Effect Of Different Process Parameters Research Articles

The effect of different process parameters on the flowability of modified magnesium-coal based solid waste carbon fixation backfill slurry rich in dicalcium silicate

The effect of different process parameters on the flowability of modified magnesium-coal based solid waste carbon fixation backfill slurry rich in dicalcium silicate

Critical factors for enhancing electrical performance in LaGdO3 capacitor

This study investigates the characteristics of metal/LaGdO3/Si capacitors using LaGdO3 as the dielectric material. LaGdO3 thin films were deposited using radio-frequency magnetron sputtering, and the effects of different process parameters, such as annealing temperature, electrode materials, and oxygen ratio, on the capacitance characteristics were investigated. Results showed that the presence of oxygen vacancies affects the dielectric constant, flat-band voltage, and breakdown field of LaGdO3 films. The optimal annealing temperature for the LaGdO3/Si stack was identified to be 600 °C, resulting in a dielectric constant of 13.9 and a flat-band voltage shift of 0.1 V. Introducing 10 % O2 during deposition effectively repaired oxygen vacancies in the film, while excessively high oxygen proportions resulted in a lower dielectric constant and a higher flat-band voltage shift. Moreover, the electrode material was found to affect the capacitance characteristics. The dielectric constants for Al/LaGdO3/Si, Ti/LaGdO3/Si, and Pt/Ti/LaGdO3/Si capacitors were 10.0, 16.3, and 17.3, respectively. The flat-band voltage shifts were −0.7, −0.42, and −0.03 V, with hysteresis voltages of 345, 117, and 32 mV, respectively. The Pt/Ti/LaGdO3/Si device exhibited the lowest oxide defect density, indicating superior interface quality and potentially enhanced device performance. In addition, the band diagrams for metal/LaGdO3/Si were constructed. This study demonstrates that oxygen vacancies and electrode materials are crucial factors influencing the capacitance characteristics of LaGdO3 films. The electrical properties of LaGdO3 films can be effectively improved by controlling process parameters, enhancing their potential for applications in capacitors and other electronic devices.

Avoiding heat source calibration for finite element modeling of the laser powder bed fusion process

The melt pool characteristics govern process stability and microstructure development during Laser Powder Bed Fusion (LBPF). The melt pool is strongly affected by the laser parameters and based on the melt pool depth-to-width ratio, three melting modes can be distinguished: conduction, transition, and keyhole mode. Finite element (FE) simulations have been extensively used to investigate the cyclic thermal history of the LPBF process and the effects of different process parameters on the part quality. However, the heat sources applied in such simulations can only accurately predict the melt pool behavior, and thus the temperature profile, when processing in conduction mode. As for the transition and keyhole regime modeling, heat source parameters or material properties are usually adjusted to make the simulated melt pool dimensions match the real values. This study proposes a novel approach to bypass the conventional heat source calibration strategy to simulate the LBPF process across different melting regimes. The predicted melt pool dimensions are validated for a wide range of process parameters applied to three different alloys: Ti-6Al-4V, 316L austenitic stainless steel (316L), and 2507 super duplex stainless steel (SDSS). The average errors obtained on the melt pool width, depth, length, and aspect ratio are 9.7%, 12.4%, 14.5%, and 14.3% respectively. These results demonstrate how the proposed approach can capture the melt pool dimensions throughout different materials and melting modes eliminating the time-consuming heat source calibration steps and facilitating the LPBF modeling workflow.

Insights into the effect of operating parameters and hydrodynamics on hydrolysis reaction in Copper–Chlorine thermochemical water splitting cycle for hydrogen production: Modelling and experimental validation

