Unknown Soil Parameters Research Articles

Prediction of SPT Value Based on Cone Penetration Test at Intake Water Project of Wolo River, Southeast Sulawesi

Soil investigation plays an important role in construction design. Adequate information regarding soil types and parameters are needed for a safe and economical foundation. However, limited budget often leads to inadequate soil investigations, and as a result, unknown soil parameters are estimated through correlations from the limited investigations that have been carried out. Correlations from SPT and CPT results are often used for design, but their applicability from location to location is questionable. This paper discusses the correlation of N-SPT values to CPT values in Wolo District, Kolaka Regency. The correlation was performed using linear regression analysis to obtain relationships between N-SPT and CPT. The three correlations obtained are N-SPT = 5.64 + 0.012qc, R2 value of 0.082; N-SPT = 5.93 + 0.01 qc – 0.095qf, R2 value of 0.125; N-SPT = 0.025qc + 0.341qf, R2 value of 0.455.

Robust design of monopiles for offshore wind turbines considering uncertainties in dynamic loads and soil parameters

Complex marine environment causes significant variations in the dynamic loads and soil parameters that affect the design of a monopile. Despite these uncertainties, a multi-objective optimization technique is developed to produce the optimal designs. This optimization is based on the robust design concept, in which the design robustness, cost, and safety are considered as the optimal objectives. The responses of a monopile to arbitrary dynamic loads are initially determined using a transient finite element technique, which considers unknown soil parameters. These responses include the maximum rotation and displacement at the midline, maximum axial stress, and fatigue damage. Next, the variations (regarding standard deviations) in these responses, which are determined by the Monte–Carlo simulations, are adopted to define the design robustness. Finally, the cost and safety requirements of the monopile are evaluated, and robust design optimization is performed. The aforementioned robust design protocols are demonstrated with a 5 MW offshore wind turbine, which produces the optimal design. Therefore, the optimal designs for the monopile are investigated based on various safety requirements. Moreover, the design parameters that promote the design robustness with optimum efficiency are studied and proposed.

Tractive Force Prediction for Unmanned Ground Vehicles in Rough Terrain

Unmanned ground vehicles traversing rough terrain can be applied in a wide range of industries, such as agriculture, defence, mining, space exploration and construction. The interaction dynamics between the vehicle and the terrain play a crucial role in determining the mobility characteristics of the vehicle. The two critical parameters that influence the interaction dynamics are the wheel/track slip and the unknown soil parameters. A method for estimating vehicle slip parameters based on an optical flow algorithm and a sliding mode observer is presented. A tractive force prediction algorithm based on the soil and slip information is developed to predict the traversability of the vehicle. The proposed algorithms are tested and evaluated using test rigs and mobile robots, and the test results are demonstrated in the paper.

Hybrid Soil Parameter Measurement and Estimation Scheme for Excavation Automation

Real-time measurement and estimation of soil-tool interaction dynamics are key tools for the development of automated excavation systems. Automating a complex operation such as excavation is a challenging task that strongly hinges on a good estimate of soil properties as well as the interaction forces between the excavator tool and the environment. This paper presents a method for identifying all the unknown soil parameters (density, tool-soil friction angle, soil-soil friction angle, and cohesion) required for predicting the interaction forces in real time using a novel hybrid soil model. The hybrid model consists of the Mohr-Coulomb (M-C) soil model and the Chen and Liu upper bound (CLUB) soil model. A switching mode is utilized to select the most appropriate soil model to compute the failure forces that depend on the position of the excavator bucket. The Newton-Raphson method (NRM) is adapted and is used to identify the soil parameters by minimizing the error between the measured forces and the forces computed by the hybrid soil model. The experimental results presented demonstrate that the proposed estimation scheme is accurate when compared to measured soil parameters. The Newton-Raphson estimation method is applied iteratively to efficiently and robustly identify the parameters. The conducted comparative study shows that the proposed method is a promising way for the on-line soil-tool interaction force identification of an automated excavator in dynamic and potentially hazardous environments, outperforming other estimation methods including the least squares method (LSM).

The modelling and estimation of driving forces for unmanned ground vehicles in outdoor terrain

Ground vehicles traversing rough unknown terrain has many applications in a range of industries including agriculture, defence, mining, space exploration and construction. The interaction dynamics between the vehicle and the terrain play a crucial role in determining the mobility characteristics of the vehicle. The two critical parameters that influence the interaction dynamics are the wheel/track slip and the unknown soil parameters. An algorithm for identifying unknown soil parameters based on a dynamic model and sensor feedback is presented. A method for estimating vehicle slip parameters based on an optical flow algorithm and a sliding mode observer is also presented. The last section addresses the traversability prediction for tracked vehicles traversing in circular trajectories. The algorithms are developed for both tracked and wheeled vehicles. The algorithms are tested and evaluated using two specially designed test rigs, and the test results are presented in the paper.

Soil Parameter Identification and Driving Force Prediction for Wheel-Terrain Interaction

This paper considers wheeled vehicles traversing unknown terrain, and proposes an approach for identifying the unknown soil parameters required for vehicle driving force prediction (drawbar pull prediction). The predicted drawbar pull can potentially be employed for traversability prediction, traction control, and trajectory following which, in turn, improve overall performance of off-road wheeled vehicles. The proposed algorithm uses an approximated form of the wheel-terrain interaction model and the Generalized Newton Raphson method to identify terrain parameters in real-time. With few measurements of wheel slip, i, vehicle sinkage, z, and drawbar pull, DP, samples, the algorithm is capable of identifying all the soil parameters required to predict vehicle driving forces over an entire range of wheel slip. The algorithm is validated with experimental data from a wheel-terrain interaction test rig. The identified soil parameters are used to predict the drawbar pull with good accuracy. The technique presented in this paper can be applied to any vehicle with rigid wheels or deformable wheels with relatively high inflation pressure, to predict driving forces in unknown environments.

