Method of fabricating artificial rock specimens based on extrusion free forming(EFF)3D printing

Three-dimensional(3D)printing technology has been widely used to create artificial rock samples in rock mechanics.While 3D printing can create complex fractures,the material still lacks sufficient similarity to natural rock.Extrusion free forming(EFF)is a 3D printing technique that uses clay as the printing material and cures the specimens through high-temperature sintering.In this study,we attempted to use the EFF technology to fabricate artificial rock specimens.The results show the physico-mechanical properties of the specimens are significantly affected by the sintering temperature,while the nozzle diameter and layer thickness also have a certain impact.The specimens are primarily composed of SiO_(2),with mineral compositions similar to that of natural rocks.The density,uniaxial compressive strength(UCS),elastic modulus,and tensile strength of the printed specimens fall in the range of 1.65–2.54 g/cm3,16.46–50.49 MPa,2.17–13.35 GPa,and 0.82–17.18 MPa,respectively.It is capable of simulating different types of rocks,especially mudstone,sandstone,limestone,and gneiss.However,the simulation of hard rocks with UCS exceeding 50 MPa still requires validation.

A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

In blasting operation,the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak.Therefore,predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome.Since many parameters affect the blasting results in a complicated mechanism,employment of robust methods such as artificial neural network may be very useful.In this regard,this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran.Back propagation neural network（BPNN） and radial basis function neural network（RBFNN） are adopted for the simulation.Also,regression analysis is performed between independent and dependent variables.For the BPNN modeling,a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN,architecture 636-2 with spread factor of 0.79 provides maximum prediction aptitude.Performance comparison of the developed models is fulfilled using value account for（VAF）,root mean square error（RMSE）,determination coefficient（R2） and maximum relative error（MRE）.As such,it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error.Also,sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak,respectively.On the other hand,for both of the outputs,specific charge is the least effective parameter.

New artificial neural networks for true triaxial stress state analysis and demonstration of intermediate principal stress effects on intact rock strength

Simulations are conducted using five new artificial neural networks developed herein to demonstrate and investigate the behavior of rock material under polyaxial loading. The effects of the intermediate principal stress on the intact rock strength are investigated and compared with laboratory results from the literature. To normalize differences in laboratory testing conditions, the stress state is used as the objective parameter in the artificial neural network model predictions. The variations of major principal stress of rock material with intermediate principal stress, minor principal stress and stress state are investigated. The artificial neural network simulations show that for the rock types examined, none were independent of intermediate principal stress effects. In addition, the results of the artificial neural network models, in general agreement with observations made by others, show （a） a general trend of strength increasing and reaching a peak at some intermediate stress state factor, followed by a decline in strength for most rock types; （b） a post-peak strength behavior dependent on the minor principal stress, with respect to rock type; （c） sensitivity to the stress state, and to the interaction between the stress state and uniaxial compressive strength of the test data by the artificial neural networks models （two-way analysis of variance; 95% confidence interval）. Artificial neural network modeling, a self-learning approach to polyaxial stress simulation, can thus complement the commonly observed difficult task of conducting true triaxial laboratory tests, and/or other methods that attempt to improve two-dimensional （2D） failure criteria by incorporating intermediate principal stress effects.

Application of microbially induced carbonate precipitation to form biocemented artificial sandstone

It is difficult to collect and characterise well-preserved samples of weakly-cemented granular rocks as conventional sampling techniques often result in destruction of the cementation.An alternative approach is to prepare synthetic geomaterials to match required specifications.This paper introduces microbially induced carbonate precipitation(MICP)as a method to reliably deliver artificiallycemented specimens with customised properties,closely resembling those of soft carbonate sandstones.The specimens are generated from materials with two highly different particle size distributions(PSDs)to access a range of achievable combinations of strengths and porosities.The MICP parameters are kept constant across all samples to obtain similar calcium carbonate characteristics(size of individual crystals,type,etc.),while injected volume is varied to achieve different cementation levels.Although uniform cementation of very coarse sands has been considered very difficult to achieve,the results show that both the fine and coarse sand specimens present high degrees of uniformity and a good degree of repeatability.The unconfined compressive strengths(UCSs)(less than 3000 kPa)and porosities(0.25e0.4)of the artificial specimens fall in the same range of values reported for natural rocks.The strength gainwas greater in the fine sand than that in the coarse sand,as the void size in the latter was significantly larger compared to the calcium carbonate crystals’size,resulting in precipitation on less effective locations,away from contacts between particles.The strengths and porosities obtained for the two sands in this work fall within ranges reported in the literature for natural soft rocks,demonstrating theMICP technique is able to achieve realistic properties and may be used to produce a full range of properties by varying the grain sizes,and possibly the width of PSD.

Experiment on the silica sol imbibition of low-permeability rock mass:With silica sol particle sizes and rock permeability considered

It’s a universal engineering problem to seal micro-cracks of low-permeability argillaceous rock mass by grouting in the fields of civil engineering and mining.This paper achieved the grouting sealing of lowpermeability artificial rocks with the permeability of 0.1–40 mD by adopting silica sol imbibition grouting.The variation characteristics of particle size,viscosity,and contact angle of silica sol during solidification and the pore size distribution of low-permeability artificial rocks were measured,and spontaneous imbibition tests of the artificial rocks were carried out.Finally,combined with the imbibition theory,percolation theory,and fracture medium grouting principle,the silica sol imbibition mechanism of lowpermeability rocks and soil was discussed.The results show that:(1)Silica sol can be injected into artificial rocks with the minimum permeability of 0.1 mD through spontaneous imbibition;(2)The particle size increase of silica sol leads to decreased wettability,affinity,and injectability in grouting materials;and(3)In the range of 0.1–40 mD,the grout absorption first increases and then decreases with increased permeability.The number of large pores and fractures in the rock mass is related to injectability,and the number of small and medium pores is related to the internal driving force of imbibition.This study provides a theoretical basis for silica sol grouting sealing of low-permeability argillaceous rocks and is,therefore,an important reference for application.