Search Results (58)

Thermal analysis (TA) has been a valuable tool for controlling the carbon equivalent (CE) of cast irons. Additionally, this technique can provide enhanced control over melt quality, allowing for the avoidance of defects such as undesirable graphite morphology and the formation of carbides. To obtain the most valuable information from the TA, it is necessary to minimize the variations in the filling operation of the TA cups. However, the mass and pouring temperature of TA cups can vary in TA’s typical foundry operations. A design of experiments was performed to determine whether specific parameters of cooling curves used for quality control can distinguish the inoculation effect in the melt when the mass and the pouring temperature of TA cups are varied. The minimum temperature of the eutectic arrest proved to be a robust inoculation potential control parameter when variations in the cup’s mass were within a range of 268–390 g and were filled at any pouring temperature between 1235 and 1369 °C. Lighter cups under 268 g and poured at a low temperature are not suitable for controlling inoculation potential by TA; however, they remain helpful in controlling CE. These later cups are related to cooling times of less than 180 s, which can serve as a criterion for discarding unsuitable samples. A bimodal population of cell surfaces was revealed in the samples, with the population of small cells being proportionally more numerous in samples with lower TE_min values. Full article

A localized freezing technique was proposed as an auxiliary method for retrofitting the lining of a vertical shaft. The influence of the freezing temperature, lining thickness, slot height, and slot duration on the evolution of the freezing wall in the clay layer was analyzed using a hydro-thermal numerical model. Under the baseline conditions (stratum temperature of 24 °C, shaft lining thickness of 2 m, and freezing temperature of −30 °C), the freezing wall behind the slotting zone was 0.74 m at 90 d, 1.89 m at 180 d, 2.78 m at 270 d, and 3.48 m at 360 d. The average growth rate of the freezing wall during one year was negatively linearly correlated with the freezing temperature and the shaft lining thickness, with change rates of −0.00033 m/(d∙°C) and −0.00262 m/(d∙m), respectively. Using the thickness of the freezing wall behind the slotting zone to reach 1.2 m as the slotting criterion, a freezing duration of 123 days is required under typical operational parameters. The evolution of the freezing wall was simulated for a slotting duration of 15 d with a slot height of 0.5–2.0 m and for a slot height of 1.5 m with a slotting duration of 5–20 d. The freezing walls did not melt in both schemes and expanded outward. The research findings are significant for improving freezing methods for shaft linings. Full article

Electrical heating ice removal pavement represents a promising technology for pavement ice melting. Existing studies primarily focus on optimizing cable-heated asphalt pavement through indoor model tests or finite element results. To obtain more accurate and reasonable temperature rise processes and heat transfer results, we propose a new evaluation metric for heat transfer capability and optimization in electric heating asphalt pavement. Firstly, a three-dimensional heat transfer model considering environmental heat exchange is established, and the accuracy of the model is verified by outdoor measured data. A dual-variable control experiment was carried out between the cable buried depth and insulation layer configuration to specifically analyze their influence on the temperature field of the asphalt layer. We further investigated heat transfer performance metrics (entransy dissipation and entransy dissipation thermal resistance), with results indicating that shallower cable burial depths reduce environmental interference on pavement heat transfer; the thermal insulation layer most significantly enhances pavement surface temperature (35.66% improvement) when cables are embedded in the lower asphalt layer. Placing cables within corresponding pavement layers according to burial depth reduces heat transfer loss capacity and thermal resistance, and positioning cables in the lower asphalt layer with a thermal insulation layer significantly decreases thermal resistance in both concrete and lower asphalt layers while reducing heat transfer capacity loss, demonstrating that installing thermal insulation layers under this structure improves heat transfer efficiency. The combined experimental and simulation verification method and fire dissipation evaluation system proposed in this study provide a new theoretical tool and design criterion for the optimization of electric heating road systems. Full article

