Optimisation of the bolt profile configuration for load transfer enhancement

Both bolt profile shape and profile spacing (rib spacing) have been found to influence the bonding capacity of the grouted rock bolt. The bolt surface profile configuration has greater importance to rock bolt than the steel rebar used in civil engineering construction, because the rock bolt is subjected to greater dynamic loading than the steel rebar. The increased bonding capacity of bolts is important when supported ground is either heavily fractured, faulted or the supported ground is of soft formation, typically that of coal measure rocks. Past laboratory studies have identified the bolt profile spacing as of significant relevance to bolt resin rock bonding increase, however, no attempt has been made to determine the optimum spacing between the bolt profiles spacing. Accordingly, a series of laboratory tests were carried out on 22 core diameter bolts installed in cylindrical steel sleeve. The study was carried out by both push and pull testing. The push testing was carried out in 150 mm long sleeves while the pull testing was made in 115 mm long sleeves. Profile spacing tested include, 12.5, 25.0mm, 37.5 mm and 50 mm lengths. The profile spacing of 37.5 mm wide was found to provide the optimum bearin

Prediction of rock strength parameters for an Iranian oil field using neuro-fuzzy method

Uniaxial compressive strength (UCS) and internal friction coefficient (µ) are the most important strength parameters of rock. They could be determined either by laboratory tests or from empirical correlations. The laboratory analysis sometimes is not possible for many reasons. On the other hand, Due to changes in rock compositions and properties, none of the correlations could be applied as an exact universal correlation. In such conditions, the artificial intelligence could be an appropriate candidate method for estimation of the strength parameters. In this study, the Adaptive Neuro-Fuzzy Inference System (ANFIS) which is one of the artificial intelligence techniques was used as dominant tool to predict the strength parameters in one of the Iranian southwest oil fields. A total of 655 data sets (including depth, compressional wave velocity and density data) were used. 436 and 219 data sets were randomly selected among the data for constructing and verification of the intelligent model, respectively. To evaluate the performance of the model, root mean square error (RMSE) and correlation coefficient (R2) between the reported values from the drilling site and estimated values was computed. A comparison between the RMSE of the proposed model and recently intelligent models shows that the proposed model is more accurate than others. Acceptable accuracy and using conventional well logging data are the highlight advantages of the proposed intelligent model

Correction to: The emerging role of probiotics as a mitigation strategy against coronavirus disease 2019 (COVID�19) (Archives of Virology, (2021), 166, 7, (1819-1840), 10.1007/s00705-021-05036-8)

Authors would like to correct the error in their publication. The original article has been corrected. 1. Reference 17 is incorrect. The correct one should be �The probiotic Bifidobacterium in the management of Coronavirus: A theoretical basis� https://doi.org/10.1177/2058738420961304. 2. The unnecessary symbol �??� found in text is deleted. © 2021, Springer-Verlag GmbH Austria, part of Springer Nature

Bacterial co-infections with SARS-CoV-2

The pandemic coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has affected millions of people worldwide. To date, there are no proven effective therapies for this virus. Efforts made to develop antiviral strategies for the treatment of COVID-19 are underway. Respiratory viral infections, such as influenza, predispose patients to co-infections and these lead to increased disease severity and mortality. Numerous types of antibiotics such as azithromycin have been employed for the prevention and treatment of bacterial co-infection and secondary bacterial infections in patients with a viral respiratory infection (e.g., SARS-CoV-2). Although antibiotics do not directly affect SARS-CoV-2, viral respiratory infections often result in bacterial pneumonia. It is possible that some patients die from bacterial co-infection rather than virus itself. To date, a considerable number of bacterial strains have been resistant to various antibiotics such as azithromycin, and the overuse could render those or other antibiotics even less effective. Therefore, bacterial co-infection and secondary bacterial infection are considered critical risk factors for the severity and mortality rates of COVID-19. Also, the antibiotic-resistant as a result of overusing must be considered. In this review, we will summarize the bacterial co-infection and secondary bacterial infection in some featured respiratory viral infections, especially COVID-19. © 2020 International Union of Biochemistry and Molecular Biolog

Chain Pillar Design - Can We?

In the ten years since the University of NSW proposed a pillar design methodology for bord and pillar operations, the Australian coal mining industry has changed substantially. What was primarily a bord and pillar design approach is now being applied to chain pillar design in longwall mines where the requirements are substantially different. The dimensions of chain pillars can impact on tailgate conditions (roof, rib and floor), seal performance, and surface subsidence. The status of chain pillar design practice in Australia is reviewed, with a focus on defining pillar strength, chain pillar loading, and assessing the performance of the roof/pillar/system. A new pillar strength equation is proposed for Australian coal that applies for all width/height ratios. An alternative analysis of probability of failure of chain pillars is presented

Modelling of Sheared Behaviour Bolts Across Joints

A three dimensional numerical model was developed to simulate the shearing of reinforced joints. Reinforcement of the shearing surfaces is effected with pretensioned bolts installed perpendicular to the sheared joint surface. The influence of bolt pretension forces examined included 20 kN, 50 kN and 80 kN respectively and aimed to complement the experimental work on double shearing of bolts installed in two different strength concrete blocks. Post shear stresses were analysed for both linear and nonlinear regions of the load - deflection curve. Simulation of several models in varying conditions provided a better understanding of the role of bolt pretensioning in sheared joint and bedding plane reinforcement. There was a clear relationship between the level of bolt pretensioning and the shear load applied. It was shown that the strength of the sheared composite medium was influenced by the applied shear load. The modeling study is part of a comprehensive programme of research work aimed at providing a better understanding of load transfer mechanisms in bolt /resin /rock for effective strata reinforcement

An Assessment of Load Transfer Mechanism Using the Instrumented Bolts

Load transfer capacity and failure mechanism of a fully grouted bolt installed across joint plane in shear is evaluated experimentally and numerically, tests were made on un-instrumented and strained gauge instrumented bolts. Four types of bolts, with different properties and surface configurations were selected for the study. The changes in strength of the concrete, bolt mechanical properties and bolt pretension load were evaluated in different shear environments. Results from the instrumented bolts and numerical simulation showed that the tensile and compression stresses and strains are generated at early stage of loading and hinge points are created at both sides of the shear joints. Strains are in greater value in vicinity of the shear joint. The failure location moves towards the bolt joint intersection due to the increasing shear load, shear displacement and axial load developed along the bolt