The present study focuses on proposing various statistical models, such as linear regression (LR), nonlinear regression (NLR), and artificial neural network (ANN), to forecast the compressive strength of environmentally friendly high-strength concrete, incorporating waste agricultural material like palm oil fuel ash (POFA). A dataset of 105 experimental observations was compiled from existing literature to achieve this goal, which was subsequently partitioned into training and testing subsets. Each model was developed based on the training data and evaluated using the testing data. The performance of each proposed model was gauged using diverse statistical metrics like the coefficient of determination, mean absolute error, root mean square error, and scatter index to identify the most effective model. The findings indicate that using POFA with a finer particle size exerts a greater influence on the concrete's properties. The replacement was done using the weight method, and the predicted equation worked with the variation of the used rate of POFA from 0 to 60% of total binder weight. Substituting a portion of cement with POFA leads to a reduction in the heat of hydration and an extension of the setting time. The optimal percentage of POFA is 30%, yielding mechanical properties superior to those of the control mixture, particularly in the later stages of development. Among the models considered, the ANN demonstrates superior efficiency and accuracy in predicting the compressive strength of conventional concrete modified with POFA compared to LR and NLR models. This is evident in the ANN's higher R2 values of 52% and 16%, respectively, and a lower scatter index below 0.1%.

The objective of this study is to investigate the performance of normal- and high-strength concretes including limestone powder (LP) through their mechanical properties. Moreover, sustainable flat plates made of these concretes were investigated through their punching strength. For this purpose, two different types of concrete (normal- and high-strength) with various limestone replacement ratios of 0%, 5%, 15%, and 20% by weight were designed. The fresh and hardened characteristics of the mixtures were investigated at various ages. By this means, the experimental behavior of reinforced concrete (RC) flat plate slabs made with limestone powder subjected to punching shear failure was studied. Slump value increased up to a 5% replacement of LP; after that, there was a tendency for the slump value to decrease as the replacement of limestone in normal-strength LP concrete increased. However, slump values for high-strength LP concrete increased as the LP replacement amount increased. There was a steady decrease in the compressive strength and splitting tensile strength values with the increase in LP content in normal concrete. However, in the high-strength LP concrete, with more than 10% of replacement LP, a decrease in the compressive strength values and splitting tensile strength values occurred. Compared to the control slab specimen without LP, in normal strength, the slab specimens with LP exhibit a larger ultimate shear load for slab specimens containing 5% and 10% of LP. The maximum increment for RC slabs containing 10% limestone powder was 3.8%. However, in high-strength concrete, the slab specimens with LP remained at the same ultimate shear load as control slabs, up to 10% of LP. high-strength concrete slabs with 5–20% LP showed an overall increase of (17.2%) in punching strength over the corresponding LP normal-strength concrete slabs. The corresponding increase for control slabs was 18.8%. It can be concluded that introducing LP improves the slab punching strength in a similar way that is found in non-sustainable slabs when using either normal- or high-strength concrete.

Fine aggregates used for concrete works in Sulaymaniyah city frequently fail to meet the standard requirements for gradation and fineness modulus in cement concrete. This paper aims to critically evaluate gradation, fineness modulus, and clay contents of various natural sands produced and used for concrete work in the region. Sixteen field sand samples were collected from various sites in Darbandikhan (5 samples), Qalat Dizah (5 samples), Koysinjaq (5 samples), and Piramagroon (1 sample) confirming to ASTM D75. The field samples were parted into test specimens based on ASTM C702. Then, sieve analysis was carried out on the oven-dry test specimens in compliance with ASTM C136. The test results of fine aggregates were compared with American, British, and Iraqi specification standards using ASTM C33, BS 882, and IQS No. 45. It was revealed that only three sands satisfy the ASTM gradation limits while others do not comply and are on the coarser side. Also, eight samples meet the requirements recommended by BS 882, whereas five samples meet limits by IQS No. 45. It was found that only three sands have the fineness modulus within the ranges recommended by ACI 211.1 and ACI 211.4, while the others have high values. Furthermore, it was found that all sands include an allowable amount of finer particles passing sieve size 0.075 mm. In order to improve particle size distributions, it is recommended to use the blending method to obtain a suitable fine aggregate from two or more failed sands.