PREDICTION OF FRESH AND HARDENED PROPERTIES OF NORMAL CONCRETE VIA CHOICE OF AGGREGATE SIZES, CONCRETE MIX-RATIOS AND CEMENT

Concrete is the most commonly used building material for building most of the world’s buildings and infrastructure. After centuries of usage, it still remains the most widely adopted construction material worldwide. But in many developing nations, the frequent occurrence of building collapse has been mostly ascribed to poor quality concrete. As Nigeria is noted for frequent building collapse, this research reproduces standard concrete practices commonly adopted in Nigerian construction industry with the intent to predict design strength via choice of coarse aggregate sizes ( 12.5 mm, 19 mm, 30 mm and mixed), concrete mix-ratios (1:2:4, 1:3:6, 1:2:3) and ordinary Portland cement types (42.5R and 32.5N). Cement compound’s composition tests, fresh property tests and hardened property tests were conducted on samples. Test results from building cites of different Local Government Areas of Lagos State, Nigeria obtained in 2010 are compared with the compressive test results of this research via statistical tools. Results indicate that the fresh properties and hardened properties are influenced in a proportional manner by the sizes of aggregates and that the choices of aggregate sizes, concrete mix-ratios and cement types can be used to predict the fresh and hardened properties of normal concrete. This study also show that poor concrete production is one of the principal cause of frequent building collapse in Nigeria

Influence of Portland Cement Brands and Aggregates Sizes on the Compressive Strength of Normal Concrete

A good number of building failures have occurred in Nigeria which resulted in the loss of lives and a lot of these failures are attributed to the poor concrete practices used for the execution of these constructions. These have shown that the concrete technology adopted in Nigeria has some issues and requires urgent attention for development and improvement. This study explored methods of improving concrete practices so as to obtain better qualities structures. The research replicated some of the common concrete practices adopted by the construction industry in Nigeria to obtain the compressive strength of normal concrete. Two types of Portland cement brand, Type A and Type and three aggregate sizes (12.5mm, 19mm and 30mm) together with a mixed-size aggregate were utilized for the research. The concrete produced were tested for compressive strength and compared with test results from sites in Lagos Nigeria. The results showed how cement brands and aggregate sizes influence the compressive strength of normal concrete. The results also proved that the common poor quality concrete verified in Nigeria are not properly prepared

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran