The spring-in phenomenon of the composite parts can affect the assembly process. This study aims to predict the spring-in phenomenon of carbon fiber reinforced plastic (CFRP) part. Here, we predict the spring-in of the CFRP part using a coupled analysis of the forming and cooling processes during the stamping process. First, a simulation of the entire forming process, such as the transfer of the composite laminate, gravity analysis, and forming was performed to obtain the temperature distribution of the CFRP part. Subsequently, a finite-element (FE) simulation of the cooling process was conducted to predict the spring-in phenomenon of the shaped CFRP part using the temperature data obtained in the forming simulation. Finally, a CFRP part was manufactured and compared with the results of the FE simulation.

A programmable DC power supply with Real-time Digital Simulator (RTDS)-based photovoltaic (PV) Power Hardware-In-the-Loop (PHIL) simulators have been used to improve the control algorithm and reliability of PV Inverter. This paper proposes a supervisory control algorithm for PV PHIL simulator with non-RTDS device that is an alternative solution of high cost PHIL simulator. However, when such a simulator with conventional algorithm which is used in RTDS is connected to a PV inverter, the output is in the transient state and it makes it impossible to evaluate the performance of the PV Inverter. Therefore proposed algorithm controls the voltage and current target values according to the constant voltage (CV) and constant current (CC) modes to overcome the limitation of the Computing Unit, DC power supply and also uses a multi-rate system to account for the characteristics of each component of simulator. A mathematical models of a PV system, programmable DC power supply, isolated DC measurement device and Computing Unit are integrated to form a real-time processing simulator. Performance tests using a PV PHIL simulator which is applied proposed algorithm connected a PV inverter are carried out and proved superiority and utility of this method against conventional methods.

Many studies on flexible strain and pressure sensors have been reported due to growing interest in wearable devices for healthcare. However, most are fabricated with multiple ingredients and complicated methods even though commercial textiles, such as cotton, nylon, polyester, and silk were used. Here we present flexible pressure and strain (motion) sensors prepared with only graphene oxide (GO) and commercial silk fabrics and yarns. The pressure sensors were fabricated by simply dipping the silk fabric into GO solution followed by thermal treatment at 400 °C for reduction of GO (rGO). The pressure sensors were made from rGO-coated fabrics, which were stacked in 3-, 5-, and 7-layers. The super-sensitivity of 2.58 ×103 kPa-1 at low pressure was observed in the 7-layer pressure sensor. The strain sensors were obtained from rGO-coated twisted silk yarns whose gauge factor was 0.307. Although this value is small or comparable to other sensors, it is appropriate for motion sensing. The results of this study show a cost-effective and simple method for the fabrication of pressure and motion sensors with commercial silk and GO.

This study investigated the impact of boron and copper on the microstructure and mechanical properties of Spheroidal graphite Cast Iron (SCI). The addition of boron increased the ferrite content, while copper increased the stability of pearlite. The interaction between boron and copper significantly increased the ferrite content. Differential Scanning Calorimetry (DSC) revealed that boron decreased the enthalpy change of the α + Fe3C -> γ transformation and increased the enthalpy change of the α -> γ transformation. The addition of boron and copper reduced the tensile and yield strength but increased elongation and impact energy. The findings provide valuable insights into the effect of boron and copper on SCI, facilitating the design and development of high-performance SCI materials.