Establishing Threshold Level for Gravel Inclusion in Concrete Production

The paper investigated the threshold level for gravel inclusion in concrete production. Concrete was produced using granite/gravel combination in varying percentages of 90/10, 80/20, 70/30, 60/40, 50/50, 40/60, 30/70, 20/80 and 10/90. Concrete made from 100 % granite and 100 % gravel served as controls while other constituents of the concrete were kept constant. Two different mix ratios of 1:2:4 and 1:3:6 were employed. Sieve analysis was carried out on the aggregates while slump and compaction factor tests were carried out on fresh concrete. Compressive and splitting tensile strength tests were performed on hardened concrete. Specimens were produced using 150 mm cubes and 150 mm × 300 mm cylinders for compressive and tensile strength tests respectively. The size analysis results show that the coefficient of uniformity for sand, gravel and granite are 2.29, 2.95 and 4.07 respectively an indication that the fine and coarse aggregates were well graded. The slump and compactive factor increased with increasing gravel content. Compressive strength tests showed that 60/40 and 70/30 percentage of granite/gravel combination with values of 21.15 N/mm2 and 15.17 N/mm2 respectively for mix ratios 1:2:4 and 1:3:6 at 28 days was quite satisfactory. The minimum requirement of 20 N/mm2 and 15 N/mm2 for 1:2:4 and 1:3:6 mix ratio respectively as specified by BS 8110:Part 1 (1997), EN 1992-1-1 (2004) were satisfied . The splitting tensile strength of 70/30 percentage of granite/gravel combination for 1:2:4 and 1:3:6 mix ratios were 10.50 N/mm and 4.70 N/mm2 respectively. The study concluded that the thresholds corresponding to 60 % and 70 % granite contents are suitable for 1:2:4 and 1:3:6 concrete mix proportions respectively

A Study of Neem Seed Husk Ash as Partial Replacement for Cement in Concrete

The production of neem products from neem tree generates large quantity of waste annually. There is need to reduce environmental pollution resulting from neem seed covering. Therefore, the use of Neem Seed Husk Ash (NSHA) as partial substitution for cement in concrete was investigated. Neem seed husk was obtained from Bishop Smith Memorial College, Ilorin, Nigeria; sun – dried for 3 days and then calcined at 650o C. The calcined neem seed husk was ground and sieved using 200 μm sieve to obtain NSHA. Pozzolanicity test was conducted on NSHA to determine its chemical composition. Concrete was produced with 5, 10, 15, 20 and 25% by weight of NSHA substitution for ordinary Portland cement. Workability tests (slump and compacting factor) were performed on fresh concrete while compressive strength test was conducted on 150 mm cubes at ages 3, 7, 14, 21, 28, 56, 90 and 180 days for the hardened concrete. NSHA mainly comprises Al2O3, SiO2 and Fe2O3 with a combined percentage of 75.35%.  The slump and compacting factors of NSHA concrete ranged from 5.50 mm to 10.00 mm and 0.91 to 0.95, respectively. The compressive strength at 180 days decreased from 26.9 N/mm2 to 19.4 N/mm2 as the NSHA content increased from 5% to 25%. Only 5% NSHA substitution is adequate to enjoy maximum benefit of strength gain

Wood Ash from Bread Bakery as Partial Replacement for Cement in Concrete

This paper reports the results of experiments evaluating the use of wood ash from bread bakery as partial replacement for ordinary Portland cement in concrete. The chemical composition of the wood ash as well as the workability and compressive strength of the concrete were determined. Wood ash was used to replace 5% - 25% by weight of the cement in concrete. Concrete with no wood ash serves as the control. The mix ratio used was 1:2:4 with water to binder ratio maintained at 0.5. The Compressive strength was determined at curing ages 3, 7, 28, 56, 90 and 120 days. The results showed that wood ash from bread bakery is a Class F fly ash since the sum of (SiO2 +Al2O3 +Fe2O3) is greater than 70%. The compressive strength of wood ash concrete increases with curing period and decreases with increasing wood ash content. There was a sharp decrease in compressive strength beyond 10% wood ash substitution. It was concluded that a maximum of 10% wood ash substitution is adequate for use in structural concret

Optimal Raw Material Mix for the Production of Rice Husk Ash Blended Cement

Rice husk is the residue left after the grain is removed. Previous studies considered the conversion of rice husk into useful material by incorporating its ash into cement on site. However, the mixing on site was arbitrary. In this study, the optimization of Rice Husk Ash (RHA) blended cement in a cement factory was carried out. Fourteen (14) experimental runs of RHA-blended cements were generated using three-factor D-optimal design (RHA, Ordinary Portland Cement (OPC) clinker and gypsum). The chemical compositions of RHA, OPC-clinker and RHA-blended cements produced were determined using X-ray fluorescence analyzer. The physical properties of the RHA-blended cement produced were also determined. Design-Expert 6.0.8 was used to optimize the RHA-blended cement. The optimum mixture components for the production of RHA-blended cement were 12.45% RHA, 83.44 % OPC-clinker and 4.11 % gypsum. The  D-optimal design was effective in enhancing the properties of RHA blended cement

