• International conference on construction engineering and project management
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• 2022.06a
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• pp.686-693
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• 2022

Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

• Computers and Concrete
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• v.33 no.6
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• pp.643-658
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• 2024

To date, shell-solid and fibre element model analysis are the most commonly used methods to investigate the seismic performance of concrete-filled steel tube (CFST) bridge piers. However, most existing research does not consider the loss of bearing capacity caused by the fracture of the outer steel tube. To fill this knowledge gap, a refined finite element (FE) model considering the ductile damage of steel tubes and the behaviour of infilled concrete with cracks is established and verified against experimental results of unidirectional, bidirectional cyclic loading tests and pseudo-dynamic loading tests. In addition, a parametric study is conducted to investigate the seismic performance of CFST bridge piers with different concrete strength, steel strength, axial compression ratio, slenderness ratio and infilled concrete height using the proposed model. The validation shows that the proposed refined FE model can effectively simulate the residual displacement of CFST bridge piers subjected to highintensity earthquakes. The parametric analysis indicates that CFST piers hold sufficient strength reserves and sound deformation capacity and, thus, possess excellent application prospects for bridge construction in high-intensity areas.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.19-19
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• 2009

Dynamic Stall is a flow phenomenon which occurs on the retreating side of helicopter rotor blades during forward flight. It also occurs on blades of stall regulated wind turbines under yawing conditions as well as during gust loads. Time scales occurring during this process are comparable on both helicopter and wind turbine blades. Dynamic Stall limits the speed of the helicopter and its manoeuvrability and limits the amount of power production of wind turbines. Extensive numerical as well as experimental investigations have been carried out recently to get detailed insight into the very complex flow structures of the Dynamic Stall process. Numerical codes have to be based on the full equations, i.e. the Navier-Stokes equations to cover the scope of the problems involved: Time dependent flow, unsteady flow separation, vortex development and shedding, compressibility effects, turbulence, transition and 3D-effects, etc. have to be taken into account. In addition to the numerical treatment of the Dynamic Stall problem suitable wind tunnel experiments are inevitable. Comparisons of experimental data with calculated results show us the state of the art and validity of the CFD-codes and the necessity to further improve calculation procedures. In the present paper the phenomenon of Dynamic Stall will be discussed first. This discussion is followed by comparisons of some recently obtained experimental and numerical results for an oscillating helicopter airfoil under Dynamic Stall conditions. From the knowledge base of the Dynamic Stall Problems, the next step can be envisaged: to control Dynamic Stall. The present discussion will address two different Dynamic Stall control methodologies: the Nose-Droop concept and the application of Leading Edge Vortex Generators (LEVoG's) as examples of active and passive control devices. It will be shown that experimental results are available but CFD-data are only of limited comparison. A lot of future work has to be done in CFD-code development to fill this gap. Here mainly 3D-effects as well as improvements of both turbulence and transition modelling are of major concern.

• Proceedings of the KSRS Conference
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• v.1
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• pp.368-371
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• 2006

A coastline is the boundary between land and ocean masses. Knowledge of coastline is essential for autonomous navigation, geographical exploration, coastal erosion monitoring and modelling, water line change, etc. Many methods have been researched to extract coastlines from the synthetic aperture radar (SAR) and optic images. Most methods were based on the intensity contrast between land and sea regions. However, in these methods, a coastline detection task was very difficult because of insufficient intensity contrast and the ambiguity in distinguishing coastline from other object line. In this paper, we propose an efficient method for the delineation of coastline using interferometric coherence values estimated from ERS tandem pair. The proposed method uses the facts that a tandem pair of ERS is acquired from a time interval of an accurate day and that the coherent and incoherent values in coherence map are land and water, respectively. The coherence map was generated from ERS tandem pair, filtered by MAP filter, and divided into land and water by the determination of threshold value that is based on the bimodality of the histogram. Finally, a coastline was detected by delineating the boundary pixels. There was a good visual match between the detected coastline and the manually contoured line. The interferometric coherence map will be helpful to identify land and water regions easily, and can be used to many applications that are related with a coastline.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1476-1479
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• 1996

The ring rolling process is one of the best known ring production method. The present model based control system was designed for rings with rectangle cross-section yet. An Adaptive Fuzzy Control for Closed-Die Ring-Rolling was developed in order to enhance the flexibility of the radial-axial ring rolling machine and to produce the rings with highly complex cross-section profile, roller bearing rings. A fuzzy method was implemented because of its simple application and to utilize the known process knowledge. The quality of the control system was estimated by die filling grad, which is strong dependent on the rising time of the controller. The rolling process parameters were also varied to determine their influence on filling of the ring profile. Die filling met the requirement of the industry.

• Journal of Construction Engineering and Project Management
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• v.6 no.2
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• pp.1-7
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• 2016

Construction in the UK is the second most dangerous industry in terms of fatal and minor injuries according to the 2014 report of HSE. The use of mobile devices such as iPad, Tablets and Smart phones on the live construction projects is also on the increase in the UK due to the 2016 - Level 2 BIM (Building Information Modelling) implementation target, set by the UK Government. Hence, the use of such devices may become a distraction from work activities on the construction sites and will cause a major risk to the end users. The subject of improving safety of BIM use is widely researched, but there is a gap in knowledge about the actual use of the mobile devices and perception of 'Site BIM', on the construction site activities. The main gap identified in the 'Site BIM' is the health and safety aspect of using such devices on the construction sites. A safer way of working with such devices needs to be identified to avoid any potential site hazards and fatalities before the widespread use of the devices are found on the construction projects. In that context, the paper is aimed to highlight the safety issues that are required to address for the successful implementation of the mobile devices for safer use of the 'Site BIM'. Questionnaire survey was used to collect the site information among construction professionals in the UK. The survey findings suggested that a proactive approach may be helpful to stop potential hazards and risks causing by the use of mobile devices and potential measures need to be identified before any injuries and incidents occur. The paper concludes that training, changing size of mobile devices and ensuring a separate induction training for 'Site BIM' tools will improve the health and safety of the end users of the mobile devices at the live construction sites.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.129-137
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• 2014

This study proposed an IT convergence curriculum for educating the Non-Commissioned Officers. This program was produced by the comprehensive reference to the curriculums of military academies and systematic and rational modelling. The key features of the proposed curriculum are to consolidate the following three areas to meet the needs of the NCO, a recipient of the education. First, IT related subjects were posed as a mainstay of the curriculum that is critical for the scientific and information advancement of the forces. Second, the military leadership courses were included in the effective management of the soldiers. Third, military counseling certificate courses were included, a ground breaking trial nationally. In addition to this, we presented a characterized courses that focus on hands-on skills and knowledge for performing the duties of the NCO.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.258-265
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• 2017

At the early stage of the development of high speed propulsion systems, the designers suffer from the lack of both the quantity and the quality of test data. In that situation, the associated uncertainties could not be modeled as probabilistic distribution since probabilistic modelling requires large amount of data. In this paper, instead, the information provided by experts based on their experience and engineering knowledge was used to model uncertainty using the evidence theory. In designing the DCR(Dual Combustion Ramjet) engine, the combustion efficiencies, not well understood and little data existing, are assumed to have been provided by experts. And the uncertainties are quantified by Evidence theory. The quantified uncertainties are incorporated into the optimization. The design variables, area of inlet and area of combustor exit, have been found while satisfying reliability margins of thrust and thermal choking. The results show a reasonable design of the engine under the uncertain circumstances.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.