Original Mold Research Articles

Research on shear-thinning and surface properties of CaO–SiO2–CaF2–Al2O3-based mould flux

The main feature of high-efficiency continuous casting production is the increase in casting speed. This leads to an increased risk of slag entrapment in the liquid surface area of the mould and steel leakage due to the bonding of the casting billet. Both traditional mould flux and non-Newtonian fluid mould flux with only shear-thinning properties cannot effectively solve these problems. This study selected a practical high-casting speed thin slab mould flux from a steel plant as the original mould flux. Add 4.6–12.1% Al2O3 and 3.6–4.9% MnO and other additives to prepare a new type of mould flux with both shear thinning characteristics and high surface tension. The shear-thinning properties, interface properties and microstructure of the mould flux were detected and studied using methods such as the rotating cylinder method. The results showed that with the increase of Al2O3 content, the shear-thinning properties of the mould flux first enhanced and then weakened. The strongest effect was observed when the Al2O3 content was 8.7%. The contact angle, surface tension and interface tension of the mould flux were significantly improved and the degree of molecular polymerisation gradually increased. The shear-thinning properties of mould flux are mainly related to the Si–O–Al structure. The interaction force between Al3+ in the slag and the surface O2− of the mould flux increases, and the surface tension of the mould flux increases. When the Al2O3 content is more than 10.5%, a large amount of AlO2− will be repelled to the surface of the mould flux, and the change in surface tension is no longer significant.

Simulation of the THF hydrate-water interfacial free energy from computer simulation.

In this work, the tetrahydrofuran (THF) hydrate-water interfacial free energy is determined at 500 bar, at one point of the univariant two-phase coexistence line of the THF hydrate, by molecular dynamics simulation. The mold integration-host methodology, an extension of the original mold integration technique to deal with hydrate-fluid interfaces, is used to calculate the interfacial energy. Water is described using the well-known TIP4P/Ice model, and THF is described using a rigid version of the TraPPE model. We have recently used the combination of these two models to accurately describe the univariant two-phase dissociation line of the THF hydrate in a wide range of pressures from computer simulation [Algaba et al., J. Chem. Phys. 160, 164718 (2024)]. The THF hydrate-water interfacial free energy predicted in this work is compared with the only experimental data available in the literature. The value obtained, 27(2) mJ/m2, is in excellent agreement with the experimental data taken from the literature, 24(8) mJ/m2. To the best of our knowledge, this is the first time that the THF hydrate-water interfacial free energy is predicted from computer simulation. This work confirms that the mold integration technique can be used with confidence to predict the solid-fluid interfaces of complex structures, including hydrates that exhibit sI and sII crystallographic structures.

Maximization of Total Profit for Hybrid Hydro-Thermal-Wind-Solar Power Systems Considering Pumped Storage, Cascaded Systems, and Renewable Energy Uncertainty in a Real Zone, Vietnam

The study maximizes the total profit of a hybrid power system with cascaded hydropower plants, thermal power plants, pumped storage hydropower plants, and wind and solar power plants over one operation day, considering the uncertainty of wind speed and solar radiation. Wind speed and solar radiation in a specific zone in Vietnam are collected using the wind and solar global atlases, and the maximum data are then supposed to be 120% of the collection for uncertainty consideration. The metaheuristic algorithms, including the original Slime mould algorithm (SMA), Equilibrium optimizer, and improved Slime mould algorithm (ISMA), are implemented for the system. ISMA is a developed version of SMA that cancels old methods and proposes new methods of updating new solutions. In the first stage, the cascaded system with four hydropower plants is optimally operated by simulating two cases: simultaneous optimization and individual optimization. ISMA is better than EO and SMA for the two cases, and the results of ISMA from the simultaneous optimization reach greater energy than individual optimization by 154.8 MW, equivalent to 4.11% of the individual optimization. For the whole system, ISMA can reach a greater total profit than EO and SMA over one operating day by USD 6007.5 and USD 650.5, equivalent to 0.12% and 0.013%. The results indicate that the optimization operation of cascaded hydropower plants and hybrid power systems can reach a huge benefit in electricity sales

