Search Results (28)

Optimization of process parameters for manufacturing of individual surfaces and the product as a whole is one of the key tasks of technological preparation of production. Processing of individual design elements of the product is a structurally complex process, which is a clear sequence of actions characterized by a set of parameters. The effectiveness of the optimization process directly depends on the level of detail of the process under study and the optimal choice of targets and control parameters. Thus, for a single design element of the product, the control task is reduced to the structural and parametric optimization of its processing. For this purpose, it is necessary to develop a hierarchical model of structural and parametric optimization of the processing of individual design elements of the product. The paper presents a structural hierarchical model of the design element forming process, describing the sequence of actions and intermediate states of the object at different control levels. The model is based on the structural decomposition of the process and includes three levels: technological processing route, technological transition, and working stroke. For each level, theoretical-multiple models, vector optimization criteria, control parameters, and boundary conditions are defined. The article also demonstrates the application of the model on the example of optimization for the process of shaping a group of threaded holes, where the Pareto-optimization method was used to obtain optimal machining parameters that reduced the labor intensity with an acceptable increase in error and surface roughness. The paper presents the results of controlling the machining process of a group of threaded holes by means of structural optimization of the machining process route and parametric optimization of cutting parameters for each working stroke. Optimal parameters of the machining process for the investigated group of threaded holes are achieved by reducing the number of technological transitions within the technological route of machining, as well as optimizing the value of cutting speed set in the process of tapping with a tapsetter. Thus, as a result of the optimization, the total labor intensity of individual transitions decreased by 18.3%, with an increase in processing error by 12.1%, and deterioration of the roughness parameter by 13.2%, which satisfies the initial conditions of optimization. The obtained results prove the effectiveness of the developed hierarchical model of controlling the process of machining individual design elements of the product through structural and parametric optimization of its individual stages. Full article

Shielings are seasonal settlements found in upland pastures across Scandinavia and the North Atlantic. New investigations in the county of Møre and Romsdal, Norway, demonstrate the existence of this transhumant system by the Viking Age and Early Middle Ages. Sub-terranean features in these pastoral mountain landscapes have been identified by remote sensing technologies, but non-invasive methods still face challenges in terms of practical applicability and in confirming the presence of archaeological sites. Generally, aerial surveys, such as LiDAR and image-based modelling, excel in documenting visual landscapes and may enhance detection of low-visibility features. Thermography may also detect shallow subsurface features but is limited by solar conditions and vegetation. Magnetic methods face challenges due to the heterogeneous moraine geology. Ground-penetrating radar has yielded better results but is highly impractical and inefficient in these remote and rough landscapes. Systematic soil coring or test-pitting remain the most reliable options for detecting these faint sites, yet non-invasive methods may offer a better understanding of the archaeological contexts—between the initial survey and the final excavation. Altogether, the study highlights the dependency on landscape, soil, and vegetation, emphasising the need to consider each method’s possibilities and limitations based on site environments and conditions. Full article

The processes of rock excavation and processing involve intense mechanical stresses on cutting, displacing, and transporting tools, inevitably leading to the phenomenon of dry friction wear. The factors influencing the intensity and mechanisms of wear are complex and interdependent, being conditioned by the physical–mechanical properties of the rocks, the geometric characteristics and materials of the tools, as well as the cutting process parameters (cutting force, feed rate). Previous studies have mainly addressed the global aspect of wear without delving into the microstructural evolution of the contact surfaces during the friction process. In this paper, through controlled tribometric tests, we have investigated in detail the abrasive wear mechanisms of metallic materials in contact with different types of rocks, with an emphasis on the role played by surface roughness and the mineralogical properties of the rocks. Experimentally, we varied the applied forces and the number of friction cycles to simulate different working conditions and evaluate how these parameters influence wear intensity and surface morphology evolution. Microstructural analysis of the samples, combined with roughness measurements, allowed the identification of the predominant degradation mechanisms (abrasion, adhesion, fatigue) and their correlation with the material properties and the friction process parameters. The results have shown a strong correlation between the wear capacity of rocks and their petrographic properties, such as hardness, porosity, and hard mineral content. It was also found that the roughness of the contact surfaces plays an essential role in wear mechanisms, influencing both the initiation and propagation of its effects. Depending on the experimental data, we have developed a classification of rocks based on their abrasive potential and proposed criteria for the optimal adoption of materials and working parameters for the tools of technological equipment depending on the type of rock encountered. The results of this study can contribute to improving the durability of tools, as well as mining equipment, and reducing operating costs. Full article

