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Previous studies have shown that RC flat slab buildings are highly vulnerable to progressive collapse because no beams could help redistribute the loads previously carried by the lost columns. The necessary strengthening methods should, therefore, be adapted to reduce the occurrence of progressive collapse. In this paper, the progressive collapse behaviour of five-storey R.C flat slab building is assessed by removing columns from the first-storey and dynamic analysis is conducted in compliance with GSA guidelines (2016). The results are analyzed in terms of vertical displacement and chord rotation at the location of removed columns and compared with the allowable limits as specified in DoD guidelines (2009). Different sized perimeter beams are used as strengthening methods to increase the progressive collapse resistance of the studied flat slab building. Since building strengthening uses structural elements that consume natural resources, sustainability criteria should be explicitly included in the strengthening requirements. These performance enhancement methods are then evaluated from structural, cost and environmental aspects and the results are examined. A strengthening alternative is then proposed which not only satisfy the progressive collapse code requirements but also requires less cost and emits less CO 2 gas. [ABSTRACT FROM AUTHOR]

In recent years, construction industry has seen huge demand for non-renewable materials such as stones, fine aggregate, coarse aggregate, etc., resulting in exponential growth in mining operation. In parallel to this, the quarrying of dimensional stone generates vast amount of waste in both solid and powder forms. Sustainable disposal of these wastes has emerged as a big challenge around the globe. The present research focusses on minimizing the environmental pollution which is often due to unplanned disposal of slurry waste generated during the cutting process. To carry out this study, eleven mortar mixes were prepared with dimension limestone slurry waste as a replacement of fine aggregate. These mixes were tested for their workability, porosity, ultrasonic pulse velocity, dynamic modulus of elasticity, water absorption, compressive strength, flexural strength and adhesive strength. The behavior of internal structure of mortar matrix was evaluated on selected mixes by TGA, FTIR, SEM and MIP techniques. Tests results revealed that up to 40 percent replacement of fine aggregate with dimensional limestone slurry improved strength and sustained necessary rheological parameters of mortar mixes. Results of microstructure studies substantiate these improvements. [ABSTRACT FROM AUTHOR]

This paper describes the mechanical, thermo-mechanical, and thermal behavior of unfilled E-glass fiber (10-50 wt%) reinforced polymer (GFRP) composites and granite powder filled (8-24 wt%) GFRP composite in different weight percentages, respectively. The void fraction of unfilled glass epoxy composite is decreased from 7.71% to 3.17% with the increase in fiber loading from 10 to 50 wt%. However, void fraction for granite powder filled GFRP composites show reverse in trend. The granite powder addition in glass-epoxy composites show significant improvement in hardness (37-47 Hv), impact strength (31.56-37.2 kJ/m2), and stress intensity factor (by 14.29% for crack length of 5 mm) of the composites. The thermo-mechanical analyses also show strong correlation with the mechanical performance of the composites. The minimum difference of 0.17 GPa in storage and flexural moduli are observed for unfilled 20 wt% glass epoxy composite; whereas, maximum difference of 0.71 GPa is recorded for unfilled 50 wt% glass epoxy composite. Moreover, the numerical and experimentally measured thermal conductivity of unfilled and granite powder filled epoxy composites are within the lower and upper bound values. Hence, a successful attempt is presented for mechanical analysis of full scale model by finite element analysis. The results show that finite element analysis predicted reasonably actual stress value and tip deflection of wind turbine blade. POLYM. COMPOS., 38:1335-1352, 2017. © 2015 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

The granite processing industry, due to its sawing and polishing activities, is responsible for producing an enormous quantity of granite powder waste, herein referred to as granite industry by-product (GIB). GIB is a hazardous pollutant that poses a threat to ecosystems, thus emphasizing the urgent need to find a sustainable and technologically viable way of utilizing GIB and thereby minimizing its risks. The paper aims to assess the feasibility of GIB as a possible sand replacement in the manufacturing of concrete. At a 0.50 water-to-cement ratio (w/c), feasibility studies were performed and analyses were done for 10, 25, 40, 55, and 70% sand replacement by GIB in the manufacturing of concrete. Strength and durability of concrete with different percentages of GIB particles were ascertained by comparing the results of compressive strength, flexural strength, abrasion, shrinkage, permeability, carbonation, acid attack, chloride penetration, and corrosion tests with the results from a control concrete. Test results were ably explained by using auxiliary analyses such as scanning electron microscopy (SEM) and X-ray powder diffraction (XRD). The encouraging results proved the suitability of GIB concrete as a sustainable construction material. Optimal replacement level of river sand by GIB was found to be 25%. [ABSTRACT FROM AUTHOR]