Copper–Chlorine (Cu–Cl) thermochemical cycle is being explored as one of the promising technologies for large scale production of clean hydrogen from water using nuclear or renewable energy. In this method, water splitting is achieved through a series of reactions in a loop producing only hydrogen and oxygen with complete recycle of all the intermediate copper and chlorine compounds. The first step of the cycle is the hydrolysis reaction wherein steam reacts with solid CuCl2 to form solid Cu2OCl2 (copper oxychloride) and HCl gas. The products enter the subsequent steps of the cycle and are recycled back to complete the loop. Multiple side reactions in the hydrolysis step result in reduced yield and loss of chemicals from the cycle. Efficient reactor design and optimal operating conditions of hydrolysis reactor is imperative towards achieving sustained closed loop operation and reducing the energy demand of Cu–Cl cycle. This paper presents a mathematical model for the simulation of hydrolysis reaction in a bubbling fluidized bed reactor. The one-dimensional model is developed based on modified two-phase theory of fluidization and is coupled with kinetics of multiple side reactions to investigate the effect of operating parameters and hydrodynamics on the conversion and yield of Cu2OCl2. The model results are validated with experimental data in 50 mm and 100 mm semi-batch fluidized bed reactors. The developed model clearly brings out the effect of different process parameters for process optimization and scale-up of the hydrolysis reactor for efficient integration in the cycle.

Influence of Laser Process Parameters on the Forming Quality and Discharge Performance of 3D-Printed Porous Anodes for Al-Air Batteries.

Aluminum-air (Al-air) batteries are considered one of the most promising next-generation energy storage devices. In this paper, we carry out an orthogonal experimental study on the SLM printing process parameters in 3D-printed Al-air battery anodes. The surface roughness, densification, and discharge performance of the electrodes under different process parameters are observed to reveal the effects of different process parameters on the forming quality and discharge performance of aluminum-air battery anodes. The results show that the laser power is the most important factor affecting the surface roughness of the porous aluminum anode, and the scanning spacing is the most important factor affecting the densification. The best printing parameters for the porous aluminum anode can be obtained when the laser power is 325 W, the scanning speed is 1000 mm/s, the scanning spacing is 0.12 mm, and the thickness of the powder spread is 0.03 mm. At this time, the surface roughness of the porous aluminum anode obtained by this process parameter is 15.01 μm, the densification is 94.97%, and the discharge is stable with a high value. In addition, we also carry out data validation to ensure that the data we obtain are optimal and valid.

Extraction of Vanadium from CaO–SiO2–MgO–Al2O3 Slags Based on Vaporization of Vanadium Pentoxide

Vanadium is an important micro‐alloying element for various steel grades. Consequently, it is also present in the slags used in the production of those grades. During steelmaking, the vanadium vaporization from the slag is not desirable, as it increases vanadium consumption and at the same time releases toxic vapors of its higher oxides. However, the recovery of vanadium from the slag after the processing is worthwhile. In oxidic form as vanadium pentoxide (V2O5), vanadium can be extracted from the slag. In this research, the vaporization behavior of vanadium from CaO–SiO2–MgO–Al2O3 industrial slag is investigated at 1873 K. The effect of different process parameters, e.g., the pressure in the furnace chamber, the duration of the oxygen treatment of the slag, and the oxygen flow rate, is considered. The effect of P2O5 and Fe2O3 addition on the extraction of vanadium is studied. It is possible to induce formation of V2O5 gas bubbles in the slag due to the oxidation of vanadium. Thus, vanadium respectively V2O5 is extracted from the slag.

Investigation of Micropattern Forming Process on Zr‐4 Alloy Surface Considering Plowing Effects

Micropattern forming process is an efficient and low‐cost process for fabricating multifunctional surfaces in electronics, energy, and biomedical products, but this process of creating microdimples on the surface of zirconium alloys has not been investigated. Currently, there are few models describing the micropattern forming process, and these existing models have not considered the effect of roughness on forming. The influence of roughness on micropattern forming process is not to be neglected due to the size effect, especially the plowing effects caused by asperities in surface roughness during sliding process. In this article, a micropattern forming process model is developed by combining a rough plane indentation model and a plowing effects model, and the experimental study of the forming process is conducted, which can quantitatively evaluate the effects of different process parameters and different roughness of forming die on forming process. The applicability range of the developed model is obtained, and the model is capable of predicting the forming process with various process parameters and surface roughness of forming die by comparing the experiment results with the model results, which is of great significance to the design of the forming die and the improvement of the forming process.

