• Advances in Computational Design
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• v.5 no.2
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• pp.111-125
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• 2020

The flow behavior of polymer melts within a slit die is an important consideration when designing a die geometry. The quality of the extruded polymer product can be determined through an evaluation of the flow homogeneity, wall shear rate and pressure drop across the central height of the die. However, mathematical formulations cannot fully determine the behavior of the flow due to the complex nature of fluid dynamics and the nonlinear physical properties of the polymer melts. This paper examines two slit die geometries in terms of outlet velocity uniformity, shear rate uniformity at the walls and pressure drop by using the licensed computational fluid dynamics package, Ansys POLYFLOW, based on the finite element method. The Carreau-Yasuda viscosity model was used for the rheological properties of the polypropylene. Comparative analysis of the simulation results will conclude that the modified die design performs better in all three aspects providing uniform exit velocity, uniform wall shear rates, and lower pressure drop.

• Advances in Computational Design
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• v.3 no.3
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• pp.289-302
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• 2018

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.

• Advances in Computational Design
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• v.7 no.3
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• pp.253-279
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• 2022

This study investigated and predicted the Marshall stability of glass-fiber asphalt mix, carbon-fiber asphalt mix and glass-carbon-fiber asphalt (hybrid) mix by using machine learning techniques such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest(RF), The data was obtained from the experiments and the research articles. Assessment of results indicated that performance of the Artificial Neural Network (ANN) based model outperformed applied models in training and testing datasets with values of indices as; coefficient of correlation (CC) 0.8492 and 0.8234, mean absolute error (MAE) 2.0999 and 2.5408, root mean squared error (RMSE) 2.8541 and 3.3165, relative absolute error (RAE) 48.16% and 54.05%, relative squared error (RRSE) 53.14% and 57.39%, Willmott's index (WI) 0.7490 and 0.7011, Scattering index (SI) 0.4134 and 0.3702 and BIAS 0.3020 and 0.4300 for both training and testing stages respectively. The Taylor diagram also confirms that the ANN-based model outperforms the other models. Results of sensitivity analysis show that Carbon fiber has a major influence in predicting the Marshall stability. However, the carbon fiber (CF) followed by glass-carbon fiber (50GF:50CF) and the optimal combination CF + (50GF:50CF) are found to be most sensitive in predicting the Marshall stability of fibrous asphalt concrete.

• Advances in Computational Design
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• v.8 no.2
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• pp.97-112
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• 2023

The Finite Element (FE) modeling of Reinforced Concrete (RC) under seismic loading has a sensitive impact in terms of getting good contribution compared to experimental results. Several idealized model types for simulating the nonlinear response have been developed based on the plasticity distribution alone the model. The Continuum Models are the most used category of modeling, to understand the seismic behavior of structural elements in terms of their components, cracking patterns, hysteretic response, and failure mechanisms. However, the material modeling, contact and nonlinear analysis strategy are highly complex due to the joint operation of concrete and steel. This paper presents a numerical simulation of a chosen RC column under monotonic and cyclic loading using the FE Abaqus, to assessthe hysteretic response and failure mechanisms in the RC columns, where the perfect bonding option is used for the contact between concrete and steel. While results of the numerical study under cyclic loading compared to experimental tests might be unsuccessful due to the lack of bond-slip modeling. The monotonic loading shows a good estimation of the envelope response and deformation components. In addition, this work further demonstrates the advantage and efficiency of the damage distributions since the obtained damage distributions fit the expected results.

• Advances in Computational Design
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• v.7 no.4
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• pp.345-369
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• 2022

Infectious disease emergency hospitals are usually temporarily built during the pneumonia epidemic with higher requirements regarding diagnosis and treatment efficiency, hygiene and safety, and infection control.This study aims to identify how the Building Information Modeling (BIM) + Industrialized Building System (IBS) approach could rapidly deliver an infectious disease hospital and develop site epidemic spreading algorithms. Coronavirus-19 pneumonia construction site spreading algorithm model mind map and block diagram of the construction site epidemic spreading algorithm model were developed. BIM+IBS approach could maximize the repetition of reinforced components and reduce the number of particular components. Huoshenshan Hospital adopted IBS and BIM in the construction, which reduced the workload of on-site operations and avoided later rectification. BIM+IBS integrated information on building materials, building planning, building participants, and construction machinery, and realized construction visualization control and parametric design. The delivery of Huoshenshan Hospital was during the most critical period of the Coronavirus-19 pneumonia epidemic. The development of a construction site epidemic spreading algorithm provided theoretical and numerical support for prevention. The agent-based analysis on hospital evacuation observed "arched" congestion formed at the evacuation exit, indicating behavioral blindness caused by fear in emergencies.

• Advances in Computational Design
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• v.3 no.4
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• pp.367-384
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• 2018

The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.