The development of advanced air mobility—an eco-friendly, next-generation transportation system—is underway and garners significant attention. Due to the novel propulsion concept of eVTOL (electric Vertical Take-Off and Landing) and its operation in low altitude, urban environment, regulations for commercialization have not yet been established. Consequently, related research on passenger safety in emergency landings is ongoing, and this study focuses on enhancing the crashworthiness of advanced air mobility. To ensure the crashworthiness of advanced air mobility, civil airworthiness standards were referenced to determine the appropriate test conditions, and a design criterion for developing an energy-absorbing structure was derived. In this study, lattice structures are considered for designing an energy-absorbing structure that satisfies the design criterion, and finite element analysis is conducted to predict the performance of lattice structures. Based on the predicted data, surrogate models are constructed using the Kriging method according to the type of lattice structure. To verify the data obtained from numerical models, representative structures are manufactured using EBM (Electron Beam Melting) technology, and compressive tests are conducted to obtain the force–displacement curves. The test data are compared with the numerical data, and it is confirmed that the test data show good agreement with the numerical data. After this confirmation, the constructed surrogate models are utilized to select a lattice-based energy-absorbing structure that satisfies the crashworthiness-related design criterion. Finally, a crash simulation of a vertical drop test is carried out using the selected lattice structure, and results indicate that the resulting acceleration due to the collision is below the human tolerance limit, thereby verifying the crashworthiness of the energy-absorbing structure. Full article

Ta₂AlC is an emerging ceramic material characterized by its high melting point, high hardness, excellent thermal stability, and superior mechanical properties, which allow for broad application prospects in aerospace and defense fields. This paper investigates the physical mechanisms underlying the modulation of the mechanical and photoelectric properties of Ta₂AlC through doping using the first-principles pseudopotential plane-wave method. We specifically calculated the geometric structure, mechanical properties, electronic structure, Mulliken population analysis, and optical properties of Ta₂AlC doped with V, Ga, or Si. The results indicate that doping induces significant changes in the structural parameters of Ta₂AlC. By applying the Born’s criterion as the standard for mechanical stability, we have calculated that the structures of Ta₂AlC, both before and after doping, are stable. The mechanical property calculations revealed that V and Si doping weaken the material’s resistance to deformation while enhancing its plasticity. In contrast, Ga doping increases the material’s resistance to lateral deformation and brittleness. Doping also increases the anisotropy of Ta₂AlC. Electronic structure calculations confirmed that Ta₂AlC is a conductor with excellent electrical conductivity, which is not diminished by doping. The symmetric distribution of spin-up and spin-down electronic state densities indicates that the Ta₂AlC system remains non-magnetic after doping. The partial density of states diagrams successfully elucidated the influence of dopant atoms on the band structure and electronic state density. Mulliken population analysis revealed that V and Ga doping enhance the covalent interactions between C-Ta and Al-Ta atoms, whereas Si doping weakens these interactions. Optical property calculations showed that V and Si doping significantly enhance the electromagnetic energy storage capacity and dielectric loss of Ta₂AlC, while Ga doping has minimal effect. The reflectivity of doped and undoped Ta₂AlC reaches over 90% in the ultraviolet region, indicating its potential as an anti-ultraviolet coating material. In the visible light region, both doped and undoped Ta₂AlC exhibit a similar metallic gray appearance, suggesting its potential as a temperature control coating material. The light loss of Ta₂AlC is limited to a narrow energy range, indicating that doping does not affect its use as a light storage material. These results demonstrate that different dopants can effectively modulate the mechanical and photoelectric properties of Ta₂AlC. Full article

