Search Results

Abstract Transient temperature analysis is involved in the thermal simulation of the heat treatment process, in which the hot metal temperature changes with respect to time from an initial state to the final state. The critical part of the simulation is to determine the heat transfer coefficient (HTC) between the hot part and the quenching medium or quenchant. In liquid quenching, the heat transfer between the hot metal part and water becomes complicated and it is difficult to determine HTC. In the current experimentation a medium carbon steel EN 9 rod with a diameter of 50 mm and length 100 mm was quenched in water and ethylene glycol mixture with different concentrations. A part model was created; meshed and actual boundary conditions were applied to conduct computational fluid dynamics (CFD) analysis. In order to validate CFD analysis the experimental trials were conducted.

Abstract AISI H13 hot work tool steel is commonly used for applications such as hot forging and hot extrusion in mechanical working operations that face thermal and mechanical stress fluctuations, leading to premature failures. Cryogenic treatment was applied for AISI H13 steel to improve the surface hardness and thereby fatigue resistance. This work involves failure analysis of H13 steel specimens subjected to cryogenic treatment and gas nitriding. The specimens were heated to 1020°C, oil quenched followed by double tempering at 550°C for 2 h, and subsequently, deep cryogenically treated at −185°C in the cryochamber. Gas nitriding was carried out for 24 h at 500°C for 200 μm case depth in NH3 surroundings. The specimens were subjected to rotating bending fatigue at constant amplitude loading at room temperature.

Abstract This study aims to explore the wear characteristics of fused deposition modeling (FDM) printed automotive parts and techniques to improve wear performance. The surface roughness of the parts printed from this widely used additive manufacturing technology requires more attention to reduce surface roughness further and subsequently the mechanical strength of the printed geometries. The main aspect of this study is to examine the effect of process parameters and annealing on the surface roughness and the wear rate of FDM printed acrylonitrile butadiene styrene (ABS) parts to diminish the issue mentioned above. American Society for Testing and Materials (ASTM) G99 specified test specimens were fabricated for the investigations. The parameters considered in this study were nozzle temperature, infill density, printing velocity, and top/bottom pattern.

Abstract The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

Abstract In this study, we have investigated the microstructural characteristics, the mechanical properties, and the dry sliding wear behavior of a ceramic coating consisting of zirconia (ZrO2) and alumina (Al2O3) deposited by flame spraying. A series of wear tests were carried out under a variety of loads and at two different sliding speeds. The evaluation included an examination of the coating microstructure, microhardness, coefficient of friction (COF), and wear resistance of the flame-sprayed coating. The results showed that the coatings had a perfectly structured micro-architecture and were metallurgically bonded to the substrate. The Al2O3 coating exhibited a fine granular structure with pores and oxides. The microstructure of Al2O3-10 wt.% ZrO2, on the other hand, showed a blocky structure with a uniform distribution of ZrO2 inclusions in the composite coating.

Abstract With the use of the stepped surface of the friction pairs of the stepped bearings (SB) in the high-speed centrifugal pumps, its liquid film thickness is suddenly changed and it was discontinuously distributed in the direction of motion of pump. To ensure the continuity of the liquid film thickness and enhance the lubrication efficiency of the pump, based on the lubrication model of the SB, two other structures of the inclined surfaces [inclined bearings (IB)] and curved surfaces [curved bearings (CB)] used to replace stepped surfaces of the SB are investigated, respectively. Under the same conditions of the minimum thickness of the liquid film and initial dimensions of the sliding friction pairs, the influence of both the thickness ratio (α) of the liquid film and dimension ratio (β) in the direction of motion of SB, IB, and CB on the bearing capacity and friction coefficient of the liquid film are simulated and analyzed, respectively.

Abstract Low-carbon equivalent austempered ductile iron (LCE-ADI) exhibits high modulus of elasticity than conventional austempered ductile iron (ADI) due to less graphite content. Austempering parameters of temperature and time significantly influence the mechanical properties of LCE-ADI. In the present work, response of the material to two-step austempering in the range of 350–450°C was studied, and a comparison was made to single-step austempering. Reduction in ferrite cell size, increase in % carbon in carbon-stabilized austenite (CSA) and increase in volume fraction of CSA led to increase in tensile strength (10%) and hardness (20%), in addition to improved toughness (10%).