Exponential slime mould algorithm based spatial arrays optimization of hybrid wind-wave-PV systems for power enhancement

Exponential slime mould algorithm based spatial arrays optimization of hybrid wind-wave-PV systems for power enhancement

Identifying and estimating solar cell parameters using an enhanced slime mould algorithm

Identifying and estimating solar cell parameters using an enhanced slime mould algorithm

Fabrication of a stacked Archimedean spiral reactor with porous carbon walls using 3D-printed PLA as internal sacrificial template and carbonized whey powder as porous carbon matrix

This study introduces a method to create porous carbon structures with intricate internal voids. 3D-printed PLA acts as an internal sacrificial template, combined with carbonized whey powder as the porous carbon matrix. Sintering whey powder at 150°C yields solid pieces that, upon carbonization, result in highly porous carbon objects while maintaining the original mold shape. Temperature control ensures successful whey powder sintering before PLA melting. The use of PLA sacrificial templates, along with whey carbonization, allows for developing devices with finely tailored internal voids, as demonstrated through a double Archimedean spiral reactor with porous carbon walls.Graphical abstract

Understanding Mold Wear Mechanisms and Optimizing Performance through Nico Coating: An In-Depth Analysis

This research investigates the wear mechanism of molds and examines the worn areas using high power microscopes and SEM (Scanning Electron Microscopy). In addition, EDS (Energy Dispersive Spectroscopy) and XRF (X-ray fluorescence) techniques are used to compare the worn areas with the normal areas. The results indicate that the wear mechanism of the molds is similar to adhesive wear. To address the issue of die wear, the application of Nico coating to the copper substrate surface is investigated. Two sample preparation methods, namely DC power supply and dual pulse power supply, are employed. SEM analysis shows that the sample group prepared using the dual pulse power supply has a relatively dense surface coating. The samples with a 60:40 weight ratio of Nico exhibit the highest average hardness and thickness, with minimal dispersion as indicated by the low standard deviation. The samples also show minimal roughness. Repeat tests under the same conditions confirm that the coating surface remains dense and uniform with a hardness of 467.628 hv, a thickness of 43.0665 μm and a roughness of 4.331 nm. The nanoindenter test results show that the coating has improved wear resistance (−28.7 nm) compared to the original mold (−142.4 nm), an increase of 80%.

Analyzing the evolution of the artistic image of “Yang Yuhuan” from a feminist perspective through the lens of arts and cultural management

Yang Yuhuan is a controversial consort from ancient China. From historical records to literary works and even contemporary film and television dramas, the image of Yang Yuhuan has been constantly reshaped. However, in the fields of stage drama and film and television works, there has been relatively limited scholarly research on her image, with even fewer touching on arts and cultural management. This paper adopts a feminist perspective to analyze the evolution of Yang Yuhuan’s image over different periods, taking her drama and film portrayals as the study subjects. The aim is to explore how, in the current societal context, one might enrich the image of Yang Yuhuan from the standpoint of arts management. Through this research, the author observes that the underlying representation of Yang Yuhuan is that of a beautiful and nation-damaging favored consort. Notably, such an image is not merely the result of personal choice but a collective product of power and knowledge. In recent years, China’s art market has seen abundant creative representations of Yang Yuhuan, but innovations concerning her image have been scant, largely adhering to its original mold. This does not align with contemporary societal and cultural norms and fails to meet audience demands. Therefore, to further diversify the image of Yang Yuhuan, creators should transcend her traditional objectified portrayal, emphasize the unique political aspects of her love story with Emperor Li Longji, reconsider the notion that “a woman can cause the downfall of a nation,” and collaboratively innovate her image through arts management.