Additive manufacturing of porous materials with a specific macrostructure and tunable mechanical properties is a state-of-the-art area of material science. Additive technologies are widely used in industry due to numerous advantages, including automation, reproducibility, and freedom of design. Selective laser melting (SLM) is one of the advanced techniques among 3D fabrication methods. It is widely used to produce various medical implants and devices including stents. It should be noticed that there is a lack of information on its application in stent production. The paper presents the technological aspects of CoCr stent SLM fabrication, including design of stents and development of regimes for their manufacturing. Physical, chemical, and technological properties of CoCr powder were initially determined. Parametric design of mesh stent models was adopted. A two-stage approach was developed to ensure dimensional accuracy and quality of stents. The first stage involves a development of the single-track fusion process. The second stage includes the stent manufacturing according to determined technological regimes. The single-track fusion process was simulated to assign laser synthesis parameters for stent fabrication. Melting bath temperature and laser regimes providing such conditions were determined. Twenty-seven SLM manufacturing regimes were realized. Dependence of single-tracks width and height on the laser power, exposition time, and point distance was revealed. The qualitative characteristics of tracks imitating the geometry of the stent struts as well as favorable and unfavorable fusion regimes were determined. The results of surface roughness regulating of the stents’ structural elements by various methods were analyzed. Thus, this two-staged approach can be considered as a fundamental approach for CoCr stent SLM fabrication. Full article

The sliding layer created during operation of the expanded graphite–steel combination has had a huge impact on the effectiveness of the friction process, and thus on the sustainable development of society. Knowledge of the factors determining the properties of the sliding layer will make it possible to reduce friction resistance in the future through the proper design and selection of sliding pairs for given applications. This paper studies the effect of the moisture content of expanded graphite on the formation of a sliding layer on a stainless steel surface. The tests were carried out in static contact for 30 s and dynamic contact for 15 and 30 min, for loads of 10, 20, and 30 N and speeds of 25 and 50 mm/s. To determine the changes in surface geometry due to material transfer, the Ra roughness value of the surface of stainless steel samples was measured. In order to realize the purpose of the work and evaluate the effect of moist rings on the resulting sliding layer, the results of the surface roughness of stainless steel samples working with dry and moist graphite rings were compiled. The obtained results show that the presence of water in the stainless steel-expanded graphite friction node affects the formation of a sliding layer. The resulting layer reduces the surface roughness of the cooperating materials and prevents their accelerated wear. After 5 min of work with the water-soaked graphite counter-sample, depending on the applied friction conditions, a reduction in the surface roughness of the stainless steel sample was achieved in the range of 11–18% compared to the initial value. After 30 min of operation, the surface roughness decreased by 3 to 25%. Pilot studies have shown that operating conditions influence the formation of a sliding layer in the stainless steel-expanded graphite tribological contact. This confirms the validity of conducting further research in this area. Full article

Aluminium smelter waste (ASW) is a big contributor to landfills, and its recycling has been of great interest. This study investigates the tribological properties of aluminium matrix syntactic foams manufactured using an Al 6082 alloy and ASW. Ball-on-disc tests were conducted under both dry and lubricated conditions. Under dry sliding conditions, the coefficient of friction (COF) had an initial sharp increase, followed by a gradual decrease and finally a steady state as the sliding distance increased. The wear surfaces showed the presence of adhesive, abrasive and oxidative wear, with some presence of delamination. Syntactic foams containing small ASW particles led to a decrease in surface roughness, decrease in the average COF and decrease in specific wear. Heating large ASW particles before manufacturing the syntactic foams enhanced overall wear properties because the particles are hardened due to a compositional change. The T6 treatment of the syntactic foams enhanced the wear properties due to the hardening of the Al matrix. The average COF of the ASW syntactic foams was higher than that of the E-sphere syntactic foam, which was predominantly abrasive wear. The specific wear of the ASW syntactic foams can be higher or lower than the E-sphere syntactic foam, depending on the ASW particle size. Under lubricated sliding test conditions, the wear was reduced significantly, and the type changed from predominantly adhesive to predominantly abrasive. The porous ASW particles acted as lubricant reservoirs and provided a constant supply of lubricant, further improving the lubrication effect. Full article