• Advances in Computational Design
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• v.5 no.4
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• pp.417-443
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• 2020

Tunnels have been an integral part of human civilization. Due to complexity in its design and structure, the stability of underground structures under extreme loading conditions has utmost importance. Increased terrorism and geo-political conflicts have forced the engineers and researchers to study the response of underground structures, especially tunnels under blast loading. The present study has been carried out to seek the response of tunnel structures under blast load using the finite element technique. The tunnel has been considered in quartzite rock of northern India. The Mohr-Coulomb constitutive model has been adopted for the elastoplastic behaviour of rock. The rock model surrounding the tunnel has dimensions of 30 m x 30 m x 35 m. Both unlined and lined (concrete) tunnel has been studied. Concrete Damage Plasticity model has been considered for the concrete lining. Four different parameters (i.e., tunnel diameter, liners thickness, overburden depth and mass of explosive) have been varied to observe the behaviour under different condition. To carry out blast analysis, Coupled-Eulerian-Lagrangian (CEL) modelling has been adopted for modelling of TNT (Trinitrotoluene) and enclosed air. JWL (Jones-Wilkins-Lee) model has been considered for TNT explosive modelling. The paper concludes that deformations in lined tunnels follow a logarithmic pattern while in unlined tunnels an exponential pattern has been observed. The stability of the tunnel has increased with an increase in overburden depth in both lined and unlined tunnels. Furthermore, the tunnel lining thickness also has a significant effect on the stability of the tunnel, but in smaller diameter tunnel, the increase in tunnel lining thickness has not much significance. The deformations in the rock tunnel have been decreased with an increase in the diameter of the tunnel.

• Advances in Computational Design
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• v.5 no.2
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• pp.195-207
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• 2020

The present study focuses on the application of artificial neural network (ANN) and Multiple linear Regression (MLR) analysis for developing a model to predict the unconfined compressive strength (UCS) and split tensile strength (STS) of the fiber reinforced clay stabilized with grass ash, fly ash and lime. Unconfined compressive strength and Split tensile strength are the nonlinear functions and becomes difficult for developing a predicting model. Artificial neural networks are the efficient tools for predicting models possessing non linearity and are used in the present study along with regression analysis for predicting both UCS and STS. The data required for the model was obtained by systematic experiments performed on only Kaolin clay, clay mixed with varying percentages of fly ash, grass ash, polypropylene fibers and lime as between 10-20%, 1-4%, 0-1.5% and 0-8% respectively. Further, the optimum values of the various stabilizing materials were determined from the experiments. The effect of stabilization is observed by performing compaction tests, split tensile tests and unconfined compression tests. ANN models are trained using the inputs and targets obtained from the experiments. Performance of ANN and Regression analysis is checked with statistical error of correlation coefficient (R) and both the methods predict the UCS and STS values quite well; but it is observed that ANN can predict both the values of UCS as well as STS simultaneously whereas MLR predicts the values separately. It is also observed that only STS values can be predicted efficiently by MLR.

• Advances in Computational Design
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• v.4 no.3
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• pp.273-294
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• 2019

In this paper is presented the minimum cost (optimal design) for reinforced concrete circular isolated footings based on an analytic model. This model considers a load and two moments in directions of the X and Y axes, and the pressure has a variation linear, these are the effects that act on the footing. The minimum cost (optimal design) and the Maple program are shown in Flowcharts. Two numerical experiments are shown to obtain the minimum cost design of the two materials that are used for a circular footing supporting an axial load and moments in two directions in accordance to the code of the ACI (American Concrete Institute), and it is compared against the current design (uniform pressure). Also, the same examples are developed through the normal procedure to verify the minimum cost (optimal design) presented in this document, i.e., the equations of moment, bending shear and punching shear are used to check the thickness, and after, the steel areas of the footing are obtained, and it is compared against the current design (uniform pressure). Results section show that the optimal design is more accurate and more economical than to any other model. Therefore, it is concluded that the optimized design model presented in this paper should be used to obtain the minimum cost design for the circular isolated footings.

• Advances in Computational Design
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• v.4 no.2
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• pp.119-139
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• 2019

Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. Better on-site management allows for substantial productivity improvements and cost savings. The procurement system should be able to manage a wider variety of materials and products of the required quality in order to have less stock, in less time, using less space, with less investment and avoiding multiple storage stations. The objective of this paper is to demonstrate the advantages of using the Chronographic modeling, by combining spatiotemporal technical scheduling with the 4D simulations, the Last Planner System and the Takt-time when modeling the construction of building projects. This paper work toward the aforementioned goal by examining the impact that material flow has on site occupancy. The proposed spatiotemporal model promotes efficient site use, defines optimal site-occupancy and workforce-rotation rates, minimizes intermediate stocks, and ensures a suitable procurement process. This paper study the material flow on the site and consider horizontal and vertical paths, traffic flows and appropriate means of transportation to ensure fluidity and safety. This paper contributes to the existing body of knowledge by linking execution and supply to the spatial and temporal aspects. The methodology compare the performance and procurement processes for the proposed Chronographic model with the Gantt-Precedence diagram. Two examples are presented to demonstrate the benefits of the proposed model and to validate the related concepts. This validation is designed to test the model's graphical ability to simulate construction and procurement.