A Nonlinear Finite Element Model for Steel-concrete Composite Beam using a Higher-order Beam Theory

Steel-concrete composite beams are commonly used in bridges, buildings and other civil engineering infrastructure for their superior structural performances. This is achieved by exploiting the typical configuration of this structural system where the concrete slab is primarily utilised to resist compressive stresses whereas the steel girder is used to sustain tensile stresses. The composite action is realised by connecting the concrete slab with the steel girder by steel shear studs. The interfacial shear slip is always observed due to the deformation of shear studs having a finite stiffness in reality which is commonly known as partial shear interaction. This is an important feature which should be considered in the analysis of these composite beams to get satisfactory results. It is observed that most of the existing models for simulating composite beams are based on Euler-Bernoulli’s beam theory (EBT) which does not consider the effect of shear deformation of the beam layers. In recent past, the incorporation of this effect is becoming popular and some attempts have already been made where Timoshenko’s beam theory (TBT) is typically used. In this beam theory (TBT), the true parabolic variation of shear stress over the beam depth is replaced by a uniform shear stress distribution over the beam depth to simplify the problem. In order to address this issue, a higher-order beam theory (HBT) has recently been developed at the University of Adelaide. However, the model is so far applied to the linear analysis of these beams. In the present study, a comprehensive nonlinear finite element model is developed based on HBT for an accurate prediction of the bending response of steel-concrete composite beams with partial shear interaction. This is achieved by taking a third order variation of longitudinal displacement over the beam depth for the steel and the concrete layers separately. The deformable shear studs used for connecting the concrete slab with the steel girder are modelled as distributed shear springs along the interface between these material layers. The effects of nonlinearities produced by large deformations and inelastic material behaviours are incorporated in the formulation of the proposed one-dimensional finite element model. The Green-Lagrange strain vector is used to capture the effect of geometric nonlinearity due to large deformations. The von Mises yield criterion with an isotropic-hardening rule is used for modelling the inelastic behaviour of steel girders, reinforcements and steel shear studs. This modelling approach is also applied to the region of concrete slab subjected to compressive stress for simplicity. A damage mechanics model is adopted to simulate the cracking behaviour of the concrete under tensile stress. The nonlinear governing equations are solved by an incremental-iterative technique following the Newton-Raphson method. A robust arc-length method is employed to capture the post peak response successfully where the energy dissipation played an important role. To assess the performance of the proposed model, the results predicted by the model are compared with existing experimental results as well as numerical results produced by using a detailed two dimensional finite element modelling of the composite beams.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental & Mining Engineering, 201

Characterization of rice husk carbon produced through simple technology

Textile wastewater contains different colors which are harmful to the environment. Activated carbon can be used for the decolorization of textile wastewater. Most of the textile plants in Bangladesh do not use the activated carbon due to its expensive cost and still it is classified as imported item. Low-cost activated carbon produced from locally available materials can solve this problem. This paper describes the color removal of textile wastewater by adsorption process using activated carbon derived from rice husk in a low-cost method. Thermal activation system was applied for the preparation of carbon. The maximum adsorption of color was found at an optimum temperature of 400C with the retention time of 60 minutes. Thus this study demonstrated encouraging performance of activated carbon produced from rice husk compared to the industrial grade activated carbon for decolorization of textile wastewater in the analysis

Nonlinear response prediction of spar platform using artificial neural network / Md. Alhaz Uddin

Due to global energy demand, offshore industries are moving towards deep and ultra-deep waters for oil and gas exploration in ocean environment. Floating offshore structures such as spar platform is considered to be the most economic and suitable offshore structure in deep water regions. During oil and gas exploration, floating offshore structures may sometimes be affected by critical environmental forces. Quick decision must be taken either to continue or to stop production, on the basis of response prediction of offshore structures under forecasted environmental conditions. Finite Element Method (FEM) is an important technique to predict the response of offshore structures considering all nonlinearities. However, FEM is a highly time-consuming process for predicting the response of platforms and usually used as a final analysis tool. On the other hand, Artificial Neural Networks (ANN) can predict response in rapid mode. ANNs are also capable of providing efficient solutions to problems such as damage detection, time series prediction and control where formal analysis is highly complex. This study presents nonlinear response prediction of spar platform for various environmental forces using ANN. The neural network has three layers, namely the input, output, and hidden layer. A hyperbolic tangent function is considered in the present study as an activation function. Environmental forces and structural parameters are used as inputs and FEM-based time history of spar platform responses are used as targets. Feed-forward neural networks with back-propagation algorithm are used to train the network. After training the network, the response of the spar platform is obtained promptly for newly selected environmental forces. The response obtained using ANN is validated by conventional FEM analysis. It has been observed that using completely new environmental forces as input to ANN, the time history response of spar platform can be very accurately predicted. Results show that the ANN approach is very efficient and significantly reduces the time for predicting response time histories

Prediction of Offshore Wave at East Coast of Malaysia—A Comparative Study

Exploration of oil and gas in the offshore regions is increasing due to global energy demand. The weather in offshore areas is truly unpredictable due to the sparsity and unreliability of metocean data. Offshore structures may be affected by critical marine environments (severe storms, cyclones, etc.) during oil and gas exploration. In the interest of public safety, fast decisions must be made about whether to proceed or cancel oil and gas exploration, based on offshore wave estimates and anticipated wind speed provided by the Meteorological Department. In this paper, using the metocean data, the offshore wave height and period are predicted from the wind speed by three state-of-the-art machine learning algorithms (Artificial Neural Network, Support Vector Machine, and Random Forest). Such data has been acquired from satellite altimetry and calibrated and corrected by Fugro OCEANOR. The performance of the considered algorithms is compared by various metrics such as mean squared error, root mean squared error, mean absolute error, and coefficient of determination. The experimental results show that the Random Forest algorithm performs best for the prediction of wave period and the Artificial Neural Network algorithm performs best for the prediction of wave height

