• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.5
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• pp.357-363
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• 2021

Eco-friendly hybrid railroad propulsion system with fuel-cell and battery was suggested to reduce carbon dioxide gas and replace retired diesel railroads. Lithium-ion battery with high energy/power density and long lifetime is selected as the energy source at the battery side due to its excellent performance. However, the performance of lithium-ion batteries was affected by temperature, current rate, and operating condition. Temperature is known to be the most influential factor in changing battery parameters. In addition, appropriate thermal management is required to ensure the safe and effective operation of lithium-ion battery. Electro-thermal coupled model with varying parameter depends on temperature, and state-of-charge (SOC) is suggested to estimate battery temperature. The electric-thermal coupled model contains diffusion current using parameter identification by adaptive control algorithm when considering thermal diffusion effect. An experiment under forced convection was conducted using cylindrical cell and 18 parallel-connected battery module to demonstrate the method.

• Wind and Structures
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• v.29 no.4
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• pp.225-234
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• 2019

Conductor galloping is a common disaster for the transmission lines. Among the existing analytical methods, the wind tunnel test is highlighted as the most effective approach to obtain the aerodynamic coefficients. In this paper, the aerodynamic coefficients of 12 conductor models covered with the crescent-shaped ice, which were fabricated considering the surface roughness of the iced conductor, were obtained based on the wind tunnel test. The influence of the Reynolds number and the shape parameter ${\beta}$, defined as the ratio of ice thickness to the diameter, were investigated. In addition, the effect of surface roughness of the iced conductor was discussed. Subsequently, unsteady areas of conductor galloping were calculated according to the Den Hartog criterion and the Nigol criterion. The results indicate that the aerodynamic coefficients of iced conductors change sharply at the attack angles of $20^{\circ}$ and $170^{\circ}$ with the increase of ${\beta}$. The surface roughness of iced conductors changed the range of attack angle, which was influenced by the increase of the Reynolds number. The experimental results can provide insights for preventing and controlling galloping.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1017-1023
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• 2018

The measurement and calculation of neutronic parameters in nuclear research reactors has an important influence on control and safety of the nuclear reactor. The power peaking factors, reactivity coefficients and kinetic parameters are the most important neutronic parameter for determining the state of the reactor. The position of the control shim safety rods in the core configuration affects these parameters. The main purpose of this work is to use the MTR_PC package to evaluate the effect of the partially insertion of the control rod on the neutronic parameters at the operating core of the Tehran Research Reactor. The simulation results show that by increasing the insertion of control rods (bank) in the core, the absolute values of power peaking factor, reactivity coefficients and effective delayed neutron fraction increased and only prompt neutron life time decreased. In addition, the results show that the changes of moderator temperature coefficients value versus the control rods positions are very significant. The average value of moderator temperature coefficients increase about 98% in the range of 0-70% insertion of control rods.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Computers and Concrete
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• v.33 no.5
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• pp.545-557
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• 2024

A real-case incident occurred where a 9-meter-high segment of a pre-fabricated concrete separation wall unexpectedly collapsed. This collapse was triggered by improperly depositing excavated soil against the wall's back, a condition for which the wall segments were not designed to withstand lateral earth pressure, leading to a flexural failure. The event's analysis, integrating technical data and observational insights, revealed that internal forces at the time of failure significantly exceeded the wall's capacity per standard design. The Lattice Discrete Particle Model (LDPM) further replicates the collapse mechanism. Our approach involved defining various parameter sets to replicate the concrete's mechanical response, consistent with the tested compressive strength. Subsequent stages included calibrating these parameters across different scales and conducting full-scale simulations. These simulations carried out with various parameter sets, were thoroughly analyzed to identify the most representative failure mechanism. We developed an equation from this analysis that quickly correlates the parameters to the wall's load-carry capacity, aligned with the simulation. Additionally, our study examined the wall's post-peak behavior, extending up to the point of collapse. This aspect of the analysis was essential for preventing failure, providing crucial time for intervention, and potentially averting a disaster. However, the reinforced concrete residual state is far from being fully understood. While it's impractical for engineers to depend on the residual state of structural elements during the design phase, comprehending this state is essential for effective response and mitigation strategies after initial failure occurs.