Enhancing wear resistance of AZ61 alloy through friction stir processing: experimental study and prediction model

In this study, friction stir processing (FSP) is proposed for the treatment of AZ61 alloy, and an artificial neural network is built to predict and compare the experimental wear results. The effects of different processing parameters, including spindle speed (800–1200 rpm), traveling speed (5–15 mm min−1), and depth of press (0.8–1.2 mm) on the microstructural evolution, mechanical properties, and wear behavior are investigated. Microstructural analysis reveals a grain size of 14 ± 2 μm for the FSP1 sample, with observed shifting of x-ray diffraction (XRD) peaks, indicative of texture development. Increasing spindle and traveling speeds increase the surface roughness, as observed by average roughness (Ra) values of 68.4 nm for a rotational speed of 800 rpm, traveling speed of 5 mm min−1, and shoulder depth of 0.8 mm (FSP1) and 116.3 nm for rotational speed of 1200 rpm, traveling speed of 15 mm min−1, and shoulder depth of 1 mm (FSP9). Microhardness values increase to 113.36 Hv for FSP1 and 79. 51 Hv for FSP9 compared to 65.92 Hv for the base material (BM) sample. The decrement in hardness from FSP1 to FSP9 can be attributed to increased heat input, resulting in coarse microstructure. Wear results show that FSP1 exhibits the lowest weight loss (0.003 g) and coefficient of friction (COF) (0.28) compared to other FSP conditions and BM samples (weight loss of 0.022 g and COF of 0.68). This work demonstrates the efficacy of friction stir processing in enhancing the wear resistance of magnesium alloys.

Analysis and optimization of stamping and forming process of bearing outer ring

To address the common issues of wrinkling, tearing, and uneven wall thickness in the actual sheet metal stamping process of the outer ring of needle roller bearings, this study analyzes critical technical indicators such as forming limits, thickness distribution, and principal strains in the forming process in detail. Three-dimensional models of the concave and convex dies were constructed. The effects of different process parameters, including stamping speed, edge pressure, sheet metal thickness, and friction coefficient, on the quality of the forming parts were investigated by varying these parameters. Subsequently, the orthogonal experimental method was used to determine an optimal experimental group from multiple sets of experiments. It was found that under the process parameters of a stamping speed of 3000 mm/s, edge pressure of 2000 N, sheet metal thickness of 0.9 mm, and friction coefficient of 0.125, the forming quality of the outer ring of the bearing is ideal.

Investigation of thermal deformation and surface microstructure of wire electrical discharge machining for thin-walled rare-earth gadolinium

Rare-earth gadolinium (Gd) has excellent magnetocaloric properties. High-aspect-ratio arrays of thin-walled parts processed with rare-earth Gd are typical structures for regenerators, which are the core components of magnetic refrigeration. Wire electrical discharge machining (WEDM) offers significant advantages for manufacturing micro-structured parts. However, in WEDM, materials are thermally ablated, which leads to compromised surface quality and significant thermal deformation in thin-walled structures with low stiffness. In this study, the effects of different process parameters on the thermal deformation and surface microstructure of rare-earth Gd thin-walled parts were studied by single-factor experiments. It was found that the pulse-on time, open voltage, and water pressure had prominent effects on thermal deformation. Lowering the pulse energy can effectively reduce the thermal deformation and oxidation of the samples and improve the machined surface quality. Through the SNR analysis of the thermal deformation and surface roughness results for the optimized experimental sample, the optimal processing parameter combination of rare-earth Gd thin-walled structure regenerator with high-aspect-ratio of 38 was determined. It was proved that the thermal deformation of thin-walled parts can be controlled within 20 μm by using the combination of optimal thermal deformation parameters, including a pulse-on time of 0.5 μs, pulse-off time of 25 μs, peak current of 12 A, open voltage of 95 V, and a water pressure of 0.22 MPa.

