DURABILITY OF NATURAL POZZOLAN-BASED MORTAR EXPOSED TO SULFATE ATTACK

Cement is a strategic commodity in the civil engineering for the construction of reinforced concrete structures. But its production generates around 5% of toxic gases such as CO2 responsible for environmental degradation. Furthermore, cement industry is a consumer sector of non-renewable energy. The use in the cement of natural additions is a solution to reduce the CO2 gas and the cost of production. The purpose of this work is the study of a sustainable building material: natural pozzolan Beni-saf (PNB) incorporated to mortars exposed to sulfate attack (5% Na2SO4). The loss of mass, monitoring the pH reading of each attack solution as well as specimens dimensions are different tests to study the durability of mortars made with 10, 20 and 30% of natural pozzolan. The result derived from this research is that pozzolan improves mortars resistance to sodium sulfate environment.</p

Valorization of mud from Fergoug dam in manufacturing mortars

The production of calcined mud, with pozzolanic properties, from the large quantities of sediments dredged from Algerian dams, could be a good opportunity for the formulation of high performance mortars and pozzolanic concretes, with lower costs and less greenhouse gas (CO2) emissions. The optimal temperatures selected for calcination were 750, 850 and 950 °C. The burning operation was continuous over a period of 3 h. Therefore, a series of physical, chemical, mechanical and microstructural analyses were conducted on sediment samples, collected from the waters of Fergoug dam. The results obtained from the analyses of the calcined mud, from the dam, allowed saying that mortars with different percentages of that mud represent a potential source of high reactivity pozzolanic materials

Mortar Incorporating Supplementary Cementitious Materials: Strength, Isothermal Calorimetry and Acids Attack

WOS:000377429900004International audienceSupplementary cementitious materials (SCMs) prove to be effective to meet most of the requirements of durable concrete and leads to a significant reduction in CO2 emissions. This research studies the effect different SCMs (natural pozzolan (PN) /limestone fine (FC) at various replacement levels) on the physical and mechano-chemical resistance of blended mortar. The paper primarily deals with the characteristics of these materials, including heat of hydration, strength and effects of aggressive chemical environments (using sulphuric acid and nitric acid). Over 6 mixes were made and compared to the control mix. Tests were conducted at different ages up to 360 days. The experimental results in general showed that Algerian mineral admixtures (PN/FC) were less vulnerable to nitric and sulphuric acid attack and improved the properties of mortars, but at different rates depending on the quantity of binder

Computational methods of Gaussian Particle Swarm Optimization (GPSO) and Lagrange Multiplier on economic dispatch issues (case study on electrical system of Java-Bali IV area)

The objective in this paper is about economic dispatch problem of electric power generation where scheduling the committed generating units outputs so as to meet the required load demand at minimum operating cost, while satisfying all units and system equality and inequality constraint. In the operating of electric power system, an economic planning problem is one of variables that its must be considered since economically planning will give more efficiency in operational cost. In this paper the economic dispatch problem which has non linear cost function solved by using swarm intelligent method is Gaussian Particle Swarm Optimization (GPSO) and Lagrange Multiplier. GPSO is a population-based stochastic algorithms which their moving inspired by swarm intelligent and probabilities theories. To analize its accuracy, the economic dispatch solution by GPSO method will be compared with Lagrange multiplier method. From the running test result the GPSO method give economically planning calculation which it better than Lagrange multiplier method and the GPSO method faster to getting error convergence. Therefore the GPSO method have better performance to getting global best solution than the Lagrange method