Enhancing the Mechanical Properties of Lateritic Brick for Better performance

The research considered the production of improved stabilized lateritic Bricks (ISLB) with enhanced mechanical properties. The research data were derived from laboratory experiments which include capillary test, erosion test, abrasion test, density test and compressive strength test. Three batches of 290mm x 140mm x 100mm brick samples were produced which are: the Adobe Unstabilized Lateritic Bricks (AULB), Improved Stabilized Lateritic Brick (ISLB) and the Control Stabilized Lateritic Bricks (CSLB). Brick stabilization was maintained at 5% by weight of cement. Compaction of the bricks were carried out manually; the moulded bricks were carefully extruded in good shape and placed on clean, hard flat surface to allowed to dry under normal atmospheric temperature and pressure . The ISLB was divided into four groups of 12 bricks samples immersed in solution of zycosil and water in the following proportion by volume: (1:100),(1:200),(1:300) and (1:400) for 30 minutes and dried under normal atmospheric temperature and pressure before curing commenced. The result of the capillary test on bricks samples after 24 hours showed that AULB and CSLB has (0.35 and 0.15)kg weight difference equivalent of (0.00599 and 0.00256) kg/m2/min suction rate while the ISLB have 0.05kg weight difference equivalent to 0.000855kg/m2/min suction rate. The result of erosion test for brick durability ranked between very firm for ISLB of 1:100, 1:200 and 1:300 Zycosil Water Solution (ZWS), firm for ISLB of 1:400 ZWS; firm for CSLB and loose for AULB. The abrasion test result showed that the ISLB have abrasion value of (1,2,2 and 2)% while the CSLB and AULB have (3 and 12)% abrasion value. The density of ISLB are (1933.50, 1921.18, 1916.26 and 1908.87) kgm-3 at 28 days while the density of CSLB and AULB were (1926.11 and 1800.49) kgm-3. Density results conform to minimum specification requirement for lateritic bricks of bulk density of 1810kgm-3 as recommended by the Nigeria Building and Road Research Institute (NBRRI). Compressive strength test for the ISLB are (3.16, 3.10, 3.07 and 3.08) Nmm-2 at 28 days while the compressive strength test for CSLB and AULB stood at (3.15 and 2.41) Nm-2 which conforms to NBRRI recommended value of compressive strength ranges of (3 to 3.5) Nmm-2 at 5% stabilization level. It was concluded that the mechanical properties of improved stabilized lateritic brick are better than CSLB and AULB in terms of capillary rise, erosion, abrasion, density and compressive strength

Production And Testing Of Lateritic Interlocking Blocks

The production and testing of lateritic interlocking blocks were examined. The experiments involved the production of 250 × 130 × 220 mm3 interlocking blocks with laterite samples obtained from Aroje (Ogbomoso North L.G), Olomi (Ogbomoso South L.G), Idioro (Surulere L.G) and Tewure (Orire L.G) using a locally fabricated manual steel mould and a 4.5 kg rammer. The blocks were tested in the laboratory to determine their compressive strength, water absorption and resistance to abrasion. The results indicated that all of the stabilised blocks satisfied the minimum 28 day wet compressive strength of 1.0 Nmm–2 recommended by the Nigeria Building and Road Research Institute. The minimum seven day dry compressive strength for 5% cement stabilised blocks of not less than 1.60 Nmm–2, as recommended in the National Building Code, was not satisfied by all of the blocks. However, with 10% cement stabilisation, blocks from Olomi and Idioro laterites satisfied the minimum seven day strength with values of 2.13 Nmm–2 and 1.62 Nmm–2, respectively. Only laterites from Olomi and Idioro that met the minimum seven day requirements were concluded to be suitable for the production of interlocking blocks in southwestern Nigeria

Machine learning algorithms in wood ash-cement-Nano TiO2-based mortar subjected to elevated temperatures

Mortar is subjected to high temperatures during fire attacks or when it is near heat-radiating equipment like furnaces and reactors. The physical and microstructure of mortar were considerably altered by high temperatures. In this investigation, the effects of elevated temperatures on the flexural and compressive strengths of wood ash (WA) cement mortar modified with green-synthesised Nano titanium oxide (NT) were examined. In order to produce mortar samples, the cement was replaced with 10% WA, and 1–3% NT by weight of binder were added at constant water-binder ratio. The specimens were heated to 105, 200, 400, 600, and 800 °C with an incremental rate of 10 °C per min in the electric furnace for a sustained period of 2 h to measure their strengths. The machine learning algorithm of artificial neural networks with Levenberg-Marquardt backpropagation training techniques of different network architectures was engaged to predict the compressive strength of WA-cement-NT-based mortar produced. The findings showed that higher temperatures reduced compressive strength after 400 °C and flexural strength after 200 °C. The mortar specimen with a 3% NT addition showed the highest residual compressive strength increase, ranging from 18.75 to 27.38%. Compared to compressive strength, flexural strength is more severely affected by high temperatures. The backpropagation training algorithm revealed that each hidden layer displayed its unique strong prediction. However, Levenberg-Marquardt backpropagation training technique of 7–10-10-1 network structures yielded the best performance metrics for training, validation, and testing compared to 7-10-10-10 and 7-10-1 network architectures

