Ice-Structure Interaction Analysis: Inverse Ice Force Prediction for Stiffened Plate and Dynamic Simulation

Offshore regions of the Arctic and the Great Lakes hold valuable resources in many respects for harvesting energy and serving as important shipping lanes. Ice loading poses a threat to structures in these regions with high local pressure and various failure modes. It is thus essential to evaluate the ice peak loadings using limited and site-specific data. This thesis aims to better predict the peak ice loading by developing an efficient inverse ice loading prediction methodology and accurate stiffened plate analysis for marine structure design. Additionally, the behavior of the ice-structure interaction is studied mathematically to understand the cyclic dynamic ice-loading applied on offshore structures during continuous ice crushing. Multiple inverse algorithms are presented for calculating the variable ice pressure acting on a stiffened steel plate. The analytical models are formulated to calculate the quasi-static pressure caused by contact of lake ice driven primarily by thermal expansion and winds. Loading pressures are calculated using strain measurements from a stiffened plate installed on a Keweenaw Peninsula lighthouse in Lake Superior. The ice sheet was essentially stationary through the winter months. The linear relationships between pressure and strain values are obtained by both strip beam theory and orthotropic plate theory. The inverse solutions are by nature not necessarily unique. Two inverse approaches using orthotropic plate theory show results with satisfying accuracy and efficiency compared to the finite element analysis. In addition, laboratory calibration and an examination using the recorded data from field measurements exhibit the effectiveness of the presented approach. Continuous ice brittle crushing occurs in the movement of an ice sheet against an offshore structure. Matlock’s ice-structure interaction model is used to simulate the behavior of the ice crushing by modeling ice teeth indentation contacting a spring-mass-dashpot structure. The dynamic behavior of the model is studied using Fourier analysis to predict the response of specific periodicity. The time histories of tooth deflections are expressed through non-linear dynamic equations. The kinematic initial conditions can be predicted at targeted periodicity via the Fourier analysis. Given a representative offshore wind tower system, the first mode shape of the physical system is calculated as input for the ice-structure interaction model as an extended validation. The amplitudes of the structural dynamic vibrations predicted by the analytical model at specific periodicity are compared to the mathematical numerical simulations. A discrete energy method is applied to accurately calculate the deformation of either unidirectional or cross-gridded stiffened panels. This approach obtains the strain energy of the plate and stiffeners using double Fourier series for the displacement fields. Two models are described assuming different reference planes. The first model presumes that the reference planes are located at the effective centroids which are calculated from the cross-sectional properties. The second model formulates the in-plane displacement fields at the mid-plane of the plate. The plate is simply supported along all four edges at the effective centroids for the first model, and at the mid-plane of the plate for the second model. Both methods accurately capture the deformations between stiffeners and the second model eliminates the complicated calculation for effective breadth which is an unavoidable effort for stiffened plate analysis using conventional orthotropic plate theory. The methods presented provide efficient design tools and can be applied to light weight structural design in various fields.PHDNaval Architecture & Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146006/1/yuxiz_1.pd

A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI

Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging techniques available for clinical applications. However, the rather slow speed of MRI acquisitions limits the patient throughput and potential indi cations. Compressive Sensing (CS) has proven to be an efficient technique for accelerating MRI acquisition. The most widely used CS-MRI model, founded on the premise of reconstructing an image from an incompletely filled k-space, leads to an ill-posed inverse problem. In the past years, lots of efforts have been made to efficiently optimize the CS-MRI model. Inspired by deep learning techniques, some preliminary works have tried to incorporate deep architectures into CS-MRI process. Unfortunately, the convergence issues (due to the experience-based networks) and the robustness (i.e., lack real-world noise modeling) of these deeply trained optimization methods are still missing. In this work, we develop a new paradigm to integrate designed numerical solvers and the data-driven architectures for CS-MRI. By introducing an optimal condition checking mechanism, we can successfully prove the convergence of our established deep CS-MRI optimization scheme. Furthermore, we explicitly formulate the Rician noise distributions within our framework and obtain an extended CS-MRI network to handle the real-world nosies in the MRI process. Extensive experimental results verify that the proposed paradigm outperforms the existing state-of-the-art techniques both in reconstruction accuracy and efficiency as well as robustness to noises in real scene

How Chinese social media sentiment about COVID changed during 2020

Chinese social media sentiment about the pandemic fluctuated during 2020. Yan Wang and Yuxi Zhang (LSE-Fudan Global Public Policy Hub) use platform data to analyse how these waves of sentiment emerged and shifted, and look at the case of Chengdu Girl, a woman who caught COVID in December of that year

The surprising impact of COVID-19 on domestic healthcare migration in China

During the COVID-19 pandemic, China adopted one of the world’s most restrictive policies on human mobility. Though largely effective at controlling the pandemic’s spread, these policies also created new pressures for ‘healthcare migrants’, citizens who need to travel to access better medical care within the country

Investigation on the Influence of Concrete Pores on Steel Corrosion Process

Concrete pores on the steel/concrete interface have a great influence on the corrosion process of steel bars. The effects of these pores on the corrosion of steel bars are observed and explored in this paper. The specimens which are in the same size and concrete proportion but have a different curing and exposure history are compared and investigated. This paper mainly observes the process of corrosion products filling into macro pores (10-4-10-2m in diameter) which including compaction pores (10-3-10-2m in diameter) and air voids (10-4-10-3 m in diameter). These pores have different effect on the steel corrosion process, and these influences in both natural environment and artificial environment are discussed in this paper

Experimental investigation on shear strengthening of corroded reinforced concrete columns by pet fibers with large fracturing strain

The seismic strengthening of the concrete columns improperly designed or constructed is in an urgent need. There has been an enormous interest in the research and application of conventional fiber reinforced polymers (FRPs) in RC column seismic retrofitting. However, due to low fracturing strain capacity of conventional FRPs, the fiber materials tend to fail sooner due to fiber breakage. New fiber materials such as polyacetal fiber (PAF), polyethylene naphthalate (PEN) and polyethylene terephthalate (PET) have properties of large fracturing strain and low stiffness in comparison to aramid, carbon, and glass fibers. In this paper, an experimental study is presented on the influence of PET warping on shear capacity, ductility and energy absorptivity of RC columns with stirrup corrosion before strengthening. The experimental program involved an electrochemical process to accelerate the migration of chlorides from an external electrolyte into the tested columns, a wetting–drying cycle process with a controlled current to speed up the corrosion of the stirrup in the tested columns, the strengthening of corroded columns with PET warping, and a Pseudo static test to determine the shear capacity of the tested beams. The shear performance of PET wrapped RC columns with different corrosion levels in stirrups, including the yield strength, the peak strength, the ductility ratio and the energy dissipation ability was examined and the related mechanism was discussed