Mobile Robot Path Planning with a Novel Multiobjective Slime Mold Algorithm

In the path planning problem of mobile robot in static complex obstacle environment, the original slime mold algorithm (SMA) has some shortcomings, such as initial solution error and easy to fall into local optimum, which leads to low accuracy of robot path planning. A novel Baldwin learning effect mobile robot Path planning with Multi‐Objective Slime Mold Algorithm (BPMOSMA) is proposed to solve the related problems. The Baldwin learning effect is introduced into to guide the development direction of slime mold in the phase of slime mold surrounding food and the k‐nearest neighbor measure is added to prune nondominated solutions to generate a well‐distributed solution set. For comparison purposes, five state‐of‐the‐art multiobjective optimization algorithms are carried on nine multiobjective test problems with kinds of types of Pareto set. The qualitative and quantitative experimental results show that BPMOSMA is very competitive performance on unconstrained multi‐objective optimization problems. BPMOSMA is finally successfully applied in the mobile robot path planning problem.

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

In this paper, an improved slime mould algorithm (ISMA) is proposed for finding the optimal location and sizing of photovoltaic distributed generation units (PVDGUs) in unbalanced distribution systems (UDSs). The proposed method is developed by changing the control variable update mechanism of the original slime mould algorithm (SMA). Total power losses on distribution lines and voltage deviation index of all buses are minimized under the consideration of various constraints. The location and sizing of PVDGUs found by ISMA are added into the cosimulation between MATLAB and OpenDSS for reaching other remaining parameters of UDSs. In addition, sunflower optimization (SFO), social-ski drive (SSD), cuckoo search algorithm (CSA), salp swarm algorithm (SSA), bonobo optimizer (BO), and SMA are also run for finding PVDGUs placement solution on the unbalanced three-phase IEEE 123-bus test feeder. As a result, the proposed ISMA can reduce the power loss up to 78.88% and cut the voltage deviation up to 1.4779 pu while that of others is from 69.10% to 78.87% and from 1.5759 to 1.4996 pu. Thus, ISMA should be used to place PVDGUs in UDSs meanwhile the cosimulation between MATLAB and OpenDSS should be applied as a power flow calculation tool for UDSs.

Melt sampling for hydrogen analysis optimized with the help of computer simulation

This research was carried out in laboratory conditions on a semi-continuous ingot casting machine owned by the Siberian Federal University. The paper compares the results of computer simulation carried out for AK12 alloy solidification process in the PoligonSoft programme. A new original mould is described designed for sampling liquid aluminium and its alloys for hydrogen analysis. The new mould has a larger surface area and walls that are made in the form of a heat exchanger intended for more efficient heat removal. It is shown that, in the commonly used Rensley mould, the melt solidifies in 14 seconds at the metal crystallization rate in the range from the pouring temperature to the solidus temperature of 15 oC/s, while in the case of the new mould these parameters are 12 seconds and 17.5 oC/s, correspondingly. The paper also compares the results of dissolved hydrogen analysis obtained when sampling was done with both the conventional Rensley mould and the new one. It was found that the concentration of hydrogen in the samples taken with the Rensley mould is lower on average by 0.01 cm3/100 g Al than in the samples taken with the new mould. Based on the results of the study, a conclusion was drawn that the proposed mould design delivers an additional advantage when sampling liquid metal. It also helps determine the concentration of dissolved hydrogen in molten aluminium with a higher degree of accuracy.This research was carried out by the Siberian Federal University as part of the governmental assignment for research; Project No. FSRZ-2020-0013.