Predicting the splitting tensile strength of concrete incorporating anacardium occidentale nut shell ash using reactivity index concepts and mix design …

The prevalence of global warming and climate change are associated with carbon dioxide (CO2) emitting from fossil fuel combustion and Portland cement (PC) production. However, in a bid to minimize over-reliance on PC, this study recycled a supplementary cementitious material (SCM), anacardium occidentale nutshell ash (AONSA), for the production of green concrete. AONSA was used as a replacement for Portland limestone cement (PLC) at 0, 5, 10, 15, and 20 % using the mix design proportions (MDPs) of grades 25 (M 25), 30 (M 30), and 40 (M 40) concrete. The chemical compositions of both AONSA and PLC were analyzed. Moreover, the chemical moduli of each and mixed binder were determined and evaluated, hence quantifying the reactivity indexes (RIs). Consequently, RIs and MDPs were applied to predict the splitting tensile strength. Compared with the experimental results, the predictive splitting tensile strength relative to the RIs and the MDPs yielded a high precision with 95 % R2 at 28 days curing. Therefore, the model equations proposed by this study can be applied to the concrete mix design procedure for the splitting tensile strength of green concrete incorporating SCMs provided the chemical compositions of each and mixed material are established

Machine learning algorithms in wood ash-cement-Nano TiO2-based mortar subjected to elevated temperatures

Mortar is subjected to high temperatures during fire attacks or when it is near heat-radiating equipment like furnaces and reactors. The physical and microstructure of mortar were considerably altered by high temperatures. In this investigation, the effects of elevated temperatures on the flexural and compressive strengths of wood ash (WA) cement mortar modified with green-synthesised Nano titanium oxide (NT) were examined. In order to produce mortar samples, the cement was replaced with 10% WA, and 1–3% NT by weight of binder were added at constant water-binder ratio. The specimens were heated to 105, 200, 400, 600, and 800 °C with an incremental rate of 10 °C per min in the electric furnace for a sustained period of 2 h to measure their strengths. The machine learning algorithm of artificial neural networks with Levenberg-Marquardt backpropagation training techniques of different network architectures was engaged to predict the compressive strength of WA-cement-NT-based mortar produced. The findings showed that higher temperatures reduced compressive strength after 400 °C and flexural strength after 200 °C. The mortar specimen with a 3% NT addition showed the highest residual compressive strength increase, ranging from 18.75 to 27.38%. Compared to compressive strength, flexural strength is more severely affected by high temperatures. The backpropagation training algorithm revealed that each hidden layer displayed its unique strong prediction. However, Levenberg-Marquardt backpropagation training technique of 7–10-10-1 network structures yielded the best performance metrics for training, validation, and testing compared to 7-10-10-10 and 7-10-1 network architectures

Machine learning algorithms in wood ash-cement-Nano TiO2-based mortar subjected to elevated temperatures

Mortar is subjected to high temperatures during fire attacks or when it is near heat-radiating equipment like furnaces and reactors. The physical and microstructure of mortar were considerably altered by high temperatures. In this investigation, the effects of elevated temperatures on the flexural and compressive strengths of wood ash (WA) cement mortar modified with green-synthesised Nano titanium oxide (NT) were examined. In order to produce mortar samples, the cement was replaced with 10% WA, and 1–3% NT by weight of binder were added at constant water-binder ratio. The specimens were heated to 105, 200, 400, 600, and 800 °C with an incremental rate of 10 °C per min in the electric furnace for a sustained period of 2 h to measure their strengths. The machine learning algorithm of artificial neural networks with Levenberg-Marquardt backpropagation training techniques of different network architectures was engaged to predict the compressive strength of WA-cement-NT-based mortar produced. The findings showed that higher temperatures reduced compressive strength after 400 °C and flexural strength after 200 °C. The mortar specimen with a 3% NT addition showed the highest residual compressive strength increase, ranging from 18.75 to 27.38%. Compared to compressive strength, flexural strength is more severely affected by high temperatures. The backpropagation training algorithm revealed that each hidden layer displayed its unique strong prediction. However, Levenberg-Marquardt backpropagation training technique of 7–10-10-1 network structures yielded the best performance metrics for training, validation, and testing compared to 7-10-10-10 and 7-10-1 network architectures