• Bulletin of the Korean Chemical Society
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• v.17 no.8
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• pp.735-744
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• 1996

We present results of molecular dynamic (MD) simulations for the thermodynamic and structural properties of liquid n-alkanes, from n-butane to n-heptadecane, using three different models Ⅰ-Ⅲ. Two of the three classes of models are collapsed atomic models while the third class is an atomistically detailed model. Model Ⅰ is the original Ryckaert and Bellemans' collapsed atomic model [Discuss. Faraday Soc. 1978, 66, 95] and model Ⅱ is the expanded collapsed model which includes C-C bond stretching and C-C-C bond angle bending potentials in addition to Lennard-Jones and torsional potentials of model Ⅰ. In model Ⅲ all the carbon and hydrogen atoms in the monomeric units are represented explicitly for the alkane molecules. Excellent agreement of the results of our MD simulations of model Ⅰ for n-butane with those of Edberg et al.[J. Chem. Phys. 1986, 84, 6933], who used a different algorithm confirms the validity of our algorithms for MD simulations of model Ⅱ for 14 liquid n-alkanes and of models Ⅰ and Ⅲ for liquid n-butane, n-decane, and n-heptadecane. The thermodynamic and structural properties of models Ⅰ and Ⅱ are very similar to each other and the thermodynamic properties of model Ⅲ for the three n-alkanes are not much different from those of models Ⅰ and Ⅱ. However, the structural properties of model Ⅲ are very different from those of models Ⅰ and Ⅱ as observed by comparing the radial distribution functions, the average end-to-end distances and the root-mean-squared radii of gyrations.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.651-664
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• 2022

A precise prediction of the ultimate bond strength between rebar and surrounding concrete plays a major role in structural design, as it effects the load-carrying capacity and serviceability of a member significantly. In the present study, Gaussian models are employed for modelling bond strength of ribbed steel bars embedded in concrete. Gaussian models offer a non-parametric method based on Bayesian framework which is powerful, versatile, robust and accurate. Five different Gaussian models are explored in this paper-Gaussian Process (GP), Variational Heteroscedastic Gaussian Process (VHGP), Warped Gaussian Process (WGP), Sparse Spectrum Gaussian Process (SSGP), and Twin Gaussian Process (TGP). The effectiveness of the models is also evaluated in comparison to the numerous design formulae provided by the codes. The predictions from the Gaussian models are found to be closer to the experiments than those predicted using the design equations provided in various codes. The sensitivity of the models to various parameters, input feature space and sampling is also presented. It is found that GP, VHGP and SSGP are effective in prediction of the bond strength. For large data set, GP, VHGP, WGP and TGP can be computationally expensive. In such cases, SSGP can be utilized.

• Ocean and Polar Research
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• v.37 no.4
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• pp.357-368
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• 2015

This study analyzed structural changes and asymmetry of price volatility during the period before and after a point of structural change in price volatility, using the Korean fresh common squid daily retail price data from January 1, 2004 to September 30, 2015. This study utilized the following analytical methods: the unit-root test was applied to ensure the stability of the data, the Quandt-Andrews breakpoint test was applied to find the point of structural change, and the Glosten-Jagannathan-Runkle GARCH and EGARCH models were applied to investigate the asymmetry of price volatility. The empirical results of this study are as follows. First, ADF, PP, KPSS and Zivot-Andrews tests showed that the daily retail price change rate of the Korean fresh common squid differentiated by logarithm was stable. Secondly, the ARIMA (2,1,2) model was selected by information criteria such as AIC, SC, and HQ. Thirdly, the Quandt-Andrews breakpoint test found that a single structural change in price volatility occurred on June 11, 2009. Fourthly, the Glosten-Jagannathan-Runkle GARCH and EGARCH models showed that estimates of coefficients within the models were statistically significant before and after structural change and also that asymmetry as a leverage effect existed before and after structural change.

• Earthquakes and Structures
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• v.12 no.1
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• pp.67-77
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• 2017

In this paper, it is aimed to present a comparative study about the structural behavior of tall buildings consisting of different type of materials such as concrete, steel or timber using finite element analyses and experimental measurements on shaking table. For this purpose, two 1/60 scaled 28 and 30-stories wooden building models with $40{\times}40cm$ and $35{\times}35cm$ ground/floor area and 1.45 m-1.55 m total height are built in laboratory condition. Considering the frequency range, mode shapes, maximum displacements and relative story drifts for structural models as well as acceleration, displacement and weight limits for shaking table, to obtain the typical building response as soon as possible, balsa is selected as a material property, and additional masses are bonded to some floors. Finite element models of the building models are constituted in SAP2000 program. According to the main purposes of earthquake resistant design, three different earthquake records are used to simulate the weak, medium and strong ground motions. The displacement and acceleration time-histories are obtained for all earthquake records at the top of building models. To validate the numerical results, shaking table tests are performed. The selected earthquake records are applied to first mode (lateral) direction, and the responses are recorded by sensitive accelerometers. Comparisons between the numerical and experimental results show that shaking table tests are enough to identify the structural response of wooden buildings. Considering 20%, 10% and 5% damping rations, differences are obtained within the range 4.03-26.16%, 3.91-65.51% and 6.31-66.49% for acceleration, velocity and displacements in Model-1, respectively. Also, these differences are obtained as 0.49-31.15%, 6.03-6.66% and 16.97-66.41% for Model-2, respectively. It is thought that these differences are caused by anisotropic structural characteristic of the material due to changes in directions parallel and perpendicular to fibers, and should be minimized using the model updating procedure.