Application of artificial neural network in fixed offshore structures

394-403<span style="font-size:9.0pt;font-family: " times="" new="" roman";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" hi"="" lang="EN-GB">Artificial Neural networks (ANNs) are good for prediction, damage detection, online monitoring and controlling in fixed jacket platform in such cases where formal analysis is tough or impossible. This paper presents state-of-the-art information reported so far on the research studies of ANN applications and future opportunity for fixed jacket offshore platforms. It is found that ANNs provide fairly accurate results as compared to conventional method. Based on the review, the future scope of work is outlined.</span

Relationship between weather variables and new daily covid-19 cases in Dhaka, Bangladesh

The present study investigated the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman rank correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature, and wind speed with the COVID-19 outbreak in Dhaka, Bangladesh. The study found that, among the seven indicators, only two indicators (minimum temperature and average temperature) had a significant relationship with new COVID-19 cases. The study also found that air quality index (AQI) had a strong negative correlation with cumulative cases of COVID-19 in Dhaka city. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 spread in Dhaka and other countries around the world.</p

Competent building elevation for incorporating base isolation in aseismic structure

The predominant lateral loads acting upon building structures are earthquake and wind induced forces. If wind load is much greater than earthquake load, the lateral force resisting system required to tackle wind loading may be enough to resist the smaller earthquake load. In this situation, a seismic base isolator will not bring any benefit to the building system. Furthermore, if time period of a building without isolator is greater, incorporation of isolator will not bring much difference to the building behavior with respect to seismic load. Additionally, for buildings with lower structural time periods, incorporation of an isolator will greatly alter the seismic behavior. In light of all of these facts, this study examines the buildings in Dhaka, intended for different heights and plan area, to establish critical height up to which earthquake is the dominant lateral load. It also examines the relationship that exists between building height and time period. The study shows that though seismic base shear governs up to larger building height, in case of greater heights, time periods are much larger than the most suitable value of limiting time period for incorporating an isolator. Realistic structural time period and governing seismic load envisage that a seismic base isolator can be efficiently incorporated for up to 30 similar to 40m structural height at low to medium soil conditions for aseismic RCC building structures. (c) 2012 Elsevier B.V...Selection and peer-review under responsibility of Bin Nusantara Universit

Data-driven strategy for evaluating the response of eco-friendly concrete at elevated temperatures for fire resistance construction

Concrete strength degrades drastically due to high temperatures (HT) destroying its components. Using supplementary cementitious materials (SCMs) in concrete and achieving the necessary compressive strength (CS) at HT is challenging and time-consuming. However, supervised machine learning (ML) approaches may be used to anticipate the expected outcome accurately, saving researchers time, effort, and money on tests. This research makes use of a decision tree (DT), Adaboost (ADB), and bagging regressor (BR) approach, to predict the CS of concrete at HT. Based on the findings of the coefficient of determination (R2), the BR model obtained the greatest value of R2 (0.92), followed by the ADB model (0.90) and the DT model (0.87). In addition, statistical analysis and k-fold cross-validation were carried out as part of the validation process for the models. According to these findings, the BR model had much lower MAE, RMSE, and RMSLE values than the ADB and DT models. Additionally, the Taylor diagram demonstrated that the values generated by the BR model were far closer to actual values than those generated by other models. This indicated that the BR model fared better than the ADB and DT models. In addition, sensitivity analysis revealed that temperature accounted for 66.3 % of the outcome, cement contributed 7.6 %, and coarse aggregates 8.4 %. Thus, ML models have been shown to be cost-effective and efficient in predicting SCM concrete CS at HTs

Localized waves and their novel interaction solutions for a dimensionally reduced (2 + 1)-dimensional Kudryashov Sinelshchikov equation

Propagation of the pressure waves in a liquid with gas bubbles is an important topic in the field of fluid dynamics and mathematical physics. The Kudryashov-Sinelshchikov equation is one of the models that describe the propagation of nonlinear waves in a bubbly liquid taking into consideration the viscosity of the liquid and the heat transfer. To explain such behaviors, we mainly focus in this study to explain the dynamics of localized waves and their variety of interaction solutions to a dimensionally reduced (2 + 1)-dimensional Kudryashov-Sinelshchikov equation with the aid of the Hirota bilinear method from N-soliton solutions. Four different forms of localized waves, including solitons, lumps, breathers, and rogues, are derived from the aforesaid equation based on the long wave limit approach. In particular, the localized waves can be used to find interaction solutions, which are the single breather or single lump formed by two solitons; interaction between one line soliton and one breather, as well as one line soliton and one lump soliton among the three solitons; interaction of the two-line soliton and one periodic breather, two periodic breathers, periodic breather and one lump soliton from the four solitons. The direction of propagation, phase shifts, shape, energy, and the variety of interaction solutions of localized waves are affected by these parameters. Moreover, analytical and graphical illustrations of these interaction solutions and their propagation properties are shown by the three-dimensional and density plots with the help of Maple 17. These newly discovered solutions in this study can be used to illustrate the interaction phenomenon of localized waves on ocean surfaces