Visualization of Melt-Flow Behavior Inside the Runner in Ultra High Speed Injection Molding

Abstract Ultra-high-speed injection molding is a highly effective technique for realizing very thin-walled molded parts; its application to the production of new high value-added products is anticipated. The melt-flow behavior in ultra-high-speed injection molding is expected to differ from that in conventional molding. However, thus far, very few studies pertaining to the phenomena occurring within cavities and runners at such high filling speeds have been reported, thus necessitating the direct observation of melt-flow behavior inside the molds. In this study, we attempted to dynamically visualize the melt-flow behavior at the runner split portion, especially under ultra-high-speed injection molding. Visualization experiments were conducted using a glass-inserted mold, which was modified from the original visualization mold structure in order to improve the pressure endurance of the glass-inserted visible area. This paper discusses the visualization analyses of melt-flow behavior in two types of experimental split runner systems (three inclined split runners and cross-shaped runners in a cascade layout). The behavior at the runner split area was studied under low to ultra-high-filling rates. The analyses clarified the effects of inertia at the runner branching point, which has not been verified in general injection molding, and the consequent changes in the filling behavior.

An evolutionary machine learning for pulmonary hypertension animal model from arterial blood gas analysis

Pulmonary hypertension (PH) is a rare and fatal condition that leads to right heart failure and death. The pathophysiology of PH and potential therapeutic approaches are yet unknown. PH animal models' development and proper evaluation are critical to PH research. This work presents an effective analysis technology for PH from arterial blood gas analysis utilizing an evolutionary kernel extreme learning machine with multiple strategies integrated slime mould algorithm (MSSMA). In MSSMA, two efficient bee-foraging learning operators are added to the original slime mould algorithm, ensuring a suitable trade-off between intensity and diversity. The proposed MSSMA is evaluated on thirty IEEE benchmarks and the statistical results show that the search performance of the MSSMA is significantly improved. The MSSMA is utilised to develop a kernel extreme learning machine (MSSMA-KELM) on PH from arterial blood gas analysis. Comprehensively, the proposed MSSMA-KELM can be used as an effective analysis technology for PH from arterial Blood gas analysis with an accuracy of 93.31%, Matthews coefficient of 90.13%, Sensitivity of 91.12%, and Specificity of 90.73%. MSSMA-KELM can be treated as an effective approach for evaluating mouse PH models.

3D Digital Technologies for the Elaboration of a Replica of a Dermatological Didactic Model Belonging to the Olavide Museum from the Original Mould

The Olavide Museum in Madrid, which was founded in the 19th century, preserves one of the most important collections in the world of three-dimensional dermatological models made of polychrome beeswax. These models have been used for the training of numerous generations of dermatologists in Spain. Unfortunately, many of the figures were preserved in precarious conditions during the time that the museum was closed in the middle of the 20th century, and some could not be found after its reopening. In this paper, we show a method for the recovery of a missing model of which only the original plaster cast remains. For this purpose, we use the combination of a structured light scanner and 3D printing, together with traditional techniques, to reproduce a copy of the original cast, in order to prevent its deterioration during the wax casting. As a result of this study, a highly realistic figure was obtained, which represented, in great detail, the small superficial reliefs of the skin lesions, as well as their colour. The conclusion of this research is that it is possible to recreate, with precision, a didactic model in beeswax from its mould, without the need to use the mould in the process, which avoids any risk of deterioration in the process.

Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation

First, this study develops an enhanced slime mould algorithm (MGSMA). The main idea is to combine the new movement strategy and Gaussian kernel probability strategy to improve the optimization performance of the original slime mould algorithm. These two tactics increase MGSMA's capacity to avoid being stuck in a local optimum and reduce the probability of delaying the convergence process. Second, by integrating non-local mean, 2D Kapur's entropy, and other relevant methodologies, a novel multi-level image segmentation (MLIS) model is developed based on the suggested MGSMA. To showcase MGSMA's performance, specific comparative tests based on IEEE CEC2014 are carried out, clearly showing that MGSMA is a swarm intelligence approach capable of jumping out of the local optimum and the convergence process does not willingly interrupt. To demonstrate that the MGSMA-based MLIS approach can provide high-quality segmentation results, it is compared to eight other comparable methods at both high and low thresholding levels, with some relevant experimental findings to back up its claims. As a consequence, there is no question that MGSMA is a high-performance swarm intelligence optimization approach and that the MGSMA-based MLIS method can provide high-quality segmentation results. The source codes of the SMA algorithm and latest updates are publicly available at https://aliasgharheidari.com/SMA.html.