In the present study, two sets of jute epoxy composites are fabricated by varying first fiber loading from 10 to 50 wt% at an interval of 10 wt% and then granite powder incorporated from 0 to 24 wt% in an interval of 8 wt% in the composites. The initial study is to prepare polymeric composites for wind turbine blade application and study the following physical to thermo-mechanical properties including fracture toughness of the composites. The void content of the unfilled composites show in decreasing order (from 6.37 to 3.07%) with the increasing in fiber loading which satisfied well with the increasing in tensile strength from 28.33 to 34.2 MPa and flexural strength from 44.2 to 97.8 MPa, respectively. As far as particulate filled composites the void content shows reverse in trend (from 2.99% to 9.68%) with the increasing in filler content and which justifies the mechanical properties i.e tensile strength decreases from 33.72 to 32.27 MPa and similarly in case of flexural strength also. Whereas, hardness shows a unique behavior both in fiber reinforced and particulate filled composites in an increasing order from 29 to 44 Hv, respectively. Fracture toughness is observed to be constant for all considered crack lengths however, its value significantly improved with both type of reinforcement. The dynamic mechanical analysis shows positive effect of both the reinforcement for mechanical performance under cyclic stresses. Finally, Cole-Cole plot is drawn from the dynamic mechanical analysis results to verify the homogeneity of the composites. POLYM. COMPOS., 38:736-748, 2017. © 2015 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

One of the most challenging problems of 21 st century is solid waste management and stone slurry is a prime shareholder in this waste. The paper aims at assessing the feasibility of utilizing the two different types of stone waste generated globally in huge quantities i.e., Granite cutting waste and marble slurry as a replacement for fine aggregate in concrete manufacturing. The paper reports the similarities and highlights the contrasting behaviour of GCW and MS concrete in terms of durability, compressive and flexure strength, abrasion, permeability and ultra-pulse velocity. The strength and durability of concrete is determined by a number of factors including the physical and chemical composition of constituent ingredients as well as the microstructure of ingredient particles. Explanations for the trends observed have been derived from microstructural studies using SEM and EDS test and also the inter-particle behaviour of the ingredients within concrete matrix . It was found that neglecting minor variations the optimum replacement percentage for GCW and MS concrete were 25% and 15% respectively. Abbreviation: GCW- Granite cutting waste; MS – Marble Slurry; w/c – water-cement ratio. [ABSTRACT FROM AUTHOR]

With rapid growth in the construction industry, Ready Mix Concrete (RMC) is playing a key role in offering high-quality customized concrete to contractors and builders. The workability of concrete involves early stage operations of concrete: placing, compaction, and finishing. Since RMC is manufactured at a plant and transported to the construction site, loss of workability is of prime concern due to the considerable time interval between mixing and placing of concrete. Workability of concrete is measured using a slump test to evaluate the life of the concrete during its transportation phase and the uniformity of the concrete from batch to batch. The proportions of cement, fly ash, coarse aggregates, fine aggregates, water, and admixtures in the concrete govern its workability or slump value. In this study, an Artificial Neural Networks (ANNs) learning from past examples gathered from a RMC plant were used to model the functional relationship between the input parameters and the slump value of concrete. The ANN model provided promising results compared to first-order and second-order regression techniques for modeling the unknown and complex relationships exhibited by the design mix proportions and the slump of concrete. The neural network synaptic weights that control the learning mechanism of ANN were further used to compute the percentage of relative importance of each constituent of RMC on the slump value, providing insight into the composite nature of concrete. The technique presented in the study will enable technical staff to quickly estimate the slump of RMC based on its design mix constituents without having to perform multiple design mix trials in order to achieve a customized slump value. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) have been the preferred choice for modeling the complex and nonlinear material behavior where conventional mathematical approaches do not yield the desired accuracy and predictability. Despite their popularity as a universal function approximator and wide range of applications, no specific rules for deciding the architecture of neural networks catering to a specific modeling task have been formulated. The research paper presents amethodology for automated design of neural network architecture, replacing the conventional trial and error technique of finding the optimal neural network. The genetic algorithms (GA) stochastic search has been harnessed for evolving the optimum number of hidden layer neurons, transfer function, learning rate, and momentum coefficient for back propagation ANN. The methodology has been applied for modeling slump of ready mix concrete based on its design mix constituents, namely, cement, fly ash, sand, coarse aggregates, admixture, and water-binder ratio. Six different statistical performance measures have been used for evaluating the performance of the trained neural networks. The study showed that, in comparison to conventional trial and error technique of deciding the neural network architecture and training parameters, the neural network architecture evolved through GA was of reduced complexity and provided better prediction performance. [ABSTRACT FROM AUTHOR]