Yu Guo

Dr. Yu Guo

Northeastern University, China

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 August 2022 in Mathematics
Verified
Journal Article
Open access
PDF file
YGYu Guo
Yu Guo
MLMinghe Liu
Minghe Liu
YMYin Mingang
Yin Mingang
YYYutao Yan
Yutao Yan
As a vital component of electronic products, the quality of the printed circuit board (PCB) assembly directly affects the applications and service life. During the reflow soldering process, the PCB assembly may suffer excessive warpage. Therefore, in order to avoid such a failure, this paper conducts the finite element simulation of the PCB assembly temperature change and the deformation process according to a theoretical model for heat transfer and then explores the causes of warpage and predicts the percentage of warpage that occurs during the reflow soldering. A reliability sensitivity analysis is creatively applied in the PCB assembly warpage study in order to uncover the quantitative influence of multiple factors with random errors on warpage. Moreover, the reliability calculation provides a theoretical basis for the allowable error range of geometric dimensions, material properties and process parameters of the PCB assembly. This research has a remarkable significance and is valuable to engineering in promoting quality and reliability, and increasing the yield of PCB assembly in mass production.

11 September 2023 in Mathematics
Verified
Journal Article
Open access
PDF file
YMYin Mingang
Yin Mingang
MYMing Yan
Ming Yan
YGYu Guo
Yu Guo
MLMinghe Liu
Minghe Liu
This paper presents a queuing system model that incorporates multiple priorities, multiple abandonments, and heterogeneous servers. Waiting for service easily leads to impatient behaviors. The impact of two kinds of impatient behaviors, balking and reneging, on queueing system performance is examined. The problem is formulated as continuous-time Markov chains. It also introduces a special state called the non-sojourn state to record the number of customers who abandon the system. The state transition rate matrix is transformed into a block tridiagonal matrix by appropriately setting the state numbers. A novel indicator called interstate transition frequency is proposed, which aids in distinguishing state transitions during the system evaluation process. Based on the interstate transition frequency, a set of indicators is derived to offer additional analytical perspectives for the queuing system. Finally, the proposed model is applied to an automobile repair shop to validate its effectiveness in practical scenarios.

2 September 2020 in Metals
Verified
Journal Article
Open access
PDF file
YGYu Guo
Yu Guo
MLMinghe Liu
Minghe Liu
YMYin Mingang
Yin Mingang
YYYutao Yan
Yutao Yan
Grind-hardening processing is an emerging approach that combines the grinding and surface quenching process. During the process, the hardened layer—mainly martensite—is produced on the surface of the workpiece to achieve the purpose of surface strengthening. Above all, the surface temperature field of the hypoeutectoid-1045 steel workpiece was determined by finite element method for fully revealing the formation mechanism of the hardened layer. Further, the cellular automata approach was applied to dynamically simulate the transformation of both austenitization and martensitization from the initial microstructure. The hardness penetration depth was also predicted. Finally, a grind-hardening experiment was conducted to assess the theoretical study. Results showed that a combination of the finite element method and the cellular automata approach can effectively simulate the microstructure transformation of hardened layer. The microstructure and the hardness penetration depth were affected by the maximum grinding temperature and the heating rate. Research on the influence of grinding parameters showed that the hardness penetration depth increased as the depth of the wheel cut and feeding speed increased. Experiments revealed that the difference between predicted value and experimental value of the hardness penetration depth varied between 2.83% and 7.31%, which confirmed the effectiveness of the predicted model.

28 September 2021 in Materials
Verified
Journal Article
Open access
PDF file
YGYu Guo
Yu Guo
MLMinghe Liu
Minghe Liu
YYYutao Yan
Yutao Yan
As an emerging composite processing technology, the grind-hardening process implements efficient removal on workpiece materials and surface strengthening by the effective utilization of grinding heat. The strengthening effect of grind-hardening on a workpiece surface is principally achieved by a hardened layer, which is chiefly composed of martensite. As a primary parameter to evaluate the strengthening effect, the hardness of the hardened layer mostly depends on the surface microstructure of the workpiece. On this basis, this paper integrated the finite element (FE) and cellular automata (CA) approach to explore the distribution and variation of the grinding temperature of the workpiece surface in a grind-hardening process. Moreover, the simulation of the transformation process of “initial microstructure–austenite–martensite” for the workpiece helps determine the martensite fraction and then predict the hardness of the hardened layer with different grinding parameters. Finally, the effectiveness of the hardness prediction is confirmed by the grind-hardening experiment. Both the theoretical analysis and experiment results show that the variation in the grinding temperature will cause the formation to a certain depth of a hardened layer on the workpiece surface in the grind-hardening process. Actually, the martensite fraction determines the hardness of the hardened layer. As the grinding depth and feeding speed increase, the martensite fraction grows, which results in an increase in its hardness value.