An assessment of the cheese product’s nutrient profile in implementation the new resource-saving technological solutions

In the сurrent conditions the cheese industry development is determining by perspective trends: medical and social – expansion the products range with dietary properties and reduced a calorie content, technological – mastering а new moulding methods for the production of complex and combined cheese products, economic – reduction of a milk consumption rates due to involvement secondary raw materials, ecological – minimizing the carbon footprint of cheese factories by reducing whey’s discharges. The patented method for producing the combined soft cheese product offers a set of resource-saving technological solutions for introducing into the cheese head an agarised jelly "filling" based on return salty whey with the spicy plant components addition. The original mold design forms a through hole in the center of the cheese head and provides the cheese part to the "filling" in а ratio as 4 : 1. The proposed method of the using salty sub-raw whey in soft cheese’s production is justified from the point of view the adequacy level its macro- and micronutrient composition to physiological requirements in food nutrients and energy. The new cheese product with a jelly "filling" contains 14.5% protein and 15.3% fat, that makes up for 17% of the requirements for adult. The product has a reduced calorie content to 208 kcal with a significant 28% energy contribution by the protein component, that gives it dietary properties. The cheese product’s provision by essential amino acids reaches 90% of the requirement in phenylalanine and tyrosine, 87% in lysine, 74% in isoleucine and leucine. The fatty acid profile is characterized by favorable a relative content values of linolenic and oleic acids. Low-molecular volatile fatty acids form the taste and aroma of cheese product without ripening. Its vitamin composition has functional availability for vitamins A - 40%, K - 31%, group B and PP - 15-20% of the requirement. The technological solutions for making of the cheese product with the "filling" maintain a functionality its nutrient profile, contribute to saving up to 20% of milk and increase the environmental friendliness of production.

Nanoimprinting for high-throughput replication of geometrically precise pillars in fused silica to regulate cell behavior

Developing high-throughput nanopatterning techniques that also allow for precise control over the dimensions of the fabricated features is essential for the study of cell-nanopattern interactions. Here, we developed a process that fulfills both of these criteria. Firstly, we used electron-beam lithography (EBL) to fabricate precisely controlled arrays of submicron pillars with varying values of interspacing on a large area of fused silica. Two types of etching procedures with two different systems were developed to etch the fused silica and create the final desired height. We then studied the interactions of preosteoblasts (MC3T3-E1) with these pillars. Varying interspacing was observed to significantly affect the morphological characteristics of the cell, the organization of actin fibers, and the formation of focal adhesions. The expression of osteopontin (OPN) significantly increased on the patterns, indicating the potential of the pillars for inducing osteogenic differentiation. The EBL pillars were thereafter used as master molds in two subsequent processing steps, namely soft lithography and thermal nanoimprint lithography for high-fidelity replication of the pillars on the substrates of interest. The molding parameters were optimized to maximize the fidelity of the generated patterns and minimize the wear and tear of the master mold. Comparing the replicated feature with those present on the original mold confirmed that the geometry and dimensions of the replicated pillars closely resemble those of the original ones. The method proposed in this study, therefore, enables the precise fabrication of submicron- and nanopatterns on a wide variety of materials that are relevant for systematic cell studies. STATEMENT OF SIGNIFICANCE: Submicron pillars with specific dimensions on the bone implants have been proven to be effective in controlling cell behaviors. Nowadays, numerous methods have been proposed to produce bio-instructive submicron-topographies. However, most of these techniques are suffering from being low-throughput, low-precision, and expensive. Here, we developed a high-throughput nanopatterning technique that allows for control over the dimensions of the features for the study of cell-nanotopography interactions. Assessing the adaptation of preosteoblast cells showed the potential of the pillars for inducing osteogenic differentiation. Afterward, the pillars were used for high-fidelity replication of the bio-instructive features on the substrates of interest. The results show the advantages of nanoimprint lithography as a unique technique for the patterning of large areas of bio-instructive surfaces.

