Experimental Study on Measurement of Drag Coefficient of Sandy Soil Nonlinear Vadose

A porous-media-tuned liquid damper (PMTLD) can serve as an effective and economical dynamic vibration absorber. Placing porous media within a water tank can improve the capacity for energy dissipation and optimize the performance by varying its material properties. Two numerical models are adopted for the simulations of the sloshing problem in PMTLD and the dynamics of a floating platform in waves. The first potential-based approach employs a mixed-type boundary value problem (BVP) solver and a free-surface particle tracker. This approach not only simulates the inviscid water wave but also includes the nonlinear damping effects via a quadratic Forchheimer term for the PMTLD. Another equivalent mechanical model is used to reduce the degree of freedom of the PMTLD system. The Newmark method is embedded to solve the rigid-body dynamics. The second viscous approach uses the finite element method (FEM) to spatially discretize the Navier-Stokes (NS) equations and handles the free surface via the volume of fluid (VOF) and the level set (LS) equations. The multiphase simulation is implemented by a computational modeling toolkit Proteus for the fluid phase and Chrono for the solid phase. The correlations between potential flow and two-phase Navier-Stokes models are presented. The PMTLD is designed by analogy with the tuned mass damper (TMD). Numerical results show that the PMTLD can effectively reduce the structure's dynamic response in terms of vibration amplitude around resonance. Such damping devices have great potential for offshore platforms and wind turbine design.

show abstract

Performance Comparison of Different Particle Size Distribution Models in the Prediction of Soil Particle Size Characteristics

Zhang

Wang

Chen

et al. 2022

Land

View full text Add to dashboard Cite

Particle size distribution (PSD) is a rich source of information about soil properties, including soil gradation and soil particle size characteristics. This paper compared the PSD prediction ability of three types of mathematical model. We selected nine models that have been proven to accurately predict sample points in previous studies, and we fit 144 pieces of experimental data on 12 texture classes of soil samples from the UNSODA database. We compared the models’ capability for predicting non-sample points, which is important for predicting soil particle size characteristics. Each model’s ability to predict non-sample points of different texture classes of soil was studied using a comprehensive ranking method. The relative differences in the models’ prediction of non-sample points of different texture classes of soil were analyzed using the relative error method. The results showed no considerable correlation between the number of model parameters and the prediction accuracy. For the various texture classes of soil, the Skaggs model and Weipeng model had the highest accuracy in predicting non-sample points, and the Skaggs model had the widest range of application. The Zhongling model and the Weibull model were better in predicting only one texture class of soil, respectively. The Fredlund model, Kolve model, Rosin model, Van Genuchten model and Best model were not as successful as other models. The Weipeng model overestimated the solid particle mass proportion, while the Skaggs model underestimated it when the clay particle content was greater than 20%. Both the Weipeng model and the Skaggs model demonstrated good prediction accuracy when the particle size was within the silt particle size range. The Skaggs model overestimated the particle mass proportion, while the Weipeng model underestimated it when the particle size was within the sand particle size range.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Experimental Study on Measurement of Drag Coefficient of Sandy Soil Nonlinear Vadose

Cited by 3 publications

References 5 publications

Hydraulic conductivity estimation of sandy soils: a novel approach

Hydraulic conductivity estimation of sandy soils: a novel approach

Response Mitigation of Floating Platform by Porous-Media-Tuned Liquid Dampers

Performance Comparison of Different Particle Size Distribution Models in the Prediction of Soil Particle Size Characteristics

Contact Info

Product

Resources

About