Abstract Neutron diffraction is a powerful tool for noninvasive and nondestructive characterization of materials and can be applied even in large devices such as internal combustion engines thanks to neutrons’ exceptional ability to penetrate many materials. While proof-of-concept experiments have shown the ability to measure spatially and temporally resolved lattice strains in a small aluminum engine on a timescale of minutes over a limited spatial region, extending this capability to timescales on the order of a crank angle degree over the full volume of the combustion chamber requires careful design and optimization of the engine structure to minimize attenuation of the incident and diffracted neutrons to maximize count rates.

Abstract In this article, the effect of heat treatment on the microstructure and mechanical behavior of medium-carbon steel wire intended for the spring mattress is investigated using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), X-ray diffraction, Vickers hardness (Hv), and tensile strength. The results indicate that the microstructure elongation along the wire axis is observed with the bending and kinking lamellae at the deformation level of 57.81%, this change appears as a fracture in the microstructure and leads to an increase in hardness, tensile strength, and intensities of diffraction patterns. After heat treatment, we observed a redistribution in the grain, which is almost the same in the wire rod and drawn wires; indeed, this led to a decrease in hardness, tensile strength, and augmentation in intensities of peaks. The EBSD pole figures reveal the development of texture in the cementite slip plane (001).

Abstract The development of predictive maintenance has become one of the most important drivers of innovation, not only in the maritime industry. The proliferation of on-board and remote sensing and diagnostic systems is creating many new opportunities to reduce maintenance costs and increase operational stability. By predicting impending system faults and failures, proactive maintenance can be initiated to prevent loss of seaworthiness or operability. The motivation of this study is to optimize predictive maintenance in the maritime industry by determining the minimum useful remaining lead-acid battery capacity measurement frequency required to achieve cost-efficiency and desired prognostic performance in a remaining battery capacity indication system. The research seeks to balance operational stability and cost-effectiveness, providing valuable insight into the practical considerations and potential benefits of predictive maintenance.

Abstract This article addresses the design, testing, and evaluation of rigorous and verifiable prognostic and health management (PHM) functions applied to autonomous aircraft systems. These PHM functions—many deployed as algorithms—are integrated into a holistic framework for integrity management of aircraft components and systems that are subject to both operational degradation and incipient failure modes. The designer of a comprehensive and verifiable prognostics system is faced with significant challenges. Data (both baseline and faulted) that are correlated, time stamped, and appropriately sampled are not always readily available. Quantifying uncertainty, and its propagation and management, which are inherent in prognosis, can be difficult. High-fidelity modeling of critical components/systems can consume precious resources. Data mining tools for feature extraction and selection are not easy to develop and maintain.

Abstract Prediction of the surface finish of hardened bearing steels was estimated in machining with ceramic uncoated cutting tools under various process parameters using two statistical approaches. A second-order (quadratic) regression model (MQR, multiple quantile regression) for the surface finish was developed and then compared with the artificial neural network (ANN) method based on the coefficient determination (R 2), root mean square error (RMSE), and percentage error (PE). The experimental results exhibited that cutting speed was the dominant parameter, but feed rate and depth of cut were insignificant in terms of the Pareto chart and analysis of variance (ANOVA). The optimum surface finish in machining bearing steel was achieved at 100 m/min speed, 0.1 mm/revolution (rev) feed rate, and 0.6 mm depth of cut.

Abstract The present investigation has been conducted to study the tribological and adhesion properties of X10CrNi18-8 austenitic stainless steel (ASTM 301) coatings deposited on aluminum alloys such as AU4G by using the arc-spraying process. These coatings were made with and without a bond-coat layer, which is constituted by NiAl. The structure of the phases that are present in coatings was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The measurements of microhardness and tribological behavior at different loads were also performed on the surface of the coatings. Adherence test was also carried out using four-point bending tests. The SEM showed that the dense microstructures of coatings have a homogeneous lamellar morphology with the presence of porosities and unmelted particles. The main phase of coating corresponds to a solid solution as a face-centered cubic (fcc).