Lattice structures, composed of interconnected struts, offer an efficient way to reduce structural weight while maintaining structural integrity. Because of this potential, this work aims to investigate and develop an efficient variant form of a BCC (Body-Centered Cubic) lattice structure to enhance the structural robustness and energy absorption capability, based on the Maxwell stability criterion. And we specifically changed the bending-dominated to stretching-dominated behavior by adding auxiliary struts, according to the theory, and confirmed how this affects the compression behavior of the structure. For this purpose, horizontal auxiliary struts are added for the first time to the BCC structure along with vertical struts. As a macroscale cellular lattice structure, a unit cell size of 12 mm is considered. For the considered macroscale cellular lattice structures, FEA (finite element analysis) is employed to numerically investigate the stress distribution and compressive deformation mechanisms. Then, quasi-static compression tests are carried out to measure the energy absorption performance of the lattice structures manufactured by the EBM (Electron Beam Melting) metal additive manufacturing technique, which has advantages in building lattice structures without supporters. A comprehensive investigation reveals that a newly designed lattice structure offers significant advantages in structural robustness, with energy absorption capability increased by 365% compared to existing structures, achieved by incorporating vertical and cross-shaped horizontal auxiliary struts into the original BCC lattice configuration. The enhanced lattice structures can be utilized in industries where low-weight and high-strength are needed, such as aerospace, marine, and other industries. Full article

The Joule heat generated by current flow between electrodes in a resistance furnace not only melts and heats the charge but also induces mixing of the molten material. Increased mixing promotes improved chemical and temperature uniformity within the bath. This paper presents a novel approach to effectively optimizing electrode geometry in resistance furnaces. The method relies on a surrogate criterion derived exclusively from an electromagnetic submodel, which governs the process hydrodynamics. This criterion is based on the location of the Joule heat generation center in the bath. Its idea is to lower this center as much as possible while keeping it close to the vertical bath axis. Owing to this, the best conditions for the development of natural convection were obtained. The developed methodology was demonstrated through an application to a two-electrode furnace. The results showed that the influence of forced MHD convection is negligible in this furnace (with a Lorentz force of only about 0.0015 N/kg). The validation of the optimized geometry, derived using solely the electromagnetic submodel, was carried out using a full process model, including time-consuming hydrodynamic calculations. The proposed optimization methodology enabled a 10-fold increase in the average mixing velocity (from 0.0008 to 0.0084 m/s). The main significance of the presented study is the introduction of a surrogate criterion that allows for a multiple reduction in the time of numerical optimization of the mixing intensity in electrode resistance furnaces in comparison to the standard solution based on the flow velocity criterion determined from the hydrodynamic model. Full article

The work that is being presented demonstrates that there is a critical point at which the engineering stress–strain diagram’s elastic–plastic region transitions to yield and fracture stresses. This transition is demonstrated using thin-walled specimens made using selective laser melting technology from high-strength aluminum alloys (AlSi10Mg) that have undergone preliminary heat treatment. It was discovered that the strain-hardening coefficient, which was determined in the section from yield strength to fracture strength, and the critical point have a highly statistically significant association (0.83 by Spearman and 0.93 by Pearson). It was possible to derive a regression equation that connected the strain-hardening coefficient with the crucial transition point. The type of stress distribution in the elastic–plastic region changes (the Weibull distribution changes to a normal distribution) as the plasticity of the thin-walled samples increases. Additionally, the contribution of the probability density of the stress distribution described by the Cauchy distribution increases in a mode near the point at which the probability density of the fracture increases. Full article

A novel and original computer scaling-up system for the counter-rotating twin screw extrusion of polymers was developed. In the system, each scaling parameter (scaling criterion) may be considered as an objective function to be minimized for the single parameters or the functional relationships along the length of the screw. Scaling was based on the process simulation, which was performed using the comprehensive (or global) counter-rotating twin screw extrusion program called TSEM (Twin Screw Extrusion Model). The extrusion process was scaled by applying GASES_TWIN (Genetic Algorithms Screw Extrusion Scaling) software developed for this purpose using genetic algorithms. Scaling up the extrusion process was carried out to enhance extrusion process throughput according to the scaling criteria specified by the single quantities of polymer melt temperature at the die exit and relative melting length, and by distributions along the screw length of the extrusion parameters of the polymer melt temperature and polymer plasticating. The global objective function had the lowest value for the selected extrusion parameters, which means the minimal differences between the values of the scaled-up processes and extrusion throughput was significantly increased. The solution to the problem of scaling the counter-rotating process presented in this paper complements the existing solutions for optimizing and scaling basic variants of the extrusion process, i.e., flood-fed and starve (metered)-fed single-screw extrusion, as well as co-rotating and counter-rotating twin-screw extrusion. Full article