The third-body particle-involved sliding contact between two rough rubbers with wavy surfaces is experimentally studied. The experiment is designed to isolate the direct contact between the first bodies so that friction resistance is induced completely by the interactions between the third-body particle and the surfaces of the rubbers. In dry contact of a single particle, it is found that the particle exhibits pure rolling during the sliding of the first bodies, and the macroscopic friction resistance for overcoming sliding does not depend on the particle size, but it is significantly influenced by the initial position of the surface waviness relative to the particle’s position. The behavior of the particle under lubricated conditions exhibited significant differences. Due to the low local friction at the interface, the particle rapidly glided down to the valley of the waviness during compression. This abrupt motion of the particle resulted in it coming to rest in a stable position, awaiting a substantial force to push it forward. The friction resistance in the case with lubrication was found to be independent of the initial position of the waviness, and its value consistently remained at the maximum found in dry contact. Therefore, lubrication actually increases the macroscopic friction resistance. An approximate solution for the specific case of dry contact is proposed to understand the friction behavior. Full article

Welded joints in metallic pipelines and other structures are used to connect metallic structures. Welding defects, such as cracks and lack of fusion, are vulnerable to initiating early-age cracking and corrosion. The present damage identification techniques use ultrasonic-guided wave procedures, which depend on the change in the physical characteristics of waveforms as they propagate to determine damage states. However, the complexity of geometry and material discontinuity (e.g., the roughness of a weldment with or without defects) could lead to complicated wave reflection and scatters, thus increasing the difficulty in the signal processing. Artificial intelligence and machine learning exhibit their capability for data fusion, including processing signals originally from ultrasonic-guided waves. This study aims to utilize deep learning approaches, including a convolutional neural network (CNN), Long-short term memory network (LSTM), or hybrid CNN-LSTM model, to demonstrate the capability in automation for damage detection for pipes with welded joints embedded in soil. The damage features in terms of welding defect types and severity as well as multiple defects are used to understand the effectiveness of the hybrid CNN-LSTM model, which is further compared to the two commonly used deep learning approaches, CNN and LSTM. The results showed the hybrid CNN-LSTM model has much higher classification accuracy for damage states under all scenarios in comparison with the CNN and LSTM models. Furthermore, the impacts of the pipelines embedded in different types of materials, ranging from loose sand to stiff soil, on signal processing and data classification were further calibrated. The results demonstrated these deep learning approaches can still perform well to detect various pipeline damage under varying embedment conditions. However, the results demonstrate when concrete is used as an embedding material, high attention to absorbing the signal energy of concrete could pose a challenge for the signal processing, particularly under high noise levels. Full article

Nucleation is the initial phase transition process when nuclei of a new phase form within an undercooled or supersaturated parent phase under appropriate conditions. Nucleation most often occurs through a heterogeneous process on active centers on which the probability of nucleus formation is high. In general, the origin of active centers may be difficult to distinguish. In this work, we consider the formation of crystalline nuclei in a melt on various curved substrates. Knowledge of excess free energy plays a key role in understanding the process of formation of clusters and it is not easy to express this quantity in a considered system. Excess free energy is often approximated within the framework of capillarity approximation based on interfacial energy, which depends on interatomic interactions near the interface, as well as the misfit between melts, surface roughness, temperature, composition, etc., near the phase interface. The formation of nuclei requires overcoming a certain energy (nucleation) barrier that is a consequence of balancing the volume and the interfacial free energy. Knowing the nucleation barrier (W) is crucial for understanding this process, as nuclei predetermine the physical properties of a newly formed phase. W is typically expressed as a function of the nucleus radius; however, in nucleation kinetics, one needs to determine (W) as a function of the number of molecules forming the nucleus. We analyze nucleation work on various substrates (flat, convex, and concave) for crystallization from an aluminum melt to show that the formation of nuclei is the most probable on concave substrates. An analytical expression for W can be easily applied to other systems under consideration. We show that under the same conditions, the critical radius of nuclei is identical for various substrate, in contrast with the critical number of molecules forming a nucleus. Full article

