Development of Statistical Model, Mixture Design, Fresh and Hardened Properties of Furnace Slag - Lightweight Self Consolidating Concrete (FS-LWSCC)

A response surface method was carried out to model the influence of key mixtureparameters on properties affecting the performance of Expended Furnace Slag - LightweightSelf Consolidating Concrete (FS-LWSCC). Three key parameters that have significantinfluence on mixture characteristics of LWSCC were selected to derive mathematical modelfor evaluating the concrete fresh and hardened properties. Experimental levels of the variables(maximum and minimum) water/binder ratio (0.30 to 0.40), HRWRA (SP) (0.3 to1.2% bytotal content of binder), and total binder content (410 to 550kg/m3) were used for the designof Furnace Slag-LWSCC mixtures. A total of 18 mixtures were designed and produced. Theresponses of the derived statistical model were slump flow, V-funnel flow time, J-Ring flow,J-Ring height difference, L- box, filling capacity, bleeding, air content, initial and final settingtime, sieve segregation test, fresh unit weight, 28 days air dry unit weight, 28 days oven dryunit weight, and 7 and 28 days compressive strengths. It was seen that the proposed mixdesign model is a useful tool to understand the interactions between mixture parametersaffecting important characteristics of Expanded Furnace Slag - LWSCC. This understandingmight be simplified the mix design process and the required testing, as the model identifiesthe relative significance of each parameter, therefore providing important informationrequired to optimize the mix design. Consequently, minimize the effort needed to optimizeLWSCC mixtures ensuring balance between parameters affecting fresh and hardenedproperties

Size And High Temperature Effects On The Compressive Strength Of Self Compacting Concretes

The compressive strength behavior of concrete is one of the fundamental parameters of structural design as most load-bearing concrete elements, such as beams, columns and slabs. However, it was known that compressive behavior of the concrete elements alter depend on the element size and exposed temperature conditions. When the slenderness (height/diameter) of the concrete elements increased, compressive strength decreased relatively and this behavior known as size effect. In this study, compressive strength variation of the self compacting concrete specimens investigated taking in to account the different slenderness ratio and exposure temperatures. For this purpose, a self compacting mixture was prepared with water to cement ratio of 0.40 and 450 kg/m3 cement dosage. Cylindrical specimens with the diameter of 100 mm and slenderness of 2.0, 1.5, 1.0, and 0.5 were prepared and exposed to the different high temperatures (400, 600 and 800 oC) for an hour. For a control purpose, same size specimens were also tested under the laboratory conditions. The results show that high temperature exposure has severe strength loss effect on the concrete specimens irrespective of the slenderness ratio. Increasing the exposure temperature increased the strength loss of the specimens drastically. Moreover, it was seen that relative strength change (decrease) is evident when specimens' size increased

Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches

The optimization of composite materials such as concrete deals with the problem of selecting the values of several variables which determine composition, compressive stress, workability and cost etc. This study presents multi-objective optimization (MOO) of high-strength concretes (HSCs). One of the main problems in the optimization of HSCs is to obtain mathematical equations that represents concrete characteristic in terms of its constitutions. In order to solve this problem, a two step approach is used in this study. In the first step, the prediction of HSCs parameters is performed by using regression analysis, neural networks and Gen Expression Programming (GEP). The output of the first step is the equations that can be used to predict HSCs properties (i.e. compressive stress, cost and workability). In order to derive these equations the data set which contains many different mix proportions of HSCs is gathered from the literature. In the second step, a MOO model is developed by making use of the equations developed in the first step. The resulting MOO model is solved by using a Genetic Algorithm (GA). GA employs weighted and hierarchical method in order to handle multiple objectives. The performances of the prediction and optimization methods are also compared in the paper. (C) 2008 Elsevier Ltd. All rights reserved

Cost optimization of high strength concretes by soft computing techniques

In this study 72 different high strength concrete (HSC) mixes were produced according to the Taguchi design of experiment method. The specimens were divided into four groups based on the range of their compressive strengths 40-60, 60-80, 80-100 and 100-125 MPa. Each group included 18 different concrete mixes. The slump and air-content values of each mix were measured at the production time. The compressive strength, splitting tensile strength and water absorption properties were obtained at 28 days. Using this data the Genetic Programming technique was used to construct models to predict mechanical properties of HSC based on its constituients. These models, together with the cost data, were then used with a Genetic Algorithm to obtain an HSC mix that has minimum cost and at the same time meets all the strength and workability requirements. The paper describes details of the experimental results, model development, and optimization results

Investigating mix proportions of high strength self compacting concrete by using Taguchi method

In this study, mix proportion parameters of high strength self compacting concrete (HSSCC) are analyzed by using the Taguchi's experiment design methodology for optimal design. For that purpose, mixtures are designed in a L-18 orthogonal array with six factors, namely, "water/cementitious material (W/C) ratio", "water content (W)". "fine aggregate to total aggregate (s/a) percent", "fly ash content (FA)", "air entraining agent (AE) content", and "superplasticizer content (SP)". The mixtures are extensively tested, both in fresh and hardened states and to meet all of the practical and technical requirements of HSSCC. The experimental results are analyzed by using the Taguchi experimental design methodology. The best possible levels for mix proportions are determined for maximization of ultrasonic pulse velocity (UPV), compressive strength, splitting tensile strength and for the minimization of air content, water permeability, and water absorption values. (C) 2008 Elsevier Ltd. All rights reserved

Management of a patient with active rheumatoid arthritis and suspected tuberculosis causing effusive-constrictive pericarditis

In the following case report we present a patient who has been admitted for pericardial effusion causing cardiac compression with active rheumatoid arthritis and suspected tuberculosis. The patient was successfully treated with intravenous pulse steroid for active rheumatoid arthritis, with prophylactic anti-tuberculosis agents for suspected tuberculosis and with surgical pericardiectomy for the thickened pericardium as well as recurrent pericardial effusion. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved

Left ventricular pacemaker lead insertion through the foramen ovale - A case report

This report describes a patient with a 6-year-old pacemaker lead in the left ventricle, Both transthoracic and transesophageal echocardiography unequivocally showed that the lead enters the left ventricle via the foramen ovale and the mitral valve. The patient did not suffer from a thromboembolic event; therefore, we did not proceed with extraction. The importance of this case report is to emphasize the conditions and precautions of proper pacemaker implantation