Comprehensive investigation of capacitive deionization cells by response surface methodology

Freshwater resources are limited; thus, different technologies for desalination of brackish and seawater have been developed. Capacitive deionization (CDI) is one of the most promising desalination technologies owing to its low cost, simplicity, nonmoving parts, and low energy consumption. However, its energy consumption significantly increases with desalination of high-salinity water. In this regard, a good understanding of the effects of different process parameters on CDI energy consumption is crucial for further performance improvement. Therefore, the surface response methodology (RSM) was adopted to systematically study the effects of applying voltage, Stern layer capacity, volume and concentration of feed water, and volume of micropores on energy consumption and desalination time. The results showed that the Stern layer capacity and volume of micropores reduced desalination time by approximately 25% without significant changes in energy consumption. With the design of an improved electrode (improving the micropore structure for ion adsorption), the desalination time (Cycle) was reduced and a slight reduction in energy consumption was achieved. It can be claimed that any improvement in the physical (porosity) and electrical properties of the electrodes, results in an important increase in the performance of the CDI system.

Degradation of Carbamazepine in Water by UV-activated Sulfite Process

In this study, the degradation efficiency and mechanism of carbamazepine (CBZ), a typical emerging contaminant in water, in the UV/sulfite process were investigated. The effects of different concentrations of dissolved oxygen [ρ(DO)] on the degradation of CBZ by UV-activated sulfite were investigated. Additionally, under a simulated natural water environment-controlled initial ρ(DO) of (8.0 ±0.2) mg·L-1, the effects of different process parameters (sulfite dosages and reaction pH) and water environmental factors (the presence of HCO3-, Cl-, and humic acids) on the degradation of CBZ were comprehensively analyzed. The results showed that the UV/sulfite process efficiently degraded CBZ with a degradation rate of 85.3% during the 30 min reaction time and followed the pseudo-first order kinetic model with the constant of 0.055 7 min-1. Using the electron spin resonance detection, reactive species quenching tests, and the competition kinetics, the sulfate radicals (SO4-·) and hydroxyl radicals (·OH) in the UV/sulfite process were determined to be the main reactive species and were responsible for the degradation of CBZ with contribution rates of 43.9% and 56.1%, respectively. In addition, the degradation efficiency of CBZ decreased with the increasing concentration of HCO3-, and the presence of Cl- had little effect on the degradation of CBZ, whereas the presence of humic acids significantly inhibited the degradation of CBZ. Moreover, the accumulation of sulfate during the reaction was significantly lower than the limit of the Standard for Drinking Water (GB5749-2022). Additionally, the sulfite consumption rate constant was 0.004 4 min-1, which was significantly lower than the degradation rate constant of CBZ, indicating that sulfite could be activated efficiently by UV light to degrade CBZ in water.

Parametric study of WEDM of titanium grade 12 using RSM and desirability approach

The present experimental study aims to scrutinize the effect of different process parameters on the material removal rate (MRR) and surface roughness (SR) of titanium grade 12 alloy during wire electro-discharge machining (WEDM) using response surface methodology. Four parameters (pulse-on time, pulse-off time, wire feed and gap voltage) and three levels of each selected variable are considered to conduct the experimental work. Depending on experimental results, a mathematical model is generated for both MRR and SR. An analysis of variance (Anova) study is performed to find significant process parameters. The Anova results show that the developed models for both MRR and SR are significant, and pulse-on time is found to be the most significant parameter. Additionally, the desirability approach is used to scrutinize the single-objective and multi-objective criteria of response variables. The desirability functions for all of the cases are found to be 1. The maximum MRR is observed to be 12.4845 mm3/s, while the minimum value of SR is found to be 1.4911 μm. For multi-objective optimization, the maximum value of MRR and the minimum value of SR are obtained as 12.0942 mm3/min and 1.7167 μm, respectively. Finally, the surface morphology of the machined surfaces is examined using scanning electron microscopy micrographs.