TRAVERSABILITY PREDICTION FOR UNMANNED GROUND VEHICLES BASED ON IDENTIFIED SOIL PARAMETERS

A novel technique for identifying soil parameters on-line while traversing with a tracked vehicle on unknown terrain is presented. This technique, based on the Newton Raphson method is used to identify unknown soil parameters. Comparing with the Least Square method, it shows that the Newton Raphson method is better in terms of prediction accuracy, computational speed, and robustness to initial conditions and noise. For heavy tracked vehicle, cohesion has negligible effect on the vehicle performance. These identified soil parameters are then employed for traversability prediction for a tracked vehicle travelling on unknown terrain.

Back-Analysis of Deformation and Mohr-Coulomb Strength Parameters Based on Initial Strain Method

This note proposes a numerical procedure in which both deformation modulus and Mohr- Coulomb strength parameters are back-calculated from a load-displacement response monitored in the field. The back-analysis of nonlinear constitutive parameters contains the difficulty that most nonlinear constitutive models employ stress as the fundamental variable to govern the change in deformation modulus and to specify the yield criterion, and that the stress is little sensitive to the change in deformation modulus. This difficulty is easily solved by applying the initial strain method for nonlinear stress-strain analysis, because the stress calculated by the method does not directly depend on the tangent modulus of rigidity. By combining a hyperbolic stress-strain equation, FEM based on the initial strain method and mathematical programming technique, the procedure allows to correct unknown soil parameters until the difference between calculated and monitored load-displacement curves decreases sufficiently. The proposed procedure is applied to some hypothetical case studies of in-situ testing and its validity is verified. The result indicates an important role of the initial stresses within subsoil, because the effects of friction angle and cohesion can be evaluated separately, only when the confining pressure exceeds a certain value.

Estimation of Nonlinear Constitutive Parameters Based on Monitored Movement of Subsoil Under Consolidation

Described is a numerical procedure to back-analyze the nonlinear constitutive parameters and permeability from the monitored movements of subsoil under two-dimensional consolidation. The difficulty in the back-analysis of nonlinear constitutive parameters lies on the fact that most of the nonlinear constitutive models employ the stress as the fundamental variable to govern the change in the deformation moduli and to specify the yield criterion, and that the stress is little sensitive to the change in deformation moduli. At first, the authors devise a simplified hyperbolic stress-strain model in which the shear strain is the variable controlling the decrease in deformation modulus and in which the shear strength is not related to the confining pressure. The unknown soil parameters to be back-analyzed are the initial tangent moduli of rigidity, the shear strengths and the permeabilities in multiple soil layers. By combining FEM and mathematical programming technique, the procedure allows to correct the unknown soil parameters until the differences between calculated and measured quantities decrease sufficiently. The proposed procedure is verified by calibrating the performance of the procedure being applied to hypothetical case studies. Subsequently the procedure is applied to actual case studies and comparisons are made with the results obtained by assuming the linear elastic behaviour of soil deposit. By applying the proposed procedure of back-analysis to the observational procedure in construction phase, one can get the rough estimate of shear strength at each time stage of construction.

Microflora distributions in quaternary paleosols on Mount Kenya, East Africa

When numbers of microorganisms in profiles of ground and buried soils on Mount Kenya were estimated by plate counting they were found to be consistently lower than those observed for other soils in different geographical regions. Numbers declined successively in deeper horizons and no evidence was obtained of irregular patterns of distribution controlled by soil forming processes, as observed frequently in certain Mollisols and Spodosols. The lower numbers and patterns of vertical distribution appear characteristic of younger Inceptisols and Entisols usually found in the alpine zone, and older Alfisols located in the Bamboo Forest region of Mount Kenya. The A horizons of the soils studied contain proportionately fewer of the total number of organisms in the A, B and C horizons than are observed in most soils. Estimates of organic matter suggest that this may be limiting since profile TV4a, with the highest counts, also had the highest organic matter content. However, extreme climatic conditions, such as severe drought and diurnal frosts, or unknown soil parameters, may also regulate the numbers of micro- and macroorganisms. Organic and inorganic horizons of buried soils often exhibit higher counts of micro-organisms than adjacent horizons of ground soils. However, bacteria and fungi do not appear to differ qualitatively from those in surface horizons. Taken in conjunction with other evidence obtained from the profiles we conclude that they are not indigenous, but introduced by root systems, or by upward movement of the water table contaminated with microorganisms. This appears to provide a means of determining which buried horizons are likely to be contaminated by biogeochemical processes, thus possibly affecting their radiocarbon ages.

Estimation of Soil Parameters Based on Monitored Movement of Subsoil under Consolidation

This paper presents a numerical procedure in which the soil parameters affecting the two dimensional consolidation are back-calculated from the data monitored in the field. By using a combination of finite element method and mathematical programming technique, the procedure allows to seek the unknown soil parameters which minimize the differences between calculated and measured quantities. Young's modulus, Poisson's ratio, and permeability coefficient in multiple soil layers are the soil parameters determined by the procedure. The validity of the proposed procedure is verified by calibrating the performance of the procedure being applied to hypothetical case studies. The applications to practical projects provide the interesting results such as the changing trend of soil parameter values during consolidation process. By applying the procedure at the early stage of consolidation, one may be able to predict the future settlements with a good accuracy.