scholarly journals The Development of Fine Surface Roughness of FeCrAl Substrate by Gamma Alumina Coating Material Through Nickel Oxide Catalyst

2021 ◽  
Vol 2 (2) ◽  
pp. 70-75
Author(s):  
Dafit Feriyanto ◽  
S.S. Abdulmalik ◽  
Hadi Pranoto ◽  
Supaat Zakaria
Keyword(s):  
Surface Roughness ◽  
Interfacial Adhesion ◽  
Oxide Catalyst ◽  
Catalytic Converter ◽  
Organic Coating ◽  
Alumina Coating ◽  
Adhesion Forces ◽  
Fine Surface ◽  
Coating Methods ◽  
The Stability

The most commonly used method for protecting atmospherically exposed steel against corrosion, is the application of protective organic coating systems. It is widely recognized that the stability of the coating-substrate interface is related to the interfacial adhesion forces and electrochemical properties of this region. This study aim to develop fine surface roughness by ultrasonic and electroplating coating methods that applied for FeCrAl catalytic converter. This method consists of thwo methods which are ultrasonic bath that carried out by frequency of 35 kHz and various ultrasonic times of 1, 1.5, 2, 2.5 and 3 hours is imposed and the electroplating was conducted for several variation times of 15, 30, 45, 60 and 75 minutes, current density of 8 A/dm2. The result shows that the surface roughness of UB samples in between 0.11 to 0.21 µm, UBdEL samples of 0.81 to 2.17 µm, UB+EL samples of 0.64 to 1.63 µm and EL samples of 0.69 to 1.11 µm. The finest surface of each techniques are located at UB 1.5 h, UBdEL 45 minutes, UB 1.5 h+EL 30 minutes and UB 30 minutes. That data is supported by coating thickness of coated FeCrAl substrate where UB samples in between 2 -2.8 µm, UBdEL samples of 4.1 to 5 µm, UB+EL samples of 9.1 to 12 µm and EL samples of 6.2 to 11.3 µm.

Research on chatter stability in milling and parameter optimization based on process damping

2017 ◽  
Vol 24 (12) ◽  
pp. 2642-2655 ◽  
Author(s):  
Lida Zhu ◽  
Baoguang Liu ◽  
Hongyu Chen
Keyword(s):  
Surface Roughness ◽  
Frequency Method ◽  
Processing Efficiency ◽  
Machined Surface ◽  
Process Damping ◽  
Analysis Methodology ◽  
Optimization Of Process Parameters ◽  
Orthogonal Experiments ◽  
Cutting Chatter ◽  
The Stability

Cutting stability is the prerequisite to ensure efficient and high-precision machining, resulting in poor surface quality and damaged tool, which is the basis for the optimization of process parameters and improvement of processing efficiency. Aiming at process damping caused by interference between a tool flank face and a machined surface of part, the dynamic model and critical condition of stability is proposed in the paper. The frequency method is applied to solve the stability of the cutting chatter, and the correctness of the model is validated by experiments. Moreover, through orthogonal experiments, regression analysis methodology are adopted to establish a prediction model of surface roughness and finally combined with the study findings on milling stability based on process damping and surface roughness, achieved optimization of the milling parameters by genetic optimization algorithm. This conclusion provides a theoretical foundation and reference for the milling mechanism research.

Interfacial Versus Cohesive Failure on Polymer-Metal Interfaces in Electronic Packaging—Effects of Interface Roughness

2002 ◽  
Vol 124 (2) ◽  
pp. 127-134 ◽  
Author(s):  
Qizhou Yao ◽  
Jianmin Qu
Keyword(s):  
Surface Roughness ◽  
Fracture Mechanics ◽  
Electronic Packaging ◽  
Interfacial Adhesion ◽  
Interfacial Strength ◽  
Interface Roughness ◽  
Cohesive Failure ◽  
Mechanics Model ◽  
Polymer Metal ◽  
Metal Interfaces

Debonding of polymer-metal interfaces often involves both interfacial and cohesive failure. Since the cohesive strength of polymers is usually much greater than the polymer-metal interfacial strength, cohesive failure near the interface is usually desired for enhancing the interfacial adhesion. Roughened surfaces generally produce more cohesive failure; therefore, they are used commonly in practice to obtain better adhesion. This paper develops a fracture mechanics model that can be used to quantitatively predict the amount of cohesive failure once the surface roughness data are given. An epoxy/Al interface was investigated using this fracture mechanics model. The predicted amount of cohesive failure as a function of surface roughness compares very well with the experimentally measured values. It is believed that this model can be extended to other polymer–metal interfaces. Contributed by the Electronic and Photonic Packaging Division for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received by the EPPD.

