The design of reinforced concrete spread foundations mainly depends on soil bearing capacity, loading value, and column size. So for each design case, tiresome calculations and time consumption are needed. In this paper, generalized design charts are presented and plotted according to derivations based on the ACI 318 M-2019 Code. These charts could be used directly by the structural designers to estimate the column size, foundation thickness, and dimensions as well as the foundation reinforcement under a certain given concentric load assuming a uniformly distributed contact pressure underneath the foundation. Of noteworthy, these charts are oriented to deal with square isolated footings with a square concentric column, covering reasonable r

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

In this study, three strengthening techniques, near-surface mounted NSM-CRFP, NSM-CFRP with externally bonding EB-CFRP, and hybrid CFRP with circularization were studied to increase the seismic performance of existing RC slender columns under lateral loads. Experimentally, 1:3 scale RC models were studied and subjected to both lateral static load and seismic excitation. In the dynamic test, a model was subjected to El Centro 1940 NS earthquake excitation by using a shaking table. According to the test results, the strengthening techniques showed a significant increase in load carrying capacity, of about 86.6%, and 46.6%, for circularization and NSM-CFRP respectively, of the reference unstrengthened columns. On the other hand, column

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

This study investigates the impact of varying glass fiber-reinforced polymer (GFRP) stirrup spacing on the performance of doubly GFRP-reinforced concrete beams. The research focuses on assessing the behavior of GFRP-reinforced concrete beams, including load-carrying capacity, cracking, and deformability. It explores the feasibility and effectiveness of GFRP bars as an alternative to traditional steel reinforcement in concrete structures. Six concrete beams with a cross-section of 300 mm (wide) × 250 mm (deep), simply supported on a 2100 mm span, were tested. The beams underwent four-point bending with two concentrated loads applied symmetrically at one-third of the span length, resulting in a shear span (a)-to-depth (h) ratio of 2.

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo