• Smart Structures and Systems
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• v.15 no.1
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• pp.119-133
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• 2015

This paper proposed a structural time-varying damage detection method by using synchrosqueezing wavelet transform. The instantaneous frequencies of a structure with time-varying damage are first extracted using the synchrosqueezing wavelet transform. Since the proposed synchrosqueezing wavelet transform is invertible, thus each individual component can be reconstructed and the modal participation factor ratio can be extracted based on the amplitude of the analytical signals of the reconstructed individual components. Then, the new time-varying damage index is defined based on the extracted instantaneous frequencies and modal participation factor ratio. Both free and forced vibrations of a classical Duffing nonlinear system and a simply supported beam structure with abrupt and linear time-varying damage are simulated. The proposed synchrosqueezing wavelet transform method can successfully extract the instantaneous frequencies of the damaged structures under free vibration or vibration due to earthquake excitation. The results also show that the defined time-varying damage index can effectively track structural time-varying damage.

• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.17-37
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• 2011

This paper presents a new Internet-based computational framework for the realistic simulation of multi-scale response of structural systems. Two levels of parallel processing are involved in this frame work: multiple local distributed computing environments connected by the Internet to form a cluster-to-cluster distributed computing environment. To utilize such a computing environment for a realistic simulation, the simulation task of a structural system has been separated into a simulation of a simplified global model in association with several detailed component models using various scales. These related multi-scale simulation tasks are distributed amongst clusters and connected to form a multi-level hierarchy. The Internet is used to coordinate geographically distributed simulation tasks. This paper also presents the development of a software framework that can support the multi-level hierarchical simulation approach, in a cluster-to-cluster distributed computing environment. The architectural design of the program also allows the integration of several multi-scale models to be clients and servers under a single platform. Such integration can combine geographically distributed computing resources to produce realistic simulations of structural systems.

• Structural Monitoring and Maintenance
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• v.6 no.2
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• pp.161-171
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• 2019

There have been a few checking frameworks intended to ensure and improve the nature of their regular habitat. The greater part of these frameworks are constrained in their capacities. In this paper, the insightful checking framework intended for debacle help and administrations has been exhibited. The ideal administrations, necessities and coming about plan proposition have been indicated. This has prompted a framework that depends fundamentally on ecological examination so as to offer consideration and security administrations to give the self-governance of indigenous habitats. In this sense, ecological acknowledgment is considered, where, in light of past work, novel commitments have been made to help include based and PC vision situations. This epic PC vision procedure utilized as notice framework for avalanche identification depends on changes in the normal landscape. The multi-criteria basic leadership strategy is used to incorporate slope data and the level of variety of the highlights. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

• Smart Structures and Systems
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• v.24 no.4
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• pp.507-524
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• 2019

A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4203-4223
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• 2021

Accelerated by the Internet of Things (IoT), the need for further technical innovations and developments within wireless communications beyond the fifth generation (B5G) networks is up-and-coming in the past few years. High altitude platform station (HAPS) communication is expected to achieve such high levels that, with high data transfer rates and low latency, millions of devices and applications can work seamlessly. The HAPS has emerged as an indispensable component of next-generations of wireless networks, which will therefore play an important role in promoting massive IoT interconnectivity with 6G. The performance of communication and key technology mainly depend on the characteristic of channel, thus we propose an efficient Markov chain based channel model, then analyze the HAPS communication system's uplink capability and swing effect through experiments. According to the simulation results, the efficacy of the proposed scheme is proven to meet the requirements of ubiquitous connectivity in future IoT enabled by 6G.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.3
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• pp.269-278
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• 2022

The buffer is a critical barrier component in an engineered barrier system, and its purpose is to prevent potential radionuclides from leaking out from a damaged canister by filling the void in the repository. No experimental parameters exist that can describe the buffer expansion phenomenon when Kyeongju bentonite, which is a buffer candidate material available in Korea, is exposed to groundwater. As conventional experiments to determine these parameters are time consuming and complicated, simple swelling pressure tests, numerical modeling, and machine learning are used in this study to obtain the parameters required to establish a numerical model that can simulate swelling. Swelling tests conducted using Kyeongju bentonite are emulated using the COMSOL Multiphysics numerical analysis tool. Relationships between the swelling phenomenon and mechanical parameters are determined via an artificial neural network. Subsequently, by inputting the swelling tests results into the network, the values for the mechanical parameters of Kyeongju bentonite are obtained. Sensitivity analysis is performed to identify the influential parameters. Results of the numerical analysis based on the identified mechanical parameters are consistent with the experimental values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.261-279
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• 2023

In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

• Journal of Hydrogen and New Energy
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• v.34 no.5
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• pp.465-477
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• 2023

In proton exchange membrane fuel cell (PEMFC), proper thermal management of the stack and moisture generation by electrochemical reactions significantly affect fuel cell performance. In this study, the PEMFC dynamic characteristic model was developed through Simcenter AMESim, a development program. In addition, the developed model aims to understand the thermal resin balance of the stack and performance characteristics for input loads. The developed model applies the thermal management model of the stack and the moisture content and permeability model to simulate voltage loss and stack thermal behavior precisely. This study extended the C based AMESet (adaptive modeling environment submodeling tool) to simulate electrochemical reactions inside the stack. Fuel cell model of AMESet was liberalized with AMESim and then integrated with the balance of plant (BOP) model and analyzed. And It is intended to be used in component design through BOP analysis. The resistance loss of the stack and thermal behavior characteristics were predicted, and the impact of stack performance and efficiency was evaluated.

• Korean Medical Education Review
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• v.26 no.1
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• pp.19-26
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• 2024

This study examines a systematic and effective approach to career guidance in medical education, with a particular focus on the 6-year integrated career guidance education framework implemented at the College of Medicine, The Catholic University of Korea. Based on the "New SLICE" educational development principles, this framework comprehensively addresses the needs of medical students in career planning and development. It is structured into three phases: understanding yourself, exploring options, and choosing a specialty. The first phase, understanding yourself, helps students to recognize their strengths, weaknesses, aptitudes, and potentials, thereby setting the direction for future career choices. This phase includes various psychological tests and Self-Development and Portfolio courses. The second phase, exploring options, enables students to engage in related activities such as research and practical training, providing direct and indirect experiences across various fields. This phase offers courses including Medical Field Experience, Career Guidance through the Learning Community & Advisory Professors, and Student Participation in Professor Research Projects. The final phase, choosing a specialty, involves students making decisions based on in-depth self-assessment and exploration of majors, with a capstone project being a significant component. Maximizing the efficiency of career decision-making requires integration between the basic medical curriculum and postgraduate education. Including the period up to residency entrance in the framework is necessary for effective career guidance education.

• Smart Structures and Systems
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• v.33 no.6
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• pp.385-398
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• 2024

To improve the accuracy of time-frequency analysis (TFA) and instantaneous frequency (IF) extraction of structural dynamic response signals, this paper improves the spline-kernelled chirplet transform, and a new form of modified spline-kernelled chirplet transform (MSCT) based on revised Gaussian window function and energy concentration principle is put forward. The effectiveness of the proposed method is verified by numerical examples of single-component signal, multicomponent signal, single-degree-of-freedom Duffing nonlinear system and two-layer shear frame structure model. Then, a time-varying cable test is designed to collect the acceleration response signals under linear changing tension, and the IF extraction of these signals is performed by using MSCT, which further verifies the effectiveness and accuracy of this method. Through numerical simulation and experimental verification, it is proved that the proposed method can effectively extract the IF of nonlinear structure and time-varying structure.