• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.1
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• pp.22-28
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• 2019

Cement is a basic material for the construction industry and it requires high temperature sintering when manufacturing cement. $CO_2$ emissions from raw materials and fuels are recognized as new environmental problems and efforts are underway to reduce them. Techniques for reducing $CO_2$ in concrete are also recommended to use blended cement such as blast furnace slag or fly ash. In addition, the construction waste generated in the dismantling of concrete structures is recognized as another environmental problem. Thus, various methods are being implemented to increase the recycling rate. The purpose of this study is to utilize the inorganic raw materials generated during the dismantling of the structure as a raw material for the low carbon type cement binder. Such as, waste concrete powder, waste cement block, waste clay brick and waste textile as raw materials for low carbon type cement binder. From the research results, low carbon type cement binder was manufactured from the raw material composition of waste concrete powder, waste cement block, waste clay brick and waste textile.

• Composites Research
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• v.36 no.1
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• pp.16-24
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• 2023

This paper presents a multi-scale progressive fatigue damage model incorporating the model for interfacial debonding between fibers and matrix. The micromechanics model for the progressive interface debonding was adopted, which defined the four different interface phases: (1) perfectly bonded fibers; (2) mild imperfect interface; (3) severe imperfect interface; and (4) completely debonded fibers. As the number of cycles increases, the progressive transition from the perfectly bonded state to the completely debonded fiber state occurs. Eshelby's tensor for each imperfect state is calculated by the linear spring model for a damaged interface, and effective elastic properties are obtained using the multi-phase homogenization method. The fatigue damage evolution formulas for fiber, matrix and interface were proposed to demonstrate the fatigue behavior of CFRP laminates under cyclic loading. The material parameters for the fiber/matrix fatigue damage were characterized using the chaotic firefly algorithm. The model was implemented into the UMAT subroutine of ABAQUS, and successfully validated with flat-bar UD laminate specimens ([0]₈,[90]₈, [30]₁₆) of AS4/3501-6 graphite/epoxy composite.

• Resources Recycling
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• v.33 no.3
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• pp.21-29
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• 2024

Globally, the demand for electric vehicles (EVs) is surging due to carbon-neutral strategies aimed at decarbonization. Consequently, the demand for lithium-ion batteries, which are essential components of EVs, is also rising, leading to an increase in the generation of spent batteries. This has prompted research into the recycling of spent batteries to recover valuable metals. In this study, we aimed to selectively leach and recover lithium from the cathode material of spent LFP batteries. To enhance the reaction surface area and reactivity, the binder in the cathode material powder was removed, and the material was subjected to heat treatment in both atmospheric and nitrogen environments across various temperature ranges. This was followed by a mechanochemical process for aqueous leaching. Initially, after heat treatment, the powder was converted into a soluble lithium compound using sodium persulfate (Na₂S₂O₈) in a mechanochemical reaction. Subsequently, aqueous leaching was performed using distilled water. This study confirmed the changes in the characteristics of the cathode material powder due to heat treatment. The final heat treatment in a nitrogen atmosphere resulted in a lithium leaching efficiency of approximately 100% across all temperature ranges.

• Journal of the Korean Electrochemical Society
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• v.16 no.2
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• pp.59-64
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• 2013

Using $Na_2CO_3$ and $MeSO_4$ (Me = Ni, Co and Mn) as starting materials, the precursor of $[Ni_{0.6}Co_{0.2}Mn_{0.2}]CO_3$ has been synthesized by carbonate co-precipitation. The precursor was mixed with $Li_2CO_3$, and calcined at 750, 850, and$950^{\circ}C$ in air. Effect of calcinations temperature on characteristics of $Li[Ni_{0.6}Co_{0.2}Mn_{0.2}]O_2$ cathode materials was investigated. The structure and characteristics of $Li[Ni_{0.6}Co_{0.2}Mn_{0.2}]O_2$ were determined by X-ray diffraction (XRD), Scanning electron microscopy (SEM) and electrochemical measurements. The X-ray diffraction (XRD) results show that the intensity ratio of $I_{(003)}/I_{(104)}$ increased and the R-factor ratio decreased with the increase of calcinations temperature. And Scanning electron microscopy (SEM) result show that the primary particle size increased. Especially, the $Li[Ni_{0.6}Co_{0.2}Mn_{0.2}]O_2$ calcined at $950^{\circ}C$ for 24 H shows excellent electrochemical performances with reversible specific capacity of $165.3mAhg^{-1}$ [cut-off voltage 2.5~4.3 V, 0.1 C($17mAhg^{-1}$)] and good capacity retention of 95.4% after 50th charge/discharge cycles[cut-off voltage 2.5~4.3 V, 1 C($170mAhg^{-1}$)].

