Surface Characteristics of Low Carbon Steel JIS G3101 SS400 after Sandblasting Process by Steel Grit G25

This research aims to study the surface characteristics of low carbon steel JIS G3101 SS400 processed by sandblasting using steel grit G25. The sandblasting process is conducted at a fixed nozzle pressure of 5 bar and pressure angle of 90o, and varying nozzle-to-surface distances at 15, 25, and 30 cm, and blasting durations of 25, 45, and 120 s. Surface characterization is firstly carried out by conducting observation on the surface’s morphology by SEM and chemical composition by EDS. Subsequently, visual inspection and measurement on surface roughness and hardness profile identification by Rockwell and micro-Vickers hardness tests are conducted. A paint thickness test using ASTM D7091 was undertaken to observe the surface characteristics related to the coating process. Based on the result, SEM found valleys, granules, micro-cracks, and grits embedded on the surface. The visual inspection shows the roughness is within the range of Sa2 - Sa3 of ISO 8501 with values are Ra 18.1 and Ra 21.4 µm. The hardened layer exhibits a maximum hardness value of 332 HV and a depth of more than 50 µm by sandblasting parameters of 15 cm distance and 120 s duration. Both roughness and hardness profiles are confirmed, increasing with closer nozzle-to-surface distance and longer blast duration. It is concluded that sandblasting using steel grit G25 is effective in improving the mechanical strength and surface hardness of low carbon steel SS400. These mechanical properties are essential in the paint coating of machinery applications such as pump, tank, ship, and pipeline.

Development of a Numerical Model to Simulate Laser-Shock Paint Stripping on Aluminum Substrates

An explicit 3D Finite Element (FE) model was developed in the LS-Dyna code to simulate the laser shock paint stripping on aircraft aluminum substrates. The main objective of the model is to explain the physical mechanisms of the laser shock stripping process in terms of shock wave propagation, stress and strain evolution and stripping shape and size and to evaluate the effects of laser and material parameters on the stripping pattern. To simulate the behavior of aluminum, the Johnson–Cook plasticity model and the Gruneisen equation of state were applied. To simulate stripping, the cohesive zone modeling method was applied. The FE model was compared successfully against experiments in terms of back-face velocity profiles. The parameters considered in the study are the aluminum thickness, the epoxy paint thickness, the laser spot diameter, the fracture toughness of the aluminum/epoxy interface and the maximum applied pressure. In all cases, a circular solid or hollow stripping pattern was predicted, which agrees with the experimental findings. All parameters were found to affect the stripping pattern. The numerical results could be used for the design of selective laser shock stripping tests.

Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network

An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based on the limited experimental observations. The prediction accuracy of the trained ANN was evaluated by using a metric, mean absolute percentage error. The ANN predicted pressure sensitivity to luminophore content and to paint thickness, within confidence intervals based on experimental errors. The present approach of applying ANN and the data augmentation has the potential to predict pressure-sensitive paint (PSP) characterizations that improve the performance of PSP for global surface pressure measurements.

Aplikasi Disain Komposit Pusat Pada Proses Pengecatan Mobil Bekas

The business of buying and selling used cars is increasingly substantial in Indonesia, in the era of globalization progressively developing depends on demands a process that must be fast, precise, and economical. Repair to body, chassis, and engine are competency expertise in the field of Automotive Engineering that emphasizes automotive repair service skills. at now selling price of used cars, it is necessary to do repairs, the process of repairing used cars or better known as refurbishment work pre-owned cars is mostly done by small-scale used car buying and selling businesses. In order for used cars to return to their like-new condition, generally small-scale used car sellers carry out the process of repairing the vehicle themselves, especially repairs to the vehicle's body paint. This study aims to process of painting a Toyota Avanza car bodypaint against the thickness of the paint using a spray booth tool by using the model of central composite design (CCD). The effect of spray-on booth temperature, interstice size of the spray gun, and time according to the thickness of the paint will be analyzed using the CCD method. This spray booth painting technology is expected to help reduce bodypaint lead time. The results of the ANOVA (Analysis of Variance) regression analysis, the temperature of the spray booth, interstice size of the spray gun, and time are the factors that most significantly affect the thickness of the paint. The operating conditions to produce optimal paint thickness are temperature 55oC, interstice size of spray gun of 1.7 mm and time of painting and drying of 30 minutes, the resulted of a thickness of the paint for used and new cars are 130.2 μm and 81.84 μm., with a coefficient of determination for used and new cars of 90.78% and 96.19%.

Safe and Sustainable Design of Composite Smart Poles for Wireless Technologies

The multiplicity of targets of the 5G and further future technologies, set by the modern societies and industry, lacks the establishment of design methods for the highly multidisciplinary application of wireless platforms for small cells. Constraints are set by the overall energy concept, structural safety and sustainability. Various Smart poles and Light poles exist but it is challenging to define the design drivers especially for a composite load-carrying structure. In this study, the design drivers of a composite 5G smart pole are determined and the connecting design between finite element modelling (FEM), signal penetration and computational fluid dynamics (CFD) for thermal analysis are reported as an interdisciplinary process. The results emphasize the significant effects of thermal loading on the material selection. The physical architecture, including various cutouts, is manipulated by the needs of the mmW radios, structural safety and the societal preferences of sustainable city planning, i.e., heat management and aesthetic reasons. Finally, the paint thickness and paint type must be optimized due to radome-integrated radios. In the future, sustainability regulations and realized business models will define the cost-structure and the response by customers.