• Structural Engineering and Mechanics
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• v.64 no.5
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• pp.671-681
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• 2017

This study investigates the structural performance of 3D steel pipe rack suspended scaffolding systems. For the purpose, a standard full scale 3D steel pipe rack suspended scaffolding system considering two frames, two plane trusses, purlins and wooden floor is constructed in the laboratory. A developed load transmission system was placed in these experimental systems to distribute single loads to the center of a specific area in a step-by-step manner using a load jack. After each load increment, the displacements are measured by means of linear variable differential transducers placed in several critical points of the system. The tests are repeated for five different system conditions to determine the structural performance. The means of system conditions is the numbers of the tie bars which are used to connect plane trusses under level. Finite elements models of the 3D steel pipe rack suspended scaffolding systems considering different systems conditions are constituted using SAP2000 software to support the experimental tests and to use the models in future studies. Each of models including load transmission platform is analyzed under a single loading and the displacements are obtained. In addition, to calibrate the numerical models some uncertain parameters such as elasticity modulus of wooden floor and connection rigidity of purlins to plane trusses are assessed experimentally. The results of this work demonstrate that when increasing numbers of tie bars the displacement values are decreased. Also the results obtained from developed numerical models have harmony with those of experimental. In addition, the scaffolding system with two tie bars at the beginning and at the end of the plane truss has the optimum structural performance compared the results obtained for other scaffolding system conditions.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Structural Engineering and Mechanics
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• v.51 no.2
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• pp.249-265
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• 2014

The mechanical characteristics of materials are very essential in structural analysis for the accuracy of structural calculations. The estimation modulus of elasticity of concrete ($E_c$), one of the most important mechanical characteristics, is a very complex area in terms of analytical models. Many attempts have been made to model the modulus of elasticity through the use of experimental data. In this study, the neuro-fuzzy (NF) technique was investigated in estimating modulus of elasticity of concrete and a new simple NF model by implementing a different NF system approach was proposed. A large experimental database was used during the development stage. Then, NF model results were compared with various experimental data and results from several models available in related research literature. Several statistic measuring parameters were used to evaluate the performance of the NF model comparing to other models. Consequently, it has been observed that NF technique can be successfully used in estimating modulus of elasticity of concrete. It was also discovered that NF model results correlated strongly with experimental data and indicated more reliable outcomes in comparison to the other models.

• Earthquakes and Structures
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• v.4 no.3
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• pp.325-339
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• 2013

A number of structural and modal parameters are derived from the strong motion records of an instrumented G + 9 storeyed RC building during Bhuj earthquake, 26 Jan. 2001 in India. Some of the extracted parameters are peak floor accelerations, storey drift and modal characteristics. Modal parameters of the building are also compared with the values obtained from ambient vibration survey of the instrumented building after the occurrence of earthquake. These parameters are further used for calibrating the accuracy of fixed-base Finite Element (FE) models considering structural and non-structural elements. Some conclusions are drawn based on theoretical and experimental results obtained from strong motion records and time history analysis of FE models. An important outcome of the study is that strong motion peak acceleration profile in two horizontal directions is close to FE model in which masonry infill walls are modeled.

• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.181-193
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• 2017

An identification method for determination of the parameters of the rheological models of dampers made of viscoelastic material is presented. The models have two, three or four parameters and the model equations of motion contain derivatives of the fractional order. The results of dynamical experiments are approximated using the trigonometric function in the first part of the procedure while the model parameters are determined as the solution to an appropriately defined optimization problem. The particle swarm optimization method is used to solve the optimization problem. The validity and effectiveness of the suggested identification method have been tested using artificial data and a set of real experimental data describing the dynamic behavior of damper and a fluid frequently used in dampers. The influence of a range of excitation frequencies used in experiments on results of identification is also discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.569-576
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• 2003

Fundamental issues in static finite element analysis of reinforced concrete panel subjected to biaxial tensile loads are discussed. This paper is trying to bring our attention to the appropriate use of concrete material models such as cracking criteria, tension stiffening model and the steel models which are basically used in the nonlinear finite element analysis of reinforced concrete panels. We mainly investigate the sensitivity of available material models and finite element technologies to the finite element analysis result using our recent reinforced concrete panel experiment result. Throughout this study, we found that the judicious use of the material models and finite element technologies with the sound understanding of structural characteristics can only guarantee the accurate prediction of panel behaviour.