Advances in Mechanical and Materials Engineering

The Influence of Plasma Nitriding Process Conditions on the Microstructure of Coatings Obtained on the Substrate of Selected Tool Steels

Fri, 05 Jan 2024 00:00:00 +0000

This study presents the results of research into the influence of the time of the plasma nitriding process on the microstructure of the coatings obtained. Cold-work tool steels (60WCrV8, 90MnCrV8, 145Cr6), hot-work tool steel (X37CrMoV5-1) and high-speed tool steel (HS6-5-2) were selected as substrate material. The processes were carried out under industrial conditions using an Ionit device from Oerlikon Metaplas with variable process times of 2, 4 and 6 hours. According to literature data, a nitriding mixture consisting of 5% nitrogen and 95% hydrogen was chosen, which allowed the expected diffusion layer to be obtained without a white layer (composed of iron nitrides). Analysis of elemental mapping indicates that the presence and content of nitride-forming elements influences the formation of alloy additive nitrides in the microstructure of the diffusion layer. It was also found that an increase in the duration of plasma nitriding, results in an increase in the depth of the nitrided layers formed on the substrate of high-alloy steels: X37CrMoV5-1 and HS6-5-2. Nitrides of alloying additives, present in the diffusion layer, are formed in the high-alloyed the hot-work steel X37CrMoV5-1, indicating that these steels are the most suitable for plasma nitriding of the entire tool steels analysed.

Analysis of the Thermal Expansion Coefficient of Glass- and Carbon-Fibre-Reinforced Composites

Romuald Fejkiel, Krystian Skwara — Fri, 12 Jan 2024 07:41:36 +0000

With the development of manufacturing processes, an increase in the importance of metal-fibre composites in materials engineering is observed. These are materials consisting of appropriately arranged layers of metal and various types of fibres. The very wide use of composite materials in the construction of machine and equipment components means they are often exposed to work in variable temperature conditions. The aim of this article was analysis of the thermal expansion of typical composites: carbon fibre-reinforced polymer, glass fibre-reinforced polymer, glass-reinforced aluminium laminate and carbon-fibre reinforced aluminium laminate. EN AW-6060 aluminium alloy was used as the reference material. The aim of the dilatometric tests was to determine the coefficient of thermal expansion and the dimensional stability of composite materials at elevated temperatures up to 100 °C. The EN AW-6060 aluminium alloy was characterized by the highest linear expansion coefficient (20.27×10⁻⁶1/K). Composites containing glass fibres were characterized by the lowest positive linear thermal expansion coefficient. Among the composite materials tested, CARALLs exhibit the lowest thermal expansion coefficient.

Effect of Floating-Plug Drawing Process Parameters on Surface Finish of Inner and Outer Surfaces of AISI 321 Stainless Steel Thin-Walled Tubes

Krzysztof Żaba, Marcin Szpunar — Mon, 29 Jan 2024 08:18:07 +0000

This article presents the results of the analysis of changes in the surface topography of AISI 321 (1.4541) thin-walled stainless steel tubes in single-pass Floating-Plug Drawing (FPD) process. Experimental tests were carried out with variable drawing speed (1, 2, 3, 4, 6, and 10 m/min) and different angles of floating plug (11.3°, 13° and 14°). Wisura DSO7010 (Fuchs Oil) lubricant was used in the experiments. Mean roughness Ra and ten point height of irregularities Rz were adopted as surface quality indicators. Roughness parameters were measured independently on the inner and outer surfaces of thin-walled tubes. Analysis of variance was used to analyse the relationship between process parameters (drawing speed and angle of floating plug) and surface roughness of tubes. A decrease in the values of both analyzed roughness parameters was observed as a result of the drawing process. The FPD process significantly improves the inner surface quality of AISI 321 thin-walled stainless steel tubes. The mean roughness value tends to increase with increasing drawing speed, while the angle of the floating-plug has no significant effect on the mean roughness Ra.

The Impact of Particle Size in Fluidized Bed on Heat Transfer Behavior: A Review

Ahmed Hammood Darweesh, Musa Mustafa Weis — Wed, 21 Feb 2024 08:08:05 +0000

This review paper explores the significance of fluidized bed heat exchangers in various industrial applications. By delving into the operation of fluidized beds as multiphase flow systems, the aim is to enhance their capabilities and efficiency. Key parameters such as minimum fluidization velocity and local gas holdup are crucial for characterizing the hydrodynamic behavior of materials within fluidized beds. Fluidization, achieved by passing atmospheric air through particulate solids, imparts fluid-like properties to the bed. Fluidized beds serve as reactors where this phenomenon takes place, offering several advantages in industrial processes, including high rates of heat and mass transfer, low pressure drops, and uniform temperature distribution. In future work, a focus on understanding and optimizing the fluidization process will contribute to further advancements in the performance of fluidized bed heat exchangers.