Adhesion and Pull-Off Forces for Polysilicon MEMS Surfaces Using the Sub-Boundary Lubrication Model

2002 ◽  
Vol 125 (1) ◽  
pp. 193-199 ◽  
Author(s):  
Allison Y. Suh ◽  
Andreas A. Polycarpou
Keyword(s):  
Surface Roughness ◽  
Boundary Lubrication ◽  
Intermolecular Forces ◽  
Contact Forces ◽  
Root Mean Square Roughness ◽  
Magnetic Storage ◽  
Smooth Surfaces ◽  
Adhesion Forces ◽  
Disk Interface ◽  
Adhesion Model

Miniature devices including MEMS and the head disk interface in magnetic storage often include very smooth surfaces, typically having root-mean-square roughness, σ of the order of 10 nm or less. When such smooth surfaces contact, or come into proximity of each other, either in dry or wet environments, then strong intermolecular (adhesive) forces may arise. Such strong intermolecular forces may result in unacceptable and possibly catastrophic adhesion, stiction, friction and wear. In the present paper, a model termed sub-boundary lubrication (SBL) adhesion model is used to calculate the adhesion forces, and an elastic-plastic model is used to calculate the contact forces at typical MEMS interfaces. Several levels of surface roughness are investigated representing polished and as-deposited polysilicon films that are typically found in MEMS. The SBL adhesion model reveals the significance of the surface roughness on the adhesion and pull-off forces as the surfaces become smoother. The validity of using the SBL adhesion model to estimate the pull-off forces in miniature systems is further supported by direct comparison with experimental pull-off force measurements performed on silicon and gold interfaces. Finally, the significance of the interfacial forces as relate to the reliability of MEMS interfaces is discussed.

A Kinetic Investigation of Triacetin Methanolysis and Assessment of the Stability of a Sulfated Zirconium Oxide Catalyst

2018 ◽  
Vol 95 (7) ◽  
pp. 865-874 ◽  
Author(s):  
Rafael L. Temóteo ◽  
Marcio J. da Silva ◽  
Fabio de Ávila Rodrigues ◽  
Wagner F. da Silva ◽  
Deusanilde de Jesus Silva ◽  
...  
Keyword(s):  
Zirconium Oxide ◽  
Oxide Catalyst ◽  
Kinetic Investigation ◽  
The Stability

scholarly journals Adhesion force mapping on wood by atomic force microscopy: influence of surface roughness and tip geometry

2016 ◽  
Vol 3 (10) ◽  
pp. 160248 ◽  
Author(s):  
X. Jin ◽  
B. Kasal
Keyword(s):  
Surface Roughness ◽  
Atomic Force Microscopy ◽  
Wood Surface ◽  
Adhesion Force ◽  
Data Interpretation ◽  
Natural Fibre ◽  
Force Distribution ◽  
Adhesion Forces ◽  
Force Microscopy ◽  
Atomic Force

This study attempts to address the interpretation of atomic force microscopy (AFM) adhesion force measurements conducted on the heterogeneous rough surface of wood and natural fibre materials. The influences of wood surface roughness, tip geometry and wear on the adhesion force distribution are examined by cyclic measurements conducted on wood surface under dry inert conditions. It was found that both the variation of tip and surface roughness of wood can widen the distribution of adhesion forces, which are essential for data interpretation. When a common Si AFM tip with nanometre size is used, the influence of tip wear can be significant. Therefore, control experiments should take the sequence of measurements into consideration, e.g. repeated experiments with used tip. In comparison, colloidal tips provide highly reproducible results. Similar average values but different distributions are shown for the adhesion measured on two major components of wood surface (cell wall and lumen). Evidence supports the hypothesis that the difference of the adhesion force distribution on these two locations was mainly induced by their surface roughness.

Effect of Surface Roughness and Joint Material on Torque-Tension Relationship in Threaded Fasteners

2005 ◽  
Author(s):  
S. A. Nassar ◽  
T. S. Sun
Keyword(s):  
Surface Roughness ◽  
Load Level ◽  
Friction Torque ◽  
Joint Surface ◽  
Specific Level ◽  
Tightening Torque ◽  
Safety And Reliability ◽  
The Stability ◽  
Engineering Practices ◽  
Effect Of Surface

An experimental study is presented in order to investigate the effect of surface roughness on the torque-tension relationship in bolted assemblies. Three levels of surface roughness are considered for the fastener underhead and the joint surface; namely, low, medium, and high levels of surface roughness. The study is conducted for two joint materials, two fastener classes, and for coarse and fine threads. In this study, the torque-tension data is expressed in terms of the value of the nut factor as well as its scatter. The effect of the number of tightenings on surface roughness and on the torque-tension relationship is investigated as well. The surface roughness is measured before tightening, and after each loosening using a WYKO optical profiling system. An M12 fastener is used in this study. Both fine and coarse threads and fastener material Classes 8.8 and 10.9 for M12 fasteners are used in this study. The torque-tension data is analyzed for both steel and aluminum joints. The safety and reliability of bolted assemblies are mainly determined by the level and the stability of the clamp load provided by the initial tightening of the threaded fastener. The value of initial clamp load, which is achieved by a specific level of tightening torque, is highly sensitive to the friction torque components. This study provides an insight into the reliability of the existing engineering practices for estimating the clamp load level from the tightening torque. Hence, the findings of the study would help enhance the reliability and the safety of bolted assemblies, especially in critical applications.

