The engineering practices for applying the microbial precipitation of carbonates require a design of the blending biocement solution (BCS). The BCS is usually blended with concentrated strains NO-A10, reaction media, such as urea and CaCl2, and a solvent, i.e., water or seawater. To characterize the BCS, the unknown microbial characteristics, such as the cell viability, are complex factors. Therefore, the optical density (OD) was redefined as Rcv OD*, in which OD* was the tentative OD of the BCS used and Rcv was the conversion rate concerning the cell viability. To determine Rcv values, a standard precipitation curve based on the precipitation rate at 24 h was determined. It was found that the curve was expressed by λ1 OD+ λ2 OD2, in which λ1 and λ2 were 8.46 M and −17.633 M, respectively. With this, the Rcv and OD values of unknown BCS were estimated from the results of precipitation tests using arbitrary OD* values. By extending the testing time, the second order term of OD or OD* was negligible. Accordingly, the precipitation amount is expressed as 8.46 OD, in which the OD can be estimated by precipitation tests using arbitrary OD* values of BCSs. Unless the Ca2+ value is dominant, the optimum blending of BCS can be determined by OD. Thus, it is concluded that the blending design of BCS is achieved using 8.46 OD, or 8.46 Rcv OD*, and the standard precipitation curve was defined in this study.

The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore, a method for evaluating the undrained shear strength of organic soils using artificial neural networks based on data obtained from a dilatometer test and organic soil properties is presented in this study. The presented neural network, with an architecture of 5-4-1, predicts the normalized undrained shear strength based on five independent variables: the normalized net value of a corrected first pressure reading (po − uo)/σ′v, the normalized net value of a corrected second pressure reading (p1 − uo)/σ′v, the organic content Iom, the void ratio e, and the stress history indictor (oc or nc). The neural model presented in this study provided a more reliable prediction of the undrained shear strength in comparison to the empirical methods, with a maximum relative error of ±10%.

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Infl uence of the rotation of principal stress directions on undrained shear strength. The paper presents the results of research on natural cohesive soil carried out in the Hollow Cylinder Apparatus (HCA). The main goal of this study was to determine the values of undrained shear strength at different angle of the rotation of principal stress directions. The research were carried out with anisotropic consolidation and shearing in undrained conditions (CAU) on cohesive soil with overconsolidation ratio (OCR) equals 4 and plasticity index (I p ) about 77%. The results of laboratory tests allow to assess the infl uence of the rotation of principal stress directions on undrained shear strength.