Journal of Research in Multidisciplinary Methods and Applications

Study on the Carbon Footprint of Photovoltaic Modules Based on the Life Cycle Assessment

Chunxiao Kou — 2025-02-15

With the global enhancement of environmental protection awareness and adjustments to the energy structure, solar energy, as a clean and renewable form of energy, is increasingly prominent. Photovoltaic (PV) modules, as the core components of solar power generation systems, have garnered significant attention with regard to their carbon footprint during production and usage, which is a key indicator for measuring environmental impact and sustainability. In the context of the global active promotion of climate governance and strengthening carbon regulation, China, as an important exporter of photovoltaic modules in the world, carries out carbon footprint work and deeply taps the carbon reduction potential of products, which has become the only way to promote the high-quality development of the photovoltaic industry. This paper aims to explore the research progress, influencing factors, and strategies for reducing the carbon footprint of PV modules through the study of relevant project cases, providing references for the sustainable development of the photovoltaic industry.

DB-YOLO: An Improved YOLOV8 Model Based on The Second Backbone for Small Defects on PCB Surface

Jun Liu — 2025-02-15

This study introduces the DB-YOLO method, targeting the existing PCB defect detection algorithms, which struggle to identify minor flaws in intricate, small-scale layouts with comparable backdrops, to enhance detection precision. Initially, the deepening of the network layer will lead to a large number of loss of detailed features of the detection target. Although the significant features of the target can be retained, this loss will make the information of the small target incomplete in the small target detection task. Therefore, we combined CBLinear and CBFuse modules in SOTAYOLOv9 to design the second backbone. By redistributing information at different levels, the micro features in the original information are strengthened, and the communication between channels is increased at the same time, which effectively improves the richness of feature information.; next, in order to shorten the forward propagation process and retain the original information to extract the features of small defects in the structure, we use partial convolution to design a new module named CSPC, which reduces the waste of computer resources caused by feature map redundancy. Furthermore, a refined version of the inverted residual multiscale attention module (iREMA) was introduced to augment the representation of features. In conclusion, our comparison of the DB-YOLO model with other current models reveals through experiments that our suggested model surpasses them, enhancing the mAP in the validation set by 3.6% relative to YOLOv8n.

The Numerical Solution of Fractional Convection-Diffusion Problems Using a Second-Order Finite Volume Method

Ning Wang — 2025-02-15

The time second-order characteristic finite volume method is proposed for solving the one-dimensional Riemann-Liouville space fractional convection-diffusion equation. To be specific, by employing the Euler-Lagrange integration approach, the fractional convection-diffusion equation is transformed into a parabolic-like equation, simplifying its numerical treatment. To achieve a high level of time accuracy, the second-order Runge-Kutta method is applied to solve the characteristic line equation, while the Crank-Nicholson implicit scheme is employed to handle the discretized equations efficiently. Furthermore, the parabolic-like equation is discretized utilizing piecewise linear finite elements to ensure the spatial accuracy. Then, a detailed analysis of the coefficient matrix for iterative equation reveals favorable numerical properties that enhance the stability and convergence of the proposed scheme. Numerical examples are given to verify the convergence order of our scheme is O(h^(l+alpha)) in space step and O(tao^2) in time step. The results demonstrate the potential of the proposed method as a powerful and effective tool for solving complex fractional convection-diffusion problems in scientific and engineering applications.