We present a study of hybrid neutron stars with color superconducting quark matter cores at a finite temperature that results in sequences of stars with constant entropy per baryon, $s/n_B=\mathrm{const}$. For the quark matter equation of state, we employ a recently developed nonlocal chiral quark model, while nuclear matter is described with a relativistic density functional model of the DD2 class. The phase transition is obtained through a Maxwell construction under isothermal conditions. We find that traversing the mixed phase on a trajectory at low $s/n_B\lesssim 2$ in the phase diagram shows a heating effect, while at larger $s/n_B$ the temperature drops. This behavior may be attributed to the presence of a color superconducting quark matter phase at low temperatures and the melting of the diquark condensate which restores the normal quark matter phase at higher temperatures. While the isentropic hybrid star branch at low $s/n_B\lesssim 2$ is connected to the neutron star branch, it becomes disconnected at higher entropy per baryon so that the “thermal twin” phenomenon is observed. We find that the transition from connected to disconnected hybrid star sequences may be estimated with the Seidov criterion for the difference in energy densities. The radii and masses at the onset of deconfinement exhibit a linear relationship and thus define a critical compactness of the isentropic star configuration for which the transition occurs and which, for large enough $s/n_B\gtrsim 2$ values, is accompanied by instability. The results of this study may be of relevance for uncovering the conditions for the supernova explodability of massive blue supergiant stars using the quark deconfinement mechanism. The accretion-induced deconfinement transition with thermal twin formation may contribute to explaining the origin of eccentric orbits in some binary systems and the origin of isolated millisecond pulsars. Full article

Due to the scarcity of modeling samples and the low prediction accuracy of the matte grade prediction model in the copper melting process, a new prediction method is proposed. This method is based on enhanced generative adversarial networks (EGANs) and random forests (RFs). Firstly, the maximum relevance minimum redundancy (MRMR) algorithm is utilized to screen the key influencing factors of matte grade and remove redundant information. Secondly, the GAN data augmentation model containing different activation functions is constructed. And, the generated data fusion criterion based on the root mean squared error (RMSE) and the coefficient of determination (R²) is designed, which can tap into the global character distributions of the copper melting data to improve the quality of the generated data. Finally, a matte grade prediction model based on RF is constructed, and the industrial data collected from the copper smelting process are used to verify the effectiveness of the model. The experimental results show that the proposed method can obtain high-quality generated data, and the prediction accuracy is better than other models. The R² is improved by at least 2.68%, and other indicators such as RMSE, mean absolute error (MAE), and mean absolute percentage error (MAPE) are significantly improved. Full article

This study investigates the influence of the main process parameters of injection molding(mold temperature, melt temperature, and injection rate) on the appearance of defects of flake-pigmented metallic polymer parts. To understand the influence of process parameters, an appearance defects index (ADI) is proposed to quantify the appearance defects. In this process, we propose a criterion for judging the appearance of defects based on the results of fiber orientation and tensor distribution analyses of the skin layer, which is then verified analytically by simulating experiments from the literature. Using the Taguchi experimental method, we designed an ${\mathrm{L}}_{25}$ orthogonal array to systematically evaluate the influence of process parameters. For each experimental condition, the signal-to-noise ratio (S/N ratio) was calculated to determine the optimal level of each factor and its influence on the appearance of defects. According to the results, mold temperature has the greatest influence on the appearance of defects, with an influence of 48.7%, followed by injection rate with an influence of 40.8%, and melt temperature with an influence of 10.5%. The optimal process parameters were found to be a mold temperature of 40 °C, a melt temperature of 250 °C, and an injection rate of 10 cm³/s, which resulted in a 12.6% improvement in the Appearance defects index (ADI) compared to the standard injection molding condition of ABS materials. This study confirmed that it is possible to improve the appearance of defects by adjusting the process parameters of injection molding. Full article