Abstract In the current research, an aluminum alloy AA8090 is welded using the friction stir welding (FSW) technique. The main objective is to eliminate the chances of defects in the weld joint, which were observed in the conventional joining process. Experiments were planned according to the one factor at a time (OFAT) approach. The input process parameters involved during the present work are welding speed (WS), rotational speed (RS), tilt angle (TA), and dwell time (DT). However, the response variables investigated at different input parametric combinations are tensile strength (TS), percentage elongation (EL), microhardness (MH), and macroscopic structure. Due to the combination of both attributes of optimization (the higher the better in TS and the lower the better in EL), the multi-performance quality characteristics optimization approach, i.e., grey relational analysis (GRA), is implemented.

Abstract A novel method of measuring the thickness of deposits on engine pistons, including within ring grooves, is described. A laser profilometer is used in conjunction with a rotary stage to measure a continuous profile of the piston with deposits, and the measurement is repeated after cleaning the deposits from the piston. Algorithms for aligning the scans and determining the differential thickness are described, and results are compared to deposit thickness measurements using a contact-type magnetic induction coating thickness gauge. This method allows continuous measurement of deposit thickness across the entire surface including lands and ring grooves as well as quantification of the volume of the deposits.

Abstract This article primarily focuses on studying and analyzing the effect of machining parameters, viz., pulse on time (TON), pulse off time (TOFF), and pulse current (Ip) on machining performance in terms of surface roughness (Ra) and material removal rate (MRR) during electrical discharge machining (EDM) of alloy tool steel (SKD11 steel). The traditional trial-and-error methods used to derive empirical relationship and optimize the process is time consuming and results in reduced productivity, high rejection, and cost. The response surface methodology (RSM) approach of design of experiment technique was applied for designing the experiments. The influences of EDM parameters on Ra and MRR were investigated using different graphs. The mathematical model equations for Ra and MRR were generated. The optimum parametric combinations for smaller Ra (highest surface finish) and highest MRR were found, and the optimized values of Ra and MRR were obtained.

Abstract Reducing the friction of the internal combustion engine (ICE) is of major interest to reduce fuel consumption and greenhouse gas (GHG) emissions. A huge potential for friction reduction is seen in the piston ring-cylinder liner (PRCL) coupling. Approaching the cylindrical liner shape in the hot operation state will enhance the PRCL conformation. Recently, newly developed freeform honing techniques can help to achieve this perfect cylinder shape. This article presents a numerical study of the effect of freeform honing on the geometrical performance of the liner in the hot operation state. The freeform honed liner (TR) concept is based on the approach of reversing the local deformation of a conventional circular liner. A validated computational model for a gasoline engine is used to compare the geometrical performance of those TR cases with circular, elliptical (EL), and conical elliptical liners (NEL) at different operational points.

Abstract This article reports a reduced-order modeling framework of bladed disks on a rotating shaft to simulate the vibration signature of faults in different components, aiming toward simulated data-driven machine learning. We have employed lumped and one-dimensional analytical models of the subcomponents for better insight into the complex dynamic response. The framework addresses some of the challenges encountered in analyzing and optimizing fault detection and identification schemes for health monitoring of aeroengines and other rotating machinery. We model the bladed disks and shafts by combining lumped elements and one-dimensional finite elements, leading to a coupled system. The simulation results are in good agreement with previously published data. We model and analyze the cracks in a blade with their effective reduced stiffness approximation.

Abstract Laminated composites are extensively used in the aerospace industry. However, structures made from laminated composites are highly susceptible to delamination failures. It is therefore imperative to consider a structure tolerance to delamination during design and operation. Hybrid composites with laminas containing different fibers were used earlier in laminates to achieve certain benefits in strength, stiffness, and buckling. However, the concept of mixing laminas with different fibers was not explored by researchers to enhance delamination tolerance levels. This article examines the above aspect of hybridization by employing machine learning algorithms and proposes a reliable method of analysis to study delamination, which is crucial to ensure the safety of airframe composite panels.

Abstract Statistical machine learning classification methods have been widely used in the fault detection analysis in several engineering domains. This motivates us to provide in this article an overview on the application of these methods in the fault diagnosis strategies and also their successful use in unmanned aerial vehicles (UAVs) systems. Different existing aspects including the implementation conditions, offline design, and online computation algorithms as well as computation complexity and detection time are discussed in detail. Evaluation and validation of these aspects have been ensured by a simple demonstration of the basic classification methods and neural network techniques in solving the fault detection and diagnosis problem of the propulsion system failure of a multirotor UAV. A testing platform of an Hexarotor UAV is completely realized.