Optimization of ultrasound-assisted extraction of Nigella sativa seed oil for enhancement of yield and antioxidant activity

The seeds of Nigella sativa have been shown to contain a number of constituents that have nutritional and therapeutic characteristics. The oil extracted from the seeds of Nigella sativa has been traditionally used in food systems with reference to its medicinal properties. The different bioactive compounds present in the Nigella sativa seed oil consist of polyphenols which offer a fair amount of antioxidant activity to the oil. Most of these bioactive compounds are generally heat sensitive and prone to oxidation. During the processing and storage, there is loss of antioxidant activity of the oil and the associated bioactivity. This occurs primarily due to the effects of temperature and other environmental factors during processing and storage. Under this background, this study was undertaken with the aim of extracting the Nigella sativa seed oil in order to ensure the improved retention of antioxidant and bioactive characteristics in the essential oil. The extraction of Nigella sativa seed oil was carried out using ultrasound-assisted extraction technique using hexane as solvent. The process was optimized using response surface methodology in order to enhance the yield and antioxidant activity of the extracted Nigella sativa seed oil. The effect of different processing parameters was evaluated on the yield and antioxidant activity. The process variables included the extraction temperature, extraction time and solvent concentration. It was observed that all the factors had significant effect on the yield and antioxidant activity of the extracted Nigella sativa oil. The optimized conditions for maximizing the yield and antioxidant activity obtained were a solvent concentration of 42.82 mL/5 g of sample, the extraction temperature of 69.09 °C and extraction time of 86.60 min, which were validated and found close to the experiment values. Under this set of conditions, the yield was maximized to 34.53% with enhanced antioxidant activity, having IC50 value of 203.56 µg/mL.

Optimization of Pyrolysis Process Parameters for Fuel Oil Production from the Thermal Recycling of Waste Polypropylene Grocery Bags Using the Box–Behnken Design

The impact of dumping plastic waste is realized in different ecosystems of the planet. Several methods have been adopted to dispose of these wastes for energy recovery. This study, for the first time, proposed the Box–Behnken design technique to optimize the pyrolysis process parameters for fuel oil production from waste polypropylene (PP) grocery bags using a semibatch-type pyrolytic reactor. The semibatch-type pyrolytic reactor was developed and employed to produce fuel oil from waste PP grocery bags. The effect of different process parameters on fuel oil production was comprehensively analyzed using the response surface methodology (RSM) with the conjunction of the Box–Behnken design (BBD). The BBD facilitates the prediction of the response variables with respect to changes in the input variables by developing a response model. The BBD was used to optimize the process parameters, such as the reaction temperature (400–550 °C), nitrogen flow rate (5–20 mL min−1), and substrate feed rate (0.25–1.5 kg h−1), and their effect on the responses were observed. The optimum response yields of the fuel oil (89.34 %), solid residue (2.74%), and gas yield (7.92%) were obtained with an optimized temperature (481 °C), a nitrogen flow rate (13 mL min−1), and a feed rate (0.61 kg h−1). The quadratic model obtained for the fuel oil response denotes the greater R2 value (0.99). The specific gravity and calorific value of the fuel oil were found to be 0.787 and 45.42 MJ kg−1, respectively. The fuel oil had higher research octane number (RON) (100.0 min) and motor octane number (MON) (85.1 min) values. These characteristics of the fuel oil were matched with conventional petroleum fuels. Further, Fourier transform infrared spectroscopy (FT-IR) and gas chromatography–mass spectroscopy (GC-MS) were used to analyze the fuel oil, and the results revealed that the fuel oil was enriched with different hydrocarbons, namely, alkane (paraffins) and alkene (olefins), in the carbon range of C4–C20. These results, and also the fractional distillation of the fuel oil, show the presence of petroleum-range hydrocarbons in the waste PP fuel oil.

Development of flexible packaging sheet from aluminium foil laminated jute web

This study develops an impermeable and flexible sheet for food packaging using aluminium foil and jute web. A hot melt sheet is used for laminating foil with a jute web. A simple manufacturing process has been suggested. The effect of different process parameters has been studied and optimized. The optimized calendaring temperature (top/bottom), pressure, and speed are 150/120°C, 15 kPa, and 1 m/min, respectively. Preheating and three consecutive runs show higher tenacity. This hybrid sheet uses around 88% or 78% jute (by weight) in one and both side laminated sheets, respectively. The failure mechanism shows the role of fibre-to-foil bonding. The developed fabric is lighter and more cost-effective than jute woven laminated fabric. The packet from hybrid fabric is sufficiently strong and pliable with excellent barrier properties to use as a hygienic sheet for food packaging.