Fractional Order PID Design based on Novel Improved Slime Mould Algorithm

This study attempts to maintain the terminal voltage level of an automatic voltage regulator (AVR) and control the speed of a direct current (DC) motor using a fractional order proportional integral derivative (FOPID) controller. The best parameters of the controller have been adjusted using a novel meta-heuristic algorithm called opposition-based hybrid slime mold with simulated annealing algorithm. The proposed algorithm aims to improve the original slime mold algorithm in terms of exploitation and exploration using simulated annealing and opposition-based learning, respectively. A time domain objective function was adopted as performance index to design the FOPID-based AVR and DC motor systems. The initial performance evaluation was carried out using unimodal and multimodal benchmark functions. The results confirmed the superior exploration and exploitation capabilities of the developed algorithm compared to the other state-of-the-art optimization algorithms. The performance of the proposed algorithm has also been assessed through statistical tests, time domain and frequency domain simulations along with robustness and disturbance rejection analyses for both DC motor and AVR systems. The proposed algorithm has shown superior capabilities for the respective systems compared to the other state-of-the-art optimization algorithms used for the same purpose.

Balanced version of Slime Mold Algorithm: A study on PEM fuel cell system parameters identification

A new technique is proposed in this study for optimum selection of the unknown variables in the Proton Exchange Membrane Fuel Cells (PEMFCs). The major purpose is to present an efficient method for minimizing the error between the estimated and the empirical output voltages by the optimal valuation of the model parameters. To do so, a balanced version of the Slime Mold Algorithm (bSMA) is introduced and validated. The method is then performed into three standard benchmarks including NedStack PS6, Horizon H-12, and 5 kW Ballard Mark V and the results are compared with three other state-of-the-art algorithms including Blackhole Algorithm, Locust Swarm Optimization Algorithm, and the original Slime mold algorithm. The results show that the proposed bSMA with 3.01, 1.75, and 0.104 for NedStack PS6, Horizon H-12, and 5 kW Ballard Mark V, respectively has the minimum value of error. Therefore, this proves that the proposed technique gives the best results against the others for model identification. Also, to provide more analysis, the consistency of the suggested method is investigated under different temperature and pressure conditions which shows that the suggested technique has reliable results toward different conditions.

Nanoimprinting for High-Throughput Fabrication of Geometrically Precise Pillars to Regulate Cell Behavior

Developing high-throughput nanopatterning techniques that also allow for precise control over the dimensions of the fabricated features is essential for the study of cell-nanopattern interactions. Here, we developed a process that fulfills both of these criteria. Firstly, we used electron-beam lithography (EBL) to fabricate precisely controlled arrays of high aspect ratio submicron pillars with varying values of interspacing on a large area (3 × 5 mm2) of fused silica substrates. Two types of etching procedures with two different systems were developed to etch the fused silica and create the final desired height. We then studied the interactions of preosteoblasts (MC3T3-E1) with these pillars. Varying interspacing was observed to significantly affect the morphological characteristics of the cell, the organization of actin fibers, and the formation of focal adhesions. The expression of osteopontin (OPN) significantly increased on the patterns, indicating the potential of the pillars for inducing osteogenic differentiation. The EBL arrays of pillars were thereafter used as master molds in two subsequent processing steps, namely soft lithography (using hybrid PDMS) and thermal nanoimprint lithography for high-fidelity replication of the pillars on the substrates of interest. The molding parameters were optimized to maximize the fidelity of the generated patterns and minimize the wear and tear of the master mold. Comparing the replicated feature with those present on the original mold confirmed that the geometry and dimensions of the replicated pillars closely resemble those of the original ones (i.e., 1% deviation in pillar interspacing, < 20% deviation in pillar diameter). The method proposed in this study, therefore, enables the precise fabrication of submicron- and nanopatterns on a wide variety of substrate materials that are relevant for systematic cell studies.