Wire and arc additive manufacturing (WAAM) is a competitive technique, which enables the fabrication of medium and large metallic components. However, due to the presence of coarse columnar grains in the additively manufactured parts, the resultant mechanical properties will be reduced, which limits the application of WAAM processes in the engineering fields. Grain refinement and improved mechanical properties can be achieved by introducing ultrasonic vibration. Herein, we applied ultrasonic vibration to the WAAM process and investigated the effects of wire feed speed, welding speed, and ultrasonic amplitude on the weld formation and grain size during ultrasonic vibration. Finally, a regression model between the average grain size and wire feed speed, welding speed, and ultrasonic amplitude was established. The results showed that due to the difference in heat input and cladding amount, wire feed speed, welding speed, and ultrasonic amplitude have a significant influence on the weld width and reinforcement. Excessive ultrasonic amplitude could cause the weld to crack during spreading. The average grain size increased with increasing wire feed speed and decreasing welding speed. With increasing ultrasonic amplitude, the average grain size exhibited a trend of decreasing first and then increasing. This would be helpful to manufacture parts of the required grain size in ultrasonic vibration-assisted WAAM fields.

Purpose: Complicated workpiece, such as an engine block, has special rough locating datum features (i.e. six independent datum features) due to its complex structure. This locating datum error cannot be handled by current variation propagation model based on differential motion vectors. To extend variation prediction fields, this paper aims to solve the unaddressed variation sources to modify current model for multistage machining processes. Design/methodology/approach: To overcome the limitation of current variation propagation model based on differential motion vectors caused by the unaddressed variation sources, this paper will extend the current model by handling the unaddressed datum-induced variation and its corresponding fixture variation. Findings: The measurement results of the rear face with respect to the rough datum W and the pan face with respect to the hole Q by coordinate measuring machine (CMM) are −0.006 mm and 0.031 mm. The variation results for rear face and pan face predicted by the modified model are −0.009 mm and 0.025 mm, respectively. The discrepancy of model prediction and measurement is very small. Originality/value: This paper modifies the variation propagation model based on differential motion vectors by solving the unaddressed variation sources, which can extend the variation prediction fields for some complicated workpiece and is useful in the future work for many fields, such as process monitoring, fault diagnosis, quality-assured setup planning and process-oriented tolerancing.

Addressing the leakage rate prediction problem of the PEMFC sealing system is of great importance for its stable operation. The leakage calculation method of the PEMFC sealing system is proposed based on thermal coupling. The parallel plate leakage model is improved to make it applicable to the leakage rate calculation with a variable channel cross-section height. The interface macroscopic contact pressure is solved using a finite element simulation for solid mechanics analysis. The Greenwood–Williamson model is used for contact mechanics analysis to solve for the average height of the leakage channel. The effects of the ambient temperature, compression ratio, bipolar plate misalignment, and gasket size on the cell sealing effect were studied numerically. The data indicated that as the ambient temperature, compression ratio, and gasket size became larger, the volume leakage rate began to be reduced. The leakage rate as a parameter to characterize the sealing performance, considering the influence of gasket size, operating conditions, and other factors on the cell sealing effect, is more meaningful for the durability study and failure analysis of PEMFC.

The sealing technology of proton exchange membrane fuel cells (PEMFCs) is a critical factor in ensuring their performance, impacting driving safety and range efficiency. To guarantee the safe operation of PEMFCs in complex environments, it is essential to conduct related sealing research. The structure of the fuel cell sealing system is complex, with components in close contact, and identifying factors that affect its sealing performance is crucial for the development and application of the cells. This paper briefly describes the sealing mechanism of PEMFCs and introduces four typical sealing structures. It considers both the assembly and operation processes, summarizing assembly errors, sealing gaskets, and sealing leaks as well as vibration, cyclic temperature and humidity, and cyclic assembly. The research status of the sealing system in simulations and experiments is reviewed in detail. The key factors affecting the sealing performance of fuel cells are emphasized, highlighting the significance of dynamic detection of the gasket status, stack performance improvement under cumulative errors, and multi-objective optimization models combining contact pressure with the characteristics of stack components.

Variation prediction and quality control for complex-shaped workpieces in automotive and aerospace fields with multi-stage machining processes have drawn significant attention because of the widespread application and increasing diversity of these kinds of workpieces. To finish the final workpieces with complex shapes, multiple setups and operations are often applied in machining processes. However, sources of geometric error, such as fixture error, datum error, machine tool path error, and the dimensional quality of the product, interact complicatedly at different stages. These complex interactions pose significant challenges to final product error prediction and reduction. Manufacturing error prediction based on stream of variation is an effective way to control the machining quality. However, there are few integrated models that can describe the interactions among types of geometric error sources from different stages for different kinds of complex workpieces. This paper proposes a modified error prediction model to systematically capture the interactions of different error sources among different operations for complex-shaped workpieces in multi-stage machining processes. Using differential motion vectors, the connection of all key variations from machine, fixture, and workpiece is established. This modified model can not only handle general fixture layouts for complex workpieces, but also introduce machining-induced variations. Based on this model, the main error sources identification method and error compensation method are proposed. In order to evaluate the effectiveness of the proposed method, engine blocks are used to be machined as an example. Compared with a machining process without a compensating strategy, the average machining error of the key feature is reduced by 80.5% after compensating for the main error sources.

The controlled short-circuit transfer is used to control the heat input of the molten pool and the base metal in the cold metal transfer welding process, including droplet formation, droplet transfer and molten pool flow. Based on the influence of arc pressure on the surface of the molten pool, droplet impact and residual energy on the flow behavior of the molten pool, this research proposes the arc pressure driving model, the droplet impact driving model and the residual energy transfer model on the molten pool surface respectively, and on this basis, a theoretical model of controlled driving and spreading of the cold metal transition bath is proposed. The theoretical relationship between the surface shape of the keyhole and the driving force, and the relationship between the surface shape of the molten pool and the welding current are established. The model accurately predicts the formation width and contact angle of the molten pool in a specific interval, which can better control the welding process and geometry.