• Journal of Korean Tunnelling and Underground Space Association
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• v.3 no.4
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• pp.35-55
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• 2001

Recently, as tunnel structures are getting older and decrepit, many tunnel inspections are carried out for evaluating the tunnel state and safety. But, because there is no exact standard for tunnel state and safety, depending on subjective decision, the new standard to assess the tunnel state is required. The existing standard including mainly the assessment of the state of tunnel lining is not considered the characteristics of tunnel as underground structures. Also, the item of assessment and process of grading and classifying the state of tunnel is not objective and systemetic. In this study, new standard for assessment of tunnel state is presented for improving the problems in evaluating the tunnel state and safety. In the new standard, the new items of assessment including geotechnical condition were selected and graded, the process in classifying the tunnel state is quantitative for objective assessment for tunnel state. This new standard and method is practically used in effective safety inspection and diagnosis and tunnel maintenance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.28-35
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• 2005

It is now well recognized that the ultimate limit state approach is a much better basis for design and strength assessment of ships and offshore structures since it is difficult to determine the realistic margin of safety using the traditional allowable working stress approach on the basis of linear elastic method solutions together with buckling strengthchecks adjusted by a simple plasticity correction. This paper outlines ALPS theory for ultimate limit state assessment of ship structures. ALPS is a computer software which stands for nonlinear Analysis of Large Plated Structures. Application examples of ALPS program to ultimate limit state assessment of plates, stiffened panels and ship hull girders are presented. A benchmark study is made by a comparison with the ALPS solutions with other methods including class rule formulae, nonlinear finite element methods and experimental results. Future trends on ultimate limit state assessment of ship structures are addresse[1]

• Proceedings of the KGS Conference
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• 1999.05a
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• pp.56-59
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• 1999

• Computers and Concrete
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• v.18 no.1
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• pp.69-97
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• 2016

Performance-based remaining life assessment of reinforced concrete bridge girders, subject to chloride-induced corrosion of reinforcement, is addressed in this paper. Towards this, a methodology that takes into consideration the human judgmental aspects in expert decision making regarding condition state assessment is proposed. The condition of the bridge girder is specified by the assignment of a condition state from a set of predefined condition states, considering both serviceability- and ultimate- limit states, and, the performance of the bridge girder is described using performability measure. A non-homogeneous Markov chain is used for modelling the stochastic evolution of condition state of the bridge girder with time. The thinking process of the expert in condition state assessment is modelled within a probabilistic framework using Brunswikian theory and probabilistic mental models. The remaining life is determined as the time over which the performance of the girder is above the required performance level. The usefulness of the methodology is illustrated through the remaining life assessment of a reinforced concrete T-beam bridge girder.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.229-235
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• 2022

This study aims to substantiate an interdisciplinary methodology for automated analysis and qualitative assessment of legislation and court decisions. The development of this kind of methodology will make it possible to fill a number of methodological gaps in various research areas, including law effectiveness assessment and legal monitoring. We have defined a methodology based on the interdisciplinary principles and tools. In general, it should be noted that even at the level of qualitative assessment made with the use of the methodology described above, the accumulation of knowledge about the relationship between legal objectives, indicators and computer methods of their identification can reduce the role of expert knowledge and subjective factor in the process of assessment, planning, forecasting and control over the state of legislation and law enforcement. Automation of intellectual processes becomes inevitable in a digital society, but, releasing experts from routine work, simultaneously reorients it to development of interdisciplinary methods and control over their application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• Smart Structures and Systems
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• v.24 no.3
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• pp.319-332
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• 2019

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Structural Engineering and Mechanics
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• v.64 no.2
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• pp.213-223
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• 2017

Bridges are lifeline and integral components of transportation system that are susceptible to seismic actions, their vulnerability assessment is essential for seismic risk assessment and mitigation. The vulnerability assessment of bridges common in Pakistan is very important as it is seismically very active region and the available code for the seismic design of bridges is obsolete. This research presents seismic vulnerability assessment of three real case simply supported multi-span reinforced concrete bridges commonly found in northern Pakistan, having one, two and three bents with circular piers. The vulnerability assessment is carried through the non-linear dynamic time history analyses for the derivation of fragility curves. Finite element based numerical models of the bridges were developed in MIDAS CIVIL (2015) and analyzed through with non-linear dynamic and incremental dynamic analyses, using a suite of bridge-specific natural spectrum compatible ground motion records. Seismic responses of shear key, bearing pad, expansion joint and pier components of each bridges were recorded during analysis and retrieved for performance based analysis. Fragility curves were developed for the bearing pads, shear key, expansion joint and pier of the bridges that first reach ultimate limit state. Dynamic analysis and the derived fragility curves show that ultimate limit state of bearing pads, shear keys and expansion joints of the bridges exceed first, followed by the piers ultimate limit state for all the three bridges. Mean collapse capacities computed for all the components indicated that bearing pads, expansion joints, and shear keys exceed the ultimate limit state at lowest seismic intensities.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.104-112
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• 2008

This paper presents the computer program for station reliability assessment. The developed program is based on Monte-Carlo simulation using system state transition sampling, which has the merit of rapid assessment compared to state duration sampling. One of the contributions of this paper is introduction of exclusiveness among events, which makes non-exponential probabilistic distribution be utilized in modeling repair time. The developed program is applied to well-blown sample system, and its assessment results are listed in this paper to show the reliability of the program.