• Journal of the Korean Electrochemical Society
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• v.13 no.2
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• pp.116-122
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• 2010

A $Cu_3Si$ film electrode is obtained by Si deposition on a Cu foil using DC magnetron sputtering, which is followed by annealing at $800^{\circ}C$ for 10 h. The Si component in $Cu_3Si$ is inactive for lithiation at ambient temperature. The linear sweep thermammetry (LSTA) and galvano-static charge/discharge cycling, however, consistently illustrate that $Cu_3Si$ becomes active for the conversion-type lithiation reaction at elevated temperatures (> $85^{\circ}C$). The $Cu_3Si$ electrode that is short-circuited with Li metal for one week is converted to a mixture of $Li_{21}Si_5$ and metallic Cu, implying that the Li-Si alloy phase generated at 0.0 V (vs. Li/$Li^+$) at the quasi-equilibrium condition is the most Li-rich $Li_{21}Si_5$. However, the lithiation is not extended to this phase in the constant-current charging (transient or dynamic condition). Upon de-lithiation, the metallic Cu and Si react to be restored back to $Cu_3Si$. The $Cu_3Si$ electrode shows a better cycle performance than an amorphous Si electrode at $120^{\circ}C$, which can be ascribed to the favorable roles provided by the Cu component in $Cu_3Si$. The inactive element (Cu) plays as a buffer against the volume change of Si component, which can minimize the electrode failure by suppressing the detachment of Si from the Cu substrate.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.257-266
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• 2007

In On-Chip bus, the arbitration scheme is one of the critical factors that decide the overall system performance. The arbitration scheme used in traditional shared bus is the master-side arbitration based on the request and grant signals between multiple masters and single arbiter. In the case of the master-side arbitration, only one master and one slave can transfer the data at a time. Therefore the throughput of total bus system and the utilization of resources are decreased in the master-side arbitration. However in the slave-side arbitration, there is an arbiter at each slave port and the master just starts a transaction and waits for the slave response to proceed to the next transfer. Thus, the unit of arbitration can be a transaction or a transfer. Besides the throughput of total bus system and the utilization of resources are increased since the multiple masters can simultaneously perform transfers with independent slaves. In this paper, we implement and analyze the arbitration schemes for the Multi-Layer AHB BusMatrix based on the slave-side arbitration. We implement the slave-side arbitration schemes based on fixed priority, round robin and dynamic priority and accomplish the performance simulation to compare and analyze the performance of each arbitration scheme according to the characteristics of the master and slave. With the performance simulation, we observed that when there are few masters on critical path in a bus system, the arbitration scheme based on dynamic priority shows the maximum performance and in other cases, the arbitration scheme based on round robin shows the highest performance. In addition, the arbitration scheme with transaction based multiplexing shows higher performance than the same arbitration scheme with single transfer based switching in an application with frequent accesses to the long latency devices or memories such as SDRAM. The improvements of the arbitration scheme with transaction based multiplexing are 26%, 42% and 51%, respectively when the latency times of SDRAM are 1, 2 and 3 clock cycles.

• Korean Chemical Engineering Research
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• v.44 no.4
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• pp.410-416
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• 2006

