Masonry construction is the most widely used building method in the world. Concrete masonry is relatively low in cost due to the vast availability of aggregates used within the production process. ese aggregate materials are not always reliable for structural use. One of the principal issues associated with masonry is the brittleness of the unit. When subject to seismic loads, the brittleness of the masonry magni es. In regions with high seismic activity and unspeci ed building codes or standards, masonry housing has developed into a death trap for countless individuals. A common approach concerning the issue associated with the brittle characteristic of masonry is addition of steel reinforcement. However, this can be expensive, highly dependent on skillfulness of labor, and particularly dependent on the quality of available steel. A proposed solution presented in this investigation consists of introducing steel bers to the lightweight aggregate concrete masonry mix. Previous investigations in the eld of lightweight aggregate ber-reinforced concrete have shown an increase in exural strength, toughness, and ductility. e outcome of this research project provides invaluable data for the production of a ductile masonry unit capable of withstanding seismic loads for prolonged periods.
This paper introduces a methodology to assess the accuracy of engineering estimates in relation to the final project cost. The objective of this assessment is to develop a comprehensive approach towards obtaining a more reliable estimate of the project cost. This approach relies on the review of a synthesis of literature, which provides a basis for determining key components in the estimation of the capital cost of a project. A systematic review of existing data for selected projects was obtained as well. Employed data cover sampled public transportation projects to maintain existing infrastructure within selected geographical location and specified time. Enhanced analysis of existing data through statistical models was employed to indicate potential measures for prevention of errors in the estimate due to uncertainties in the time, cost, and method of construction. The comparison of results with similar findings from past research shows the effectiveness of presented methodologies and opportunities to enhance statistical analyses of bids and engineering estimates. Conclusions enable project managers to address uncertainties in the bidding process and enhance financial sustainability of projects within specific programs.
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