• Journal of Powder Materials
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• v.31 no.2
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• pp.137-145
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• 2024

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.565-576
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• 2024

In this study, the earthquake risk assessment of single-story RC precast buildings in Turkey was carried out using loss curves. In this regard, Kocaeli, a seismically active city in the Marmara region, and this building class, which is preferred intensively, were considered. Quality and period parameters were defined based on structural and geometric properties. Depending on these parameters, nine main sub-classes were defined to represent the building stock in the region. First, considering the mean fragility curves and four different central damage ratio models, vulnerability curves for each sub-class were computed as a function of spectral acceleration. Then, probabilistic seismic hazard analyses were performed for stiff and soft soil conditions for different earthquake probabilities of exceedance in 50 years. In the last step, 90 loss curves were derived based on vulnerability and hazard results. Within the scope of the study, the comparative parametric evaluations for three different earthquake intensity levels showed that the structural damage ratio values for nine sub-classes changed significantly. In addition, the quality parameter was found to be more effective on a structure's damage state than the period parameter. It is evident that since loss curves allow direct loss ratio calculation for any hazard level without needing seismic hazard and damage analysis, they are considered essential tools in rapid earthquake risk estimation and mitigation initiatives.

• Advances in nano research
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• v.17 no.4
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• pp.335-350
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• 2024

This paper investigates the mechanical behavior of a new type of functionally graded graphene-reinforced nanocomposite (FG-GRNC) doubly-curved laminated shells, referred to as cosine FG-GRNC. The study employs a refined higher-order shear deformation shell theory combined with a modified continuum nonlocal strain gradient theory. The effective Young's modulus of the GRNC shell in the thickness direction is determined using the modified Halpin-Tsai model, while Poisson's ratio and mass density are calculated using the rule of mixtures. The analysis includes two graphene-reinforced distribution patterns-FG-A CNRCs and FG-B CNRCs-along with uniform UD CNRCs. An enhanced Galerkin method is used to solve the governing equilibrium equations for the GRNC nanoshell, yielding closed-form solutions for bending deflection and critical buckling loads. The nanoshell is supported by an orthotropic elastic foundation characterized by three parameters. A detailed parametric analysis is performed to evaluate how factors such as the length scale parameter, nonlocal parameter, distribution pattern, GPL weight fraction, shell thickness, and shell geometry influence deflections and critical buckling loads.

• Journal of the Korea Computer Industry Society
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• v.9 no.1
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• pp.21-28
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• 2008

In this paper, the edge parameters were drawn from speaking image around lip and effective automatic lip reading system to recognize the Korean 'a/e/i/o/u' 5 owels were constructed using the parameter. Speaking images around lip were divided into $5{\times}5$ pane. In each pane the number of digital edge element using Sobel operator were evaluated. The observational error between samples was corrected by using normalization method and the normalized value is used for parameter In the experiment to convince the strength of parameter, 50 normal persons were sampled. The images of 10 persons were analyzed and the images of another 40 persons were experimented for recognition. 500 data are gathered and analyzed. Based on this analysis, the neural net system is constructed and the recognition experiments are performed for 400 data. The neural net system gave the best recognition result of 91.1%.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.3
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• pp.19-27
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• 1982

Minimization of total routing and number of cuts has been adopted for the placement problem in LSI and printed wire board as the object function, recently. Although it is considered that in the general situation this object function reflects the final goal which is wiring of 100% of layout, it often seems to be insufficient because it does not exhibit partial wire congestion. This paper introduces a new concept called the wire congestion of segestion to get the partial wire congestion and proposes the object function to minimize the wire congestion of segmests. In order to optimize this object function, an effective heuristic algorithm is also suggestsl Experimental results show that this algorithm sustains its efficiency. The experimental consequences point out that if the total routing length is short, maximum wire congestion of segment is small and vice versa. Therefore control parameter, that is, congestion parameter, which mintnizes total length and concurrently reduces maximal wire congestion of segment, is obtained by experiment.