ABSTRACT
With the significant growth in the production and installation of photovoltaic (PV) systems, the recycling of end-of-life PV modules has become a critical concern. Thermal treatment is a promising approach to decompose all the polymer and separate different layers rapidly. However, the combustion of the backsheet can lead to the release of hazardous fluorinated compounds. This paper proposes a novel method combining low-temperature and thermal treatment to separate different layers in PV modules. This method leverages the back metallization of solar cells for PV module separation, providing a fresh separation perspective. The focus lies on investigating a low-temperature separation process, and the separation interfaces are characterized using SEM and EDS, shedding light on the separation position and physical separation mechanisms. Subsequently, the effects of different freezing temperatures, freezing times, and different laminated parts were investigated, and the processing parameters were optimized. Compared to direct thermal treatment, the proposed process eliminates the generation of hazardous fluorides and mitigates mass losses caused by thermal treatment effectively. This research provides valuable insights into the green and sustainable resource recovery of waste PV modules.
Subject(s)
Electronic Waste , Silicon , Temperature , Silicon/chemistry , Electronic Waste/analysis , Cold Temperature , PolymersABSTRACT
Needle-tissue interaction model is essential to tissue deformation prediction, interaction force analysis and needle path planning system. Traditional FEM based needle-tissue interaction model would encounter mesh distortion or continuous mesh subdivision in dealing with penetration, in which the computational instability and poor accuracy could be introduced. In this work, a novel material point method (MPM) is applied to establish the needle-tissue interaction model which is suitable to handle the discontinuous penetration problem. By integrating a hyperelastic material model, the tissue deformation and interaction force can be solved simultaneously and independently. A testbed of needle insertion into a Polyvinyl alcohol (PVA) hydrogel phantom was constructed to validate both tissue deformation and interaction force. The results showed the experimental data agrees well with the simulation results of the proposed model.
Subject(s)
Mechanical Phenomena , Needles , Computer Simulation , Phantoms, ImagingABSTRACT
Point cloud registration plays a key role in three-dimensional scene reconstruction, and determines the effect of reconstruction. The iterative closest point algorithm is widely used for point cloud registration. To improve the accuracy of point cloud registration and the convergence speed of registration error, point pairs with smaller Euclidean distances are used as the points to be registered, and the depth measurement error model and weight function are analyzed. The measurement error is taken into account in the registration process. The experimental results of different indoor scenes demonstrate that the proposed method effectively improves the registration accuracy and the convergence speed of registration error.
ABSTRACT
Polyvinyl alcohol(PVA)hydrogel was made for simulating human's soft tissue in our experiment.The image acquisition device is composed of an optical platform,a camera and its bracket and a light source.In order to study the law of soft tissue deformation under flexible needle insertion,markers were embedded into the soft tissue and their displacements were recorded.Based on the analysis of displacements of markers in Xdirection and Ydirection,back propagation(BP)neural network was employed to model the displacement of Ydirection for the markers.Compared to the experimental data,fitting degree of the neural network model was above 95%,the maximum relative error for valid data was limited to 30%,and the maximum absolute error was 0.8mm.The BP neural network model was beneficial for predicting soft tissue deformation quantitatively.The results showed that the model could effectively improve the accuracy of flexible needle insertion into soft tissue.
