A systematic review and meta-analysis of artificial neural network application in geotechnical engineering: theory and applications

Artificial neural network (ANN) aimed to simulate the behavior of the nervous system as well as the human brain. Neural network models are mathematical computing systems inspired by the biological neural network in which try to constitute animal brains. ANNs recently extended, presented, and applied by many research scholars in the area of geotechnical engineering. After a comprehensive review of the published studies, there is a shortage of classification of study and research regarding systematic literature review about these approaches. A review of the literature reveals that artificial neural networks is well established in modeling retaining walls deflection, excavation, soil behavior, earth retaining structures, site characterization, pile bearing capacity (both skin friction and end-bearing) prediction, settlement of structures, liquefaction assessment, slope stability, landslide susceptibility mapping, and classification of soils. Therefore, the present study aimed to provide a systematic review of methodologies and applications with recent ANN developments in the subject of geotechnical engineering. Regarding this, a major database of the web of science has been selected. Furthermore, meta-analysis and systematic method which called PRISMA has been used. In this regard, the selected papers were classified according to the technique and method used, the year of publication, the authors, journals and conference names, research objectives, results and findings, and lastly solution and modeling. The outcome of the presented review will contribute to the knowledge of civil and/or geotechnical designers/practitioners in managing information in order to solve most types of geotechnical engineering problems. The methods discussed here help the geotechnical practitioner to be familiar with the limitations and strengths of ANN compared with alternative conventional mathematical modeling methods.

     

Hydration process and crack tendency of concrete based on resistivity and restrained shrinkage crack

Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were monitored by using a non-contact electrical resistivity apparatus, a novel plastic ring mould and penetration resistance methods, respectively. The results show the highest resistivity of C30 at the early stage until a point when C50 accelerated and overtook the others. It has been experimentally confirmed that the crossing point of C30 and C50 corresponds to the final setting time of C50. From resistivity derivative curve, four different stages were observed upon which the hydration process is classified; these are dissolution, induction, acceleration and deceleration periods. Consequently, restrained shrinkage crack and setting time results demonstrated that C50 set and cracked the earliest. The cracking time of all the samples occurred within a reasonable experimental period thus the novel plastic ring is a convenient method for predicting concrete’s crack potential. The highest inflection time (t _i) obtained from resistivity curve and the final setting time (t _f) were used with crack time (t _c) in coming up with mathematical models for the prediction of concrete’s cracking age for the range of concrete grade considered. Finally, an ANSYS numerical simulation supports the experimental findings in terms of the earliest crack age of C50 and the crack location.     

Optimizing Levenberg–Marquardt backpropagation technique in predicting factor of safety of slopes after two-dimensional OptumG2 analysis

Engineering with Computers - This study intended to use optimized artificial neural network (ANN) for the design of pure cohesive slopes (by means of considering sufficient safety factors (SF) of...     

Application of PSO–ANN modelling for predicting the exergetic performance of a building integrated photovoltaic/thermal system

Engineering with Computers - The main objective of this study is to examine the feasibility of hybrid PSO–ANN technique to estimate the exergetic performance of a building integrated...