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Infrastructure design, construction and development experts are making frantic efforts to overcome the overbearing effects of greenhouse gas emissions resulting from the continued dependence on the utilization of conventional cement as a construction material on our planet. The amount of CO2 emitted during cement production, transportation to construction sites, and handling during construction activities to produce concrete is alarming. The present research work is focused on proposing intelligent models for fly ash (FA)-based concrete comprising cement, fine and coarse aggregates (FAg and CAg), FA, and water as mix constituents based on environmental impact (P) considerations in an attempt to foster healthier and greener concrete production and aid the environment. FA as a construction material is discharged as a waste material from power plants in large amounts across the world. Its utilization as a supplementary cement ensures a sustainable waste management mechanism and is beneficial for the environment too; hence, this research work is a multi-objective exercise. Intelligent models are proposed for multiple concrete mixes utilizing FA as a replacement for cement to predict 28-day concrete compressive strength and life cycle assessment (LCA) for cement with FA. The data collected show that the concrete mixes with a higher amount of FA had a lesser impact on the environment, while the environmental impact was higher for those mixes with a higher amount of cement. The models which utilized the learning abilities of ANN (-BP, -GRG, and -GA), GP and EPR showed great speed and robustness with R2 performance indices (SSE) of 0.986 (5.1), 0.983 (5.8), 0.974 (7.0), 0.78 (19.1), and 0.957 (10.1) for Fc, respectively, and 0.994 (2.2), 0.999 (0.8), 0.999 (1.0), 0.999 (0.8), and 1.00 (0.4) for P, respectively. Overall, this shows that ANN-BP outclassed the rest in performance in predicting Fc, while EPR outclassed the others in predicting P. Relative importance analyses conducted on the constituent materials showed that FA had relatively good importance in the concrete mixes. However, closed-form model equations are proposed to optimize the amount of FA and cement that will provide the needed strength levels without jeopardizing the health of the environment.

SUMMARYThe aim of the present study is the detailed numerical investigation of the stress/strain distribution in polymeric matrix composites reinforced with spherical inclusions, using the finite element method (FEM). Perfect adhesion between the matrix and the inclusions was assumed and from the computed stress/strain profiles of the system, debonding initiation and propagation can easily be predicted. Analytical models available in the literature may predict the stress/strain distribution within the inclusion and along the matrix/inclusion interface, while the FEM may yield results for the whole composite, including within the inclusions. Three typical volume fractions of the composite were examined and the results were justified by the analytical predictions of other researchers. The numerical results show that the matrix starts to debond from the inclusions at angular distance forty-five degrees and as the applied load increases the debonding zone gradually extends.

In this research study, extensive literature searches on the compressive strength of concrete produced from the addition of fly ash (FA) and silica fume (SF) as extra constituents to the conventional concrete mixes, which gave rise to 330 mix points of concrete database. Due to the worrisome environmental impact of concrete production and usage in concrete activities, it has been pertinent to conduct the life cycle impact assessment of this procedure. Secondly, due to the over dependence of concrete production experts on laboratory exercise, there is also an urgent need to propose equations that reduce this dependence, that can be used in design, construction and performance evaluation of concrete infrastructure, hence the multi-objective nature of this research work. The results of the global warming potential (GWP) based on cement dosage show that Portland cement contributes about 90% of the total score. This is followed by the use of coarse aggregate contributing 6%, superplasticizer, 3% and fine aggregates, 2%. These show the functions of CO2 emissions and other greenhouses gas emissions in the entire system. Also, the result of the terrestrial acidification potential (TAP) for the concrete mixes in this study show that the lowest cement mix “C340-FAg658-FA0-SF15ˮ has a human toxicity, both carcinogenic and non-carcinogenic that showed an added impact of about 14 kg of 1, 4 equivalents of dichlorobenzene (DCB eq.). This result is 428% less impact than other studies found in the literature that used FA. Finally, it was found that the addition of FA and SF in concrete has a lowering effect on the environmental impact indicators due to reduced cement dosage. Furthermore, the results of the model predictions show that ANN with a performance index of 0.986 (4.8%) showed decisive superiority to predict the compressive strength of the FA-SF concrete over EPR, 0.951 (8.7%), GP, 0.94 (9.5%) and GEP, 0.93 (10%).

Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of two types of steel liquid storage tanks (namely, broad and slender, with aspect ratios of height to radius equal to 0.6 and 1.85) founded on half-space soil is scrutinized under different earthquake ground motions. For a better comparison, the six considered ground motions are classified, based on their pulse-like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Additionally, four types of soils are used to consider a wide variety of soil properties. To this end, after deriving the equations of motion, MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to a decrease in the impulsive displacement, overturning moment, and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period.

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The vibrations induced by moving trains especially in close distances with high-rise buildings can be destructive. The high technology of wilding rails induced a high train velocity which is associated with high vibrations. The buildings near the railways suffer from the train-induced vibrations. In this paper, a 3D FEM model was constructed to study the train-induced vibrations on a nearby high-rise building (HRB), show its response and investigate the most suitable technique to mitigate the effect of the train-induced vibrations by an open trench or a geofoam-filled trench. Three trench parameters were investigated to enhance the mitigation performance, the distance from the trench to the HRB, the trench depth and the use of either open (empty) trench or geofoam-filled trench. The geofoam-filled trench technique improved the dynamic response of the structure. Thus, trenches filled with geofoam can be considered a protection technique for high-rise buildings constructed near moving trains.