Experimental Investigation for the Multi-objective Optimization of Machining Parameters on AISI D2 Steel Using Particle Swarm Optimization Coupled with Artificial Neural Network

2020 ◽  
Vol 19 (03) ◽  
pp. 589-606 ◽  
Author(s):  
Vipin Gopan ◽  
K. Leo Dev Wins ◽  
Gecil Evangeline ◽  
Arun Surendran
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Cutting Force ◽  
Surface Finish ◽  
Fitness Function ◽  
Machining Parameters ◽  
Swarm Optimization ◽  
Fine Surface ◽  
Aisi D2

High Carbon High Chromium (or AISI D2) Steels, owing to the fine surface finish they produce upon grinding, find lot of applications in die casting. Machining parameters affect the surface finish significantly during the grinding operation. In this context, this work puts an effort to arrive at the optimum machining parameters relating to fine surface finish with minimum cutting force. The material removal caused by the abrasive grinding wheel makes the process a very complex and nonlinear machining operation. In many situations, traditional optimization techniques fail to provide realistic optimum conditions because of the associated complexity. In order to overcome this issue, particle swarm optimization (PSO) coupled with artificial neural network (ANN) is applied in this research work for parameter optimization with the objective of achieving minimum surface roughness and cutting force. The machining parameters selected for the investigation were table speed, cross feed and depth of cut and the responses were surface roughness and cutting force. ANNs, inspired from biological neural networks, are well capable of providing patterns, which are too complex in behavior. The ANN model developed was used as the fitness function for PSO to complete the optimization. Optimization was also carried out using conventional response surface methodology-genetic algorithm (RSM-GA) approach in which regression equation developed with RSM was considered as the fitness function for GA. Confirmatory experiments were conducted and the comparison showed that PSO coupled with ANN is a reliable tool for complex optimization problems.

scholarly journals Computational neuroscience applied in surface roughness fiber optic sensor

2019 ◽  
Vol 10 (1) ◽  
pp. 70-75 ◽  
Author(s):  
Wei He
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Computational Neuroscience ◽  
Fiber Optic ◽  
Rbf Neural Network ◽  
Fiber Optic Sensor ◽  
Bottom Surface ◽  
Optic Sensor ◽  
Arbitrary Precision ◽  
The Stability

Abstract Computational neuroscience has been widely used in fiber optic sensor signal output. This paper introduces a method for processing the Surface Roughness Fiber Optic Sensor output signals with a radial basis function neural network. The output signal of the sensor and the laser intensity signal as the light source are added to the input of the RBF neural network at the same time, and with the ability of the RBF neural network to approach the non-linear function with arbitrary precision, to achieve the nonlinear compensation of the sensor and reduction of the effect of changes in laser output light intensity at the same time. The Surface Roughness Fiber Optic Sensor adopting this method has low requirements on the stability of the output power of laser, featuring large measuring range, high accuracy, good repeatability, measuring of special surfaces such as minor area, and the bottom surface of holed etc. The measurements were given and various factors that affect the measurement were analyzed and discussed.

Development and Rheological Characterisation of Abrasive Flow Finishing Medium for Finishing Macro to Micro Features

2020 ◽  
Vol 70 (2) ◽  
pp. 190-196
Author(s):  
Sachin Singh ◽  
M. Ravi Sankar
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Recast Layer ◽  
Technological Advancement ◽  
Minimal Cost ◽  
Finishing Process ◽  
Fine Surface ◽  
Micro Features ◽  
Finishing Processes ◽  
Abrasive Flow Finishing

Technological advancement demands the manufacturing of components with a fine surface finish at a minimal cost. This scenario acts as the driving force for the research communities to develop economic finishing processes. Abrasive flow finishing (AFF) is one of the advanced finishing processes employed for finishing, deburring, radiusing and recast layer removal from the workpiece surfaces. AFF process uses a finishing medium that acts as a deformable tool during the finishing process. It is the rheological properties of the medium that profoundly influences the end surface finish obtained on the workpiece after the AFF process. In the current work, an attempt is made to develop an economic AFF medium by using viscoelastic polymers i.e., soft styrene and soft silicone polymer. Detailed static and dynamic characterisation of the medium is carried out. Later, to study the finishing performance of the developed medium, AFF experiments are performed for the finishing of macro and micro feature components. The experimental study showed that the nano surface finish could be achieved by varying the viscosity of the developed medium. Developed medium achieved 89.06 per cent improvement in surface roughness during finishing of tubes (macro feature component), while 92.13 per cent and 88.11 per cent surface roughness improvement is achieved during finishing of microslots and microholes (micro feature component), respectively.

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