The aim of the study was to determine the effect of accelerated thermal aging on the properties of selected poly(dimethylsiloxanes) (PDMS) differing in viscosity and hardness. This was related to the potential application for specialist casting molds with complex geometry. Four polyaddition silicones and two polycondensation ones were selected. As part of the work, tensile strength, hardness, density, roughness, and Dynamic Mechanical Analysis (DMA) and Fourier Transform Infrared Spectroscopy (FTIR) were tested, which allowed us to determine the degree of degradation of the analyzed materials subjected to thermal aging at a temperature of 150 ± 2 °C. The aging temperature was conditioned by the parameters of the materials that can be cast into molds made of poly(dimethylsiloxanes) e.g., with polymer resins, for which the exothermic peak ranges from 100 to 200 °C depending on the volume. It was observed that the initial Shore A hardness value affects parameters such as tensile strength or the amount of value change (its increase or decrease) after thermal aging. It can also be concluded that for polyaddition PDMS, the viscosity of the material has an effect on the size of the relative elongation value after thermal aging. Full article

In this work, a model for predicting the leakage rate was developed to investigate the effect of irradiation on the sealing performance of ethylene propylene diene monomer (EPDM) O-rings. The model is based on a mesoscopic interfacial gap flow simulation and accurately predicts the sealing performance of irradiated and non-irradiated materials by utilizing the gap height as an indicator in a mechanical simulation of the O-ring under operating conditions. A comparison with vacuum test results indicates that the model is a good predictor of leak initiation. The positive pressure leakage of the O-rings was investigated numerically. The results show the following. The sealing performance of the non-irradiated O-ring is much better than that of the irradiated one. The sealing performance is the worst at 0. 713 MGy and the best at 1.43 MGy, and the seal is maintained at an absorbed dose of 3.55 MGy. A theoretical analysis of the non-monotonic variation using the proposed model shows that the leakage behavior of the O-rings depends not only on the material properties but also on the roughness and prestressing properties. Finally, a method was proposed to classify the sealing performance, using the maximum allowable leakage rate as an indicator. Full article

The performance of a magnetic-field-assisted finishing (MAF) process, an advanced surface finishing process, is severely affected by the rheological properties of an MAF brush. The yield stress and viscosity of the MAF brush, comprising iron particles and abrasives mixed in a liquid carrier medium, change depending on the brush’s constituents and the applied magnetic field, which in turn affect the material removal mechanism and the corresponding final surface roughness after the MAF. A series of experiments was conducted to delineate the effect of MAF processing conditions on the yield stress of the MAF brush. The experimental data were fitted into commonly used rheology models. The Herschel–Bulkley (HB) model was found to be the most suitable fit (lowest sum of square errors (SSE)) for the shear stress–shear rate data obtained from the rheology tests and used to calculate the yield stress of the MAF brush. Processing parameters, such as magnetic flux density, weight ratio of iron and abrasives, and abrasive (black ceramic in this study) size, with p-values of 0.031, 0.001 and 0.037, respectively, (each of them lower than the significance level of 0.05), were all found to be statistically significant parameters that affected the yield stress of the MAF brush. Yield stress increased with magnetic flux density and the weight ratio of iron to abrasives in MAF brush and decreased with abrasive size. A new process model, a rheology-integrated model (RM), was formulated using the yield stress data from HB model to determine the indentation depth of individual abrasives in the workpiece during the MAF process. The calculated indentation depth enabled us to predict the material removal rate (MRR) and the instantaneous surface roughness. The predicted MRR and surface roughness from the RM model were found to be a better fit with the experimental data than the pre-existing contact mechanics model (CMM) and wear model (WM) with a R² of 0.91 for RM as compared to 0.76 and 0.78 for CMM and WM. Finally, the RM, under parametric variations, showed that MRR increases and roughness decreases as magnetic flux density, rotational speed, weight ratio of iron to abrasive particles in MAF brush, and initial roughness increase, and abrasive size decreases. Full article

