Incorporating Calibrated Numerical Models in Estimating Moduli of Compacted Geomaterials from Integrated Intelligent Compaction Measurements and Laboratory Testing

Abstract

Proof rolling after completion of compaction of earthwork using intelligent compaction (IC) technology can be used to assess the uniformity of the compacted geomaterials and to identify less stiff compacted areas. To better understand the process of quality management using IC technology, a three-dimensional finite element model was developed to document the theoretical limitations and the sensitivity of IC technology. The model can also be used for setting the target values, and can be part of a methodology to extract the moduli of geomaterials in more rigorous and defensible specifications. Different levels of complexity in relation to linear versus nonlinear behavior of geomaterial and different levels of roller operating conditions (static versus dynamic, moving versus stationary) can be assigned to the model. Such model can only be used with confidence if it is calibrated and validated with experimental field data. Five test sites including single-layer (subgrade only) and two-layer (subgrade and base) geosystems were instrumented using in-ground sensors for calibrating the model. Different vibratory IC rollers from different manufacturers were used to implement IC tests at vibratory stationary as well as moving conditions at the test sites. In all scenarios, a locally calibrated transfer function was necessary to accommodate the differences in the numerical models and vibration data obtained from the IC measurements on test sections with distinct geomaterial conditions. The study also concluded that the predictive power of the numerical models improves if the field measurements and laboratory data are integrated, and more importantly the variability of the materials is incoprorated.

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

“…The automatic elevation mode means that the electromechanical controller of coal mining automatically adjusts the height of cutting drum according to the target trajectory of the cutting drum set, so as to use the fluctuation of the roof and floor of the working face. The operator tracks a working cycle of the shearer, adjusts the height of the cutting drum according to the actual operating conditions of the shearer, and records the trajectory data of the cutting drum and the height data of the cutting drum at characteristic positions, which are used as the target trajectory and target height for automatic adjustment [12]. The intelligent control technology, machine learning and neural network learning algorithm are used to plan and control the running trajectory of the shearer and the cutting drum trajectory.…”

Roller-integrated compaction monitoring and assessment of high and low liquid limit silt subgrades using the Green spline interpolation algorithm

“…Compaction is a key link in highway subgrade construction [3], and the research on the compaction characteristics of silt through laboratory tests or numerical simulations serves as a valuable scientific and theoretical basis for effectively managing the compaction quality of silt subgrades using modern technical approaches. Fathi et al [33] conducted laboratory tests on resilient modulus to ascertain the representative resilient moduli and nonlinear parameters of poorly graded sand with silt extracted from the test sections of the subgrade. Based on a series of triaxial shear tests and mercury injection tests, Ren et al [31] conducted a study to examine the influence of different sample preparation conditions on the mechanical behaviors and distribution of pore structure in silt.…”

A Machine-Learning Approach for Extracting Modulus of Compacted Unbound Aggregate Base and Subgrade Materials Using Intelligent Compaction Technology

“…Fathi et al [31] proposed different strategies to calibrate numerical models simulating the proof-mapping process by developing adjustment factors to accommodate the differences between the field measurements and the numerical responses obtained from both linear and nonlinear 3-D finite element (FE) models. They incorporated a site-specific calibration process using LWD spot testing to adjust the stiffness conditions of the materials that were evaluated.…”