Assessment of the Depth of the Plastically Deformed Top Layer in Burnishing Process of Shaft Using a Ceramic Tool

Piotr Paszta, Leszek Chałko, Rafał Kowalik — Tue, 05 Mar 2024 05:40:12 +0000

Burnishing is one of the most effective methods of improving the strength of the surface layer of shafts as a result of strain strengthening of the material. This article presents an analytical approach to determining the the depth of the plastically deformed top layer of shaft based on Belyaev's theory. Contact of two bodies with an asymmetric stress state was assumed. A classic (symmetrical) solution was also considered. The aim of the research was to compare the calculated values of the depth of the plastically deformed top layer determined using these two methods. The calculations considered burnishing of shafts with a diameter of 48 mm made of steel with a yield stress of Re = 450 MPa and Re = 900 MPa. A burnishing tool with a Si3N4 ceramic tip was used for burnishing. It was found that in the range of low contact forces, the calculated values of the depth of the plastically deformed top layer using the asymmetric solution and the classical method are similar. It was also found that the relationship between the depth of the plastically deformed top layer and the contact force can be explained by a power equation with an accuracy of R² > 0.999.

Optimal Airfoil Selection for Small Horizontal Axis Wind Turbine Blades: A Multi-Criteria Approach

Fri, 15 Mar 2024 12:47:18 +0000

Over the last century, the growing demand for clean energy has emphasized wind energy as a promising solu-tion to address contemporary energy challenges. Within the realm of wind energy, the wind turbine plays a pivotal role in harnessing the kinetic energy of the wind and converting it into electrical power. Among the various components of the wind turbine system, turbine blades assume a critical role in capturing the wind's kinetic energy and converting it into rotational motion. Consequently, the design of wind turbine blades holds the utmost importance in determining the overall performance and efficiency of the entire wind turbine system. One essential aspect of blade design involves selecting an appropriate airfoil. Throughout history, numerous airfoil profiles have been developed for various applications. Notably, National Advisory Committee for Aeronautics (NACA) and National Renewable Energy Laboratory (NREL) airfoils have been tailored for aircraft and large-scale wind turbine blades, respectively. However, the quest for suitable airfoil types for small-scale wind turbine blades has been ongoing. This study delves into an examination of over 62 distinct NACA and NREL aerofoil types tailored for small horizontal-axis wind turbine blades. Employing specialized software, namely QBlade, specifically designed for modeling and simulating wind turbine blades, the study calculates key parameters such as power output, stress, deformation, and weight for each airfoil. Subsequently, based on the simulated data, the optimal airfoil is identified using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria selection approach. This selection process takes into account simulation results pertaining to power output, stress, deformation, and weight. The decision-making process involving multiple criteria is facilitated using Excel and Python. The findings of this study reveal that among the 62 airfoil types under consideration, the NACA 0024, NACA 2424, and NACA 4424 airfoils emerge as the most suitable choices for small horizontal-axis wind turbine blades.

Application of Categorical Boosting to Modelling the Friction Behaviour of DC05 Steel Sheets in Strip Drawing Test

Marek Szewczyk, Krzysztof Szwajka, Sherwan Mohammed Najm, Salwa O Mohammed — Fri, 12 Apr 2024 06:39:25 +0000

It is challenging to model the coefficient of friction, surface roughness, and related tribological processes during metal contact because of flattening, ploughing, and adhesion. It is important to choose the appropriate process parameters carefully when creating analytical models to overcome the challenges posed by complexity. This will ensure the production of sheet metal formed components that meets the required quality standards and is free from faults. This research analyses the impacts of nominal pressure, kinematic viscosity of lubricant, and lubricant pressure on the coefficient of friction and average roughness of DC05 deep-drawing steel sheets. The strip drawing test was used to determine the coefficient of friction. This work utilises the Categoric Boosting (CatBoost) machine learning algorithm created by Yandex to estimate the COF and surface roughness, intending to conduct a comprehensive investigation of process parameters. A Shapley decision plot exhibits the coefficient of friction prediction models via cumulative SHapley Additive exPlanations (SHAP) data. CatBoost has outstanding prediction accuracy, as seen by R² values ranging from 0.955 to 0.894 for both the training and testing datasets for the COF, as well as 0.992 to 0.885 for surface roughness.