The influence of various process parameters on the deep drawing process is a current research topic in sheet metal forming technology. Starting from the application of the previously constructed original testing device, an original tribological model was developed based on the process of sheet metal strip sliding between flat contact surfaces under variable pressures. A complex experiment was executed using an Al alloy sheet, tool contact surfaces of different roughness, two types of lubricants and variable contact pressures. The procedure included analytically pre-defined contact pressure functions based on which, for each of the mentioned conditions, the dependencies of the drawing forces and friction coefficients were obtained. The pressure in function P1 constantly decreased from a high initial value until the minimum, while in function P3 the pressure increased until the minimum value at the halfway point of the stroke, after which it increased up to the initial value. On the other hand, the pressure in function P2 constantly increased from the initial minimum value until the maximum value, while in function P4 the pressure increased until reaching the maximum value at the halfway point of the stroke, after which it decreased to the minimum value. This enabled the determination of the influence of tribological factors on the process parameters of intensity of traction (deformation force) and coefficient of friction. The pressure functions starting with decreasing trends produced higher values for the traction forces and the friction coefficient. In addition, it was established that the roughness of the contact surfaces of the tool, especially those with titanium nitride coating, has a significant influence on the process parameters. For surfaces of lower roughness (polished), a tendency of the Al thin sheet to form a glued-on layer was noticed. This was especially prominent for lubrication with MoS₂-based grease under conditions of high contact pressure (functions P1 and P4 at the beginning of the contact). Full article

Among metallic biomaterials, near-equiatomic NiTi is one of the most promising intermetallic system applicable for biomedical applications, thanks to its high biocompatibility and unique superelasticity (or pseudoelasticity), offering a complete recoverable strain up to 8%. In the prospective uses for bio-devices, the surface processing of NiTi medical components plays a fundamental role for guaranteeing both a Ti oxide passivizing layer for avoiding Ni ion release into the human body and surface morphology for controlling the cell proliferation. Mechanical polishing, thermal, chemical or electro-chemical treatments are typically performed for surface modifications. Recently, laser texturing has been successfully applied for different materials, included NiTi shape memory alloys, and also for tuning the surface properties, such as wettability. In the present work, ultrashort laser surface modification was carried out, through the use of a femtosecond laser, for the surface texturing of commercial superelastic NiTi plates. The main goal is to investigate the correlation among morphology, chemical composition and wettability with the principal process parameters, such as average power and scanning velocity in high power ultrashort laser texturing. Laser patterned surfaces were characterized by means of scanning electron microscopy, 3D-profilometry, XPS analysis and wetting measurements. After the laser treatments, both surface morphology and Ni/Ti ratio were largely modified from the initial surface, depending on the adopted process parameters. The wettability of the laser textured surfaces can be also varied with respect to the initial surface, due to the roughness values and grooves induced by the laser beam scans. The laser texturing process induced a combination between micro and nano structures, depending on the input energy. In details, the surfaces were tuned to lower roughness values (from 0.4 μm to 0.3 μm) with a laser power of 1 W, while it was increased up to 0.65 μm with a laser power of 13 W. The laser surface modification promoted a change of the contact angle from 70° of the untreated condition up to 135° to the surface laser treated with a power of 13 W. Full article

Experimental crude datasets are usually processed with statistical methods to obtain rough evaluations of nautical measurements. Taking the observations and rectifying the knowledge on them are not correlated. In modern computer applications, raw datasets are usually exploited in the initial learning phase. At this stage, the available data are explored to extract the necessary parameters required within the scheme of computations. The aim of this study was to undertake the crude data processing problem to extract the conditional dependencies that appear as the most important factors when handling the distorted data. First, I upgraded the traditional structures, which are histograms. The stepwise diagrams feature their uncertain evaluation. I upgraded the hierarchy among the evidence within the data pool and defined the given ranking adequate membership functions. The principles of fuzzy systems justified the use of the bin-to-bin additive approach to obtain the locally injective density functions, which can be perceived of as conditional dependency diagrams that enable the construction of simple belief assignments. The structural combination includes the solution to the position fixing problem. Full article