Influence of atmospheric plasma spraying process parameters on microstructure and properties of yttrium oxide coatings

Y2O3 coatings were fabricated on using atmospheric plasma spraying (APS). The effects of different process parameters on the microstructure and properties of the coating were analyzed. The results show that the overall morphology of Y2O3 coatings are smooth at high spraying power, low spraying distance and low primary gas flow rate, which is consistent with the change trend of porosity and hardness. The minimum porosity of coating is about 1.4%. The roughness of coatings isn’t sensitive to changes in parameters. Y2O3 coatings have excellent corrosion resistance. The smaller the porosity of Y2O3 coating, the better the corrosion resistance.

Parameter and Deposition Strategy Analysis for WAAM Processing of AISI 410 Stainless Steel

Wire + Arc Additive Manufacturing (WAAM®) is an additive manufacturing (AM) process capable of producing near net shape parts while reducing costs and thus gathering increased attention from researchers and manufacturers. Although a significant amount of work has already been published relating to the WAAM processing of stainless steels, it was mainly focused on austenitic stainless steels, with martensitic grades still lacking investigation. AISI 410 is a martensitic stainless steel that, due to its high hardness, demonstrates high wear resistance, being used in parts requiring high resistance to abrasion. Processing this material by WAAM allows for the creation of near net shape parts, leading to a reduction in machining, while at the same time allowing the creation of complex geometries which would be difficult, or outright impossible to obtain otherwise. In this work the effects of different processing parameters on WAAM processed AISI 410 steel, using Cold Metal Transfer (CMT) welding equipment, were investigated, as well as different deposition strategies for the fabrication of a test artifact using an AM software. It was demonstrated that it is possible to process AISI 410 steel by WAAM using an AM software to define deposition strategies and parameters based on the part design and previous experimental trials. The goal to deposit a complex part with high hardness and tensile strength, especially attractive properties to parts requiring high resistance to wear was achieved.

The Analysis of Vibration Resistance of the Shape and Braided Laminated Manufactured Structure Using Taguchi Method

In this study, the L934 orthogonal table of the Taguchi method is used as a systematic parameter analysis. A rapid prototyping machine (RPM, manufactured by the research team) and fused deposition modeling (FDM) are used to make anti-vibration test specimens and to analyze the effect of different process parameters, such as weaving and shaping, on vibration resistance. Hopefully, various application fields will be extended via the deposition method. The impact test is executed by dropping a steel ball onto each test piece which is connected to an accelerometer and a PW700 spectrometer for extracting the frequency response during the impact. The vibration performance under different process parameters is analyzed. Several parameters that may affect anti-vibration performance are selected under the existing process, namely weaving method (A), deposition thickness (B), weaving density (C) and cross weaving per n-layer (D). The policy is to evaluate the required time period to restore to the steady state after impact. Hence, the shorter the convergence time is, the better the specimen resists the vibration. The experimental results show that the build-up layer thickness and the weaving density are the main control factors that affect the anti-vibration ability most. The process parameter A3B1C1D2 obtains the best vibration resistance performance.

Serial artificial neural networks characterized by Gaussian mixture for the modelling of the Consigma25 continuous manufacturing line

In this research, the Consigma25 Continuous Manufacturing (CM) Line is statistically analysed and modelled. First, the main effects plot is employed to examine the effects of different process parameters on the granules size and the tablet strength. Second, a modelling framework based on serial interconnected artificial neural networks is proposed to model the CM line by mapping these parameters to the granules size and the tablet strength. Then, Gaussian mixture models (GMMs) are adopted to characterize the error resulting from these networks in a way that helps in extracting more information and, as a result, improves the performance of the modelling framework. Validated on an experimental data set, the proposed interconnected framework can anticipate the characteristics of the granules and tablets produced using a specific blend of excipients with an absolute error percentage value of less than 12.3%. In addition, the GMMs have improved the predictive performance by 9.7%.