For highly efficient operation of a Bunsen process section in an iodine-sulfur thermochemical hydrogen production cycle using nuclear heat, the process characteristics of $H_2SO_4-HI-H_2-O-I_2$ mixture system for separating into two liquid phases ($H_2SO_4$-rich phase and $HI_x$-rich phase) and the distribution of $H_2O$ to each phase were investigated.The experiments for process variables were carried out in the temperature range, from 298 to 353 K, and in the $H_2SO_4/HI/H_2O/I_2$ molar ratio of 1/2/14~20/0.5~8.0. As the results, for the $SO_2-I_2-H_2O$ Bunsen reaction system, the ranges between the starting point and the saturation point for two liquid phases separation were determined by calculation. The best result for the minimization of impurities (HI and $I_2$ in $H_2SO_4$ phase and $H_2SO_4$ in $HI_x$ phase) in each phase was obtained in an optimum condition with the highest temperature of 353 K and the highest $I_2$ molar composition. In this condition, the $HI/H_2SO_4$ molar ratio in the $H_2SO_4$-rich phase and the $H_2SO_4/HI_x$ molar ratio in the $HI_x$-rich phase were 0.024 and 0.028, respectively. For the distribution of $H_2O$ to each phase, it is appeared that the affinity between $HI_x$ and $H_2O$ was more superior to that between $H_2SO_4$ and $H_2O$. The affinity between $HI_x$ and $H_2O$ was decreased with increasing temperature but increased with increasing $I_2$ molar composition.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.68-78
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• 2020

According to the new climate change agreement, technology development to reduce greenhouse gases is actively conducted worldwide, and research on energy efficiency improvement in the field of power generation and transmission and distribution is underway [1,2]. Economic analysis of the operation method of storing and supplying surplus electricity using energy storage devices, and using energy storage devices as a frequency adjustment reserve power in regional cogeneration plants has been reported as the most profitable operation method [3-7]. Therefore, this study conducted an economic analysis for the installation of energy storage devices in the combined heat and power plant in the Czech Republic. The most important factor in evaluating the economics of battery energy storage devices is the lifespan, and the warranty life is generally 10 to 15 years, based on charging and discharging once a day. For the simulation, the ratio of battery and PCS was designed as 1: 1 and 1: 2. In general, the primary frequency control is designed as 1: 4, but considering the characteristics of the cogeneration plant, it is set at a ratio of up to 1: 2, and the capacity is simulated at 1MW to 10MW and 2MWh to 20MWh according to each ratio. Therefore, life was evaluated based on the number of cycles per year. In the case of installing a battery energy storage system in a combined heat and power plant in the Czech Republic, the payback period of 3MW / 3MWh is more favorable than 5MW / 5MWh, considering the local infrastructure and power market. It is estimated to be about 3 years or 5 years from the simple payback period considering the estimated purchase price without subsidies. If you lower the purchase price by 50%, the purchase cost is an important part of the cost for the entire lifetime, so the payback period is about half as short. It can be, but it is impossible to secure profitability through the economy at the scale of 3MWh and 5MWh. If the price of the electricity market falls by 50%, the payback period will be three years longer in P1 mode and two years longer in P2 and P3 modes.

• Journal of the Korean Electrochemical Society
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• v.23 no.4
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• pp.105-112
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• 2020

Transition metal oxide, which undergoes a conversion reaction in the negative electrode material for a lithium-ion batteries, has a high specific capacity, but still has several critical problems. In this study, manganese pyrophosphate (Mn₂P₂O₇), nickel pyrophosphate (Ni₂P₂O₇), and carbon composite materials with pyrophosphates as novel negative electrode materials instead of transition metal oxide, are synthesized through simple solid-state reaction. The initial reversible capacity of Mn₂P₂O₇ and Ni₂P₂O₇ are 333 and 340 mAh g^-1, and when the composite materials are composed with carbon, the reversible capacity increases to 433 and 387 mAh g^-1, respectively. The initial Coulombic efficiency is also improved by about 10%. The Mn₂P₂O₇ and carbon composite material has the highest initial capacity and efficiency, and has the best cycle performance. Mn₂P₂O₇ containing polyanion, has a lower specific capacity due to the large mass of polyanion compared to MnO (manganese oxide). However, since Mn₂P₂O₇ shows a voltage curve with a slope, the charging (lithiation) voltage increases from 0.51 to 0.57 V (vs. Li/Li⁺), and the discharge (delithiation) voltage decreases from 1.15 to 1.01 V (vs. Li/Li⁺). Therefore, the voltage efficiency of the cell is improved because the voltage difference between charging and discharging is greatly reduced from 0.64 to 0.44 V, and the operating voltage of the full cell increases because the negative electrode potential is lowered during the discharging process.