Thermo-responsive, biocompatible polyurethane (PU) with shape memory properties is highly desirable for biomedical applications. An innovative approach to producing wound closure strips using shape memory polymers (SMPs) is of significant interest. In this work, PU composed of polycaprolactone (PCL) and 1,4-butanediol (BDO) was synthesized using two-step polymerization. Palm oil (PO) was added to PU for enhancing the Young’s modulus of the PU beyond the set criterion of 130 MPa. It was found that PU had the ability to crystallize at room temperature and the segments of individual PCL and BDO polyurethanes crystallized separately. The crystalline domains and hard segment of PU greatly affected the tensile properties. The reduction of crystalline domains by the addition of PO and deformation at the higher melting temperature of the crystalline PCL polyurethane phase improved the shape fixity and shape recovery ratios. The new irreversible phase, raised from the permanent deformation upon stretching at the between melting temperature of the crystalline PCL and BDO polyurethanes of 70 °C, resulted in a decrease in shape fixity ratio after the first thermomechanical stretching–recovering cycles. The demonstration of PU as a wound closure strip showed its efficiency and potential until the surgical wound healed. Full article

The present work focuses on predicting the steel melt temperature following the vacuum treatment step in a vacuum tank degasser (VTD). The primary objective is to establish a comprehensive methodology for developing and validating machine learning (ML) models within this context. Another objective is to evaluate the model by analyzing the alignment of the SHAP values with metallurgical domain expectations, thereby validating the model’s predictions from a metallurgical perspective. The proposed methodology employs a Random Forest model, incorporating a grid search with domain-informed variables grouped into batches, and a robust model-selection criterion that ensures optimal predictive performance, while keeping the model as simple and stable as possible. Furthermore, the Shapley Additive Explanations (SHAP) algorithm is employed to interpret the model’s predictions. The selected model achieved a mean adjusted $R^2$ of 0.631 and a hit ratio of 75.3% for a prediction error within ±5 °C. Despite the moderate predictive performance, SHAP highlighted several aspects consistent with metallurgical domain expertise, emphasizing the importance of domain knowledge in interpreting ML models. Improving data quality and refining the model framework could enhance predictive performance. Full article

Prediction of the antibacterial activity of new chemical compounds is an important task, due to the growing problem of bacterial drug resistance. Generalized linear models (GLMs) were created using 85 amidrazone derivatives based on the results of antimicrobial activity tests, determined as the minimum inhibitory concentration (MIC) against Gram-positive bacteria: Staphylococcus aureus, Enterococcus faecalis, Micrococcus luteus, Nocardia corallina, and Mycobacterium smegmatis. For the analysis of compounds characterized by experimentally measured MIC values, we included physicochemical properties (e.g., molecular weight, number of hydrogen donors and acceptors, topological polar surface area, compound percentages of carbon, nitrogen, and oxygen, melting points, and lipophilicity) as potential predictors. The presence of R1 and R2 substituents, as well as interactions between melting temperature and R1 or R2 substituents, were also considered. The set of potential predictors also included possible biological effects (e.g., antibacterial, antituberculotic) of tested compounds calculated with the PASS (Prediction of Activity Spectra for Substances) program. Using GLMs with least absolute shrinkage and selection (LASSO), least-angle regression, and stepwise selection, statistically significant models with the optimal value of the adjusted determination coefficient and of seven fit criteria were chosen, e.g., Akaike’s information criterion. The most often selected variables were as follows: molecular weight, PASS_antieczematic, PASS_anti-inflam, squared melting temperature, PASS_antitumor, and experimental lipophilicity. Additionally, relevant to the bacterial strain, the interactions between melting temperature and R1 or R2 substituents were selected, indicating that the relationship between MIC and melting temperature depends on the type of R1 or R2 substituent. Full article