiments is used lot exploring the design space of maximum displacement and total weight and for building response surface models in order to minimize the maximum displacement and total weight of integrated seat.

• Nuclear Engineering and Technology
• /
• v.53 no.1
• /
• pp.258-265
• /
• 2021

High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.

• Nuclear Engineering and Technology
• /
• v.53 no.6
• /
• pp.1970-1978
• /
• 2021

The aim of this study was to optimize the target, moderator, and collimator (TMC) in a neutron beam generator for the accelerator-based BNCT (A-BNCT) system. The optimization employed the Monte Carlo Neutron and Photon (MCNP) simulation. The optimal geometry for the target was decided as the one with the highest neutron flux among nominates, which were called as angled, rib, and tube in this study. The moderator was optimized in terms of consisting material to produce appropriate neutron energy distribution for the treatment. The optimization of the collimator, which wrapped around the target, was carried out by deciding the material to effectively prevent the leakage radiations. As results, characteristic of the neutron beam from the optimized TMC was compared to the recommendation by the International Atomic Energy Agent (IAEA). The tube type target showed the highest neutron flux among nominates. The optimal material for the moderator and collimator were combination of Fluental (Al₂0₃+AlF₃) with ⁶⁰Ni filter and lead, respectively. The optimized TMC satisfied the IAEA recommendations such as the minimum production rate of epithermal neutrons from thermal neutrons: that was 2.5 times higher. The results can be used as source terms for shielding designs of treatment rooms.