Effect of curing, capillary action, and groundwater level increment on geotechnical properties of lime concrete: Experimental and prediction studies

Lime concrete and lime treatment are two attractive techniques for geotechnical engineers.However,researches have rarely been carried out to study the effects of moisture and capillary action due to increasing groundwater level on geotechnical properties of lime concrete.The aim of this study is to investigate the effects of curing time and degree of saturation on some of geotechnical properties of lime concrete such as unconfined compressive strength(UCS),secant modulus(ES),failure strain,brittleness index(IB),and deformability index(ID) using unconfined compression tests.First of all,geotechnical and chemical properties of used materials were determined.After curing times of 14 d,28 d,45 d,and 60 d in laboratory condition,the specimens were exposed to saturation levels ranging from 0 to 100%.The results showed that the moisture and curing time have significant effects on the properties of lime concrete.Based on the results of scanning electron micrograph(SEM) test,it was observed that the specimen was characterized by a rather well-structured matrix since both the filling of a large proportion of the coarse-grained soil voids by clay and the pozzolanic activity of lime led to retaining less pore water in the specimen,increasing the UCS and ES,and consequently resisting against swelling and shrinkage of the clay soil.Moreover,due to the pozzolanic reactions and reduction of water,by increasing the curing time and decreasing the degrees of saturation,UCS,ES,and IBincreased,and IDdecreased.Based on the experimental results,a phenomenological model was used to develop equations for predicting the properties in relation to the ratio of degree of saturation/curing time.The results showed that there was a good correlation(almost R2> 90%) between the measured parameters and the estimated ones given by the predicted equations.

Developing a novel big dataset and a deep neural network to predict the bearing capacity of a ring footing

The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.