• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.50-63
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• 2015

Explosive bolts are one of pyrotechnic release devices, which are highly reliable and efficient for a built-in release. Among them, ridge-cut explosive bolts which utilize shock wave generated by detonation to separate bolt body produce minimal fragments, little swelling and clean breaks. In this study, separation phenomena of ridge-cut explosive bolts or ridge-cut mechanism are computationally analyzed using Hydrocodes. To analyze separation mechanism of ridge-cut explosive bolts, fluid-structure interactions with complex material modeling are essential. For modeling of high explosives (RDX and PETN), Euler elements with Jones-Wilkins-Lee E.O.S. are utilized. For Lagrange elements of bolt body structures, shock E.O.S., Johnson-Cook strength model, and principal stress failure criteria are used. From the computational analysis of the author's explosive bolt model, computational analysis framework is verified and perfected with tuned failure criteria. Practical design improvements are also suggested based on a parametric study. Some design parameters, such as explosive weights, ridge angle, and ridge position, are chosen that might affect the separation reliability; and analysis is carried out for several designs. The results of this study provide useful information to avoid unnecessary separation experiments related with design parameters.

• Computers and Concrete
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• v.14 no.4
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• pp.463-477
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• 2014

The modelling approach in the case of connections in precast buildings is specific. The assembly of the constitutive parts of the connection requires the inclusion of contact definitions in the model. In addition, the material non-linearity including the influence of the spatial stress distribution should be taken into account where appropriate. Here a complex model of a beam-to-column dowel connection is presented. Experiments on the analysed connection were performed within the framework of the European project SAFECAST (Performance of Innovative Mechanical Connections in Precast Building Structures under Seismic Conditions). Several material and interaction parameters were investigated and the influence of each of them was evaluated. The set of parameters which gave the best match with the experiments was chosen.

• Agribusiness and Information Management
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• v.8 no.1
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• pp.11-16
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• 2016

This paper presents how Digital Knowledge Ecosystem such as "Govi Nena" (translates as agriculture intelligence) can be used to provide a more effective and practical solution to eliminate the inefficiencies in agricultural markets and achieve higher productivity and price stability. In order to establish the framework to analyze the system, this paper uses a set of hypothetical scenarios faced by value chain actors based on a review of the literature, established knowledge and recent developing country experiences. The scenario analysis reveals that "Govi Nena" enables farmers to make effective production decisions, deepens the level of value chain integration, and enhances the level of welfare for the society as a whole.

• Economic and Environmental Geology
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• v.24 no.3
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• pp.309-318
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• 1991

Analysis for landslides was studied in framework of Chungju dam right abutment, 6.5km northeast of Chungju city. $5.5{\times}10^6m^3$ landslide materials were excavated during dam construction for safety of the Chungju dam. Geology of study area is composed mainly of meta sediments such as dolomitic limestone, quartzite and schist which are dipping toward the Nam Han river. Scanline survey of discontinuities was performed for slope stability, resistivity exploration was performed for the evaluation of potential failure plane, and direct shear strength test of rocks and soils was performed for the effect on landslide. Monitoring systems of tiltmeter, tensiometer, ground water observation hole and level monument were installed during dam construction and interpreted for the evaluation of slope instability. Kinematic solution of the geological structure and evaluation using safety factor for slope may prove the failure of the slope.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.spc
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• pp.63-74
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• 2020

The operational safety assessment is an important part of a safety case for the deep geological repository of spent fuels. It consists of different stages such as the identification of initiating events, event tree analysis, fault tree analysis, and evaluation of exposure doses to the public and radiation workers. This study develops a probabilistic safety assessment method for the operational safety assessment and establishes an assessment framework. For the event and fault tree analyses, we propose the advanced information management system for probabilistic safety assessment (AIMS-PSA Manager). In addition, we propose the Radiological Safety Analysis Computer (RSAC) program to evaluate exposure doses to the public and radiation workers. Furthermore, we check the applicability of the assessment framework with respect to drop accidents of a spent fuel assembly arising out of crane failure, at the surface facility of the KRS⁺ (KAERI Reference disposal System for SNFs). The methods and tools established through this study can be used for the development of a safety case for the KRS⁺ system as well as for the design modification and the operational safety assessment of the KRS⁺ system.

• Interaction and multiscale mechanics
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• v.3 no.1
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• pp.23-37
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• 2010

Concrete is a heterogeneous material consisting of coarse aggregate, mortar matrix and interfacial zones at the meso level. Though studies have been done to interpret the fracture process in concrete using meso level models, not much work has been done for simulating the macroscopic behaviour of reinforced concrete structures using the meso level models. This paper presents a procedure for the mesoscopic analysis of reinforced concrete beams using a modified micro truss model. The micro truss model is derived based on the framework method and uses the lattice meshes for representing the coarse aggregate (CA), mortar matrix, interfacial zones and reinforcement bars. A simple procedure for generating a random aggregate structure is developed using the constitutive model at meso level. The study reveals the potential of the mesoscopic numerical simulation using a modified micro truss model to predict the nonlinear response of reinforced concrete structures. The modified micro truss model correctly predicts the load-deflection behaviour, crack pattern and ultimate load of reinforced concrete beams failing under different failure modes.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• Structural Engineering and Mechanics
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• v.91 no.4
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• pp.369-382
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• 2024

The earthquake loss assessment framework of ductile reinforced concrete (or RC) frame using component-performance -based methodology was studied in this paper. The elasto-plastic rotation angle was used as the damage indicator of structural component, and the damage-to-loss model was proposed on the basis of the deformation indicator of structural component. Dynamic instability during incremental dynamic analysis was taken as collapse criterion, and column failure was taken as criterion that structure has to be demolished. Expected earthquake losses of low-rise, mid-rise and high-rise RC frames were discussed. The expected earthquake loss encompassed collapse loss, demolition loss and repair loss. Furthermore, component groups of RC frame were divided into structural components, nonstructural components and rugged components. The results indicate that ductile RC frame is more likely to be demolished than collapse, especially in low-rise and mid-rise RC frames. Furthermore, the less collapse margin ratio the structure has, the more demolition probability the structure will suffer under rare earthquake. The demolition share of total earthquake loss might be more prominent than repair share and collapse share in ductile RC frame.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.70-76
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• 2014

In industrial situation, electronic and electro-mechanical systems have been using different type of batteries in rapidly increasing numbers. These systems commonly require high reliability for long periods of time. Wider application of battery for low-power design as a prime power source requires us knowledge of failure mechanism and reliability of batteries in terms of load condition, environment condition and other explanatory variables. Battery life is an important factor that affects the reliability of such systems. There is need for us to understand the mechanism leading to the failure state of battery with performance characteristic and develop a method to predict the life of such battery. The purpose of this paper is to develope the methodology of monitoring the health of battery and determining the condition or fate of such systems through the performance reliability to predict the remaining useful life of primary battery with load condition, operating condition, environment change in light of battery life variation. In order to evaluate on-going performance of systems and subsystems adopting primary batteries as energy source, The primitive prototype for performance reliability analysis device was developed and related framework explained.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.