Optimal Process Parameters Research Articles

DETERMINATION OF OPTIMAL PARAMETERS OF SINTERING OF ROLLING SCALE

This article presents the results of studies conducted to determine the optimal parameters of sintering of rolled scale in a mixture with iron-containing steelmaking waste. The conducted studies of sintering of rolled scale have shown that the gas permeability of the charge depends on a number of physical properties, the size and shape of the grains, the amount of return, the height of the charge layer, and the moisture content of the charge. The initial gas permeability strongly depends on the degree of humidification of the agglomeration charge, especially when sintering small classes of materials under study. The maximum gas permeability of the charge is ensured with an optimal granulometric composition of the charge, which is characterized by an average equivalent diameter: the higher this indicator, the higher the gas permeability of the charge. The value of the surface tension reaches its maximum at a certain moisture content of the charge, which is the optimal moisture for this charge. By increasing the amount of return during agglomeration, the vertical sintering rate increases and the quality of the agglomerate improves. These factors lead to an increase in the productivity of sintering plants. According to the results of the study, the optimal parameters of the sintering sintering process of rolled scale in a mixture with iron-containing steelmaking waste were worked out. It is established that the optimal amount of return is the use of 20 % of the mass of the sintering charge at the optimal height of the sintered layer of 300 mm. As a result of the conducted research, the following optimal indicators were achieved: mechanical strength – 70.2 %, sintering rate – 28.7 mm/min, specific productivity – 1.75 t/m2·hour. Keywords: Rolling scale, agglomeration, optimal parameters, sintering, return, layer height.

Impacts of Zirconium Carbide Incorporated Magnesium Alloy Nanocomposite on Wear Properties

In the study, zirconium carbide nanoparticle (ZrC-50 nm) incorporated magnesium alloy (AZ61) nanocomposite was prepared by liquid state stir cast process, and its wear properties were evaluated by different load (U), sliding speed (V), and sliding distance (W). The impacts on wear rate (WR) and coefficient of friction (COF) of AZ61 alloy nanocomposite were studied. With the support of a pin-on-disc wear tester, the dry sliding wear characteristics were measured. Moreover, to find the optimum process parameter on minimum WR and better COF characteristics, the L27 orthogonal array utilized U, V, and W as the input factors, and the WR & COF were treated as output responses. Based on the analysis, load was found to be the most dominant input factor that influences the WR and sliding distance was the factor for fixing the COF.

Experimental investigation of material extrusion additive manufacturing of copper with high powder loading rate

Beam-based additive manufacturing has challenges in fabricating pure copper due to high reflectivity. Material extrusion additive manufacturing (MEAM) avoids these issues with low costs, making it suitable to fabricate complex structures in pure copper. In this work, the effects of several printing parameters on the geometry of the samples are studied from single line, thin wall to cube using homemade copper feedstocks with high powder loading rate (65 vol%). The results show that the single line is most affected by layer thickness, while the thin wall has stricter requirements for printing temperature and printing speed. The geometric accuracy of the cube demonstrates large parametric tolerance due to the overlap and support between the lines. Central composite face-centered (CCF) design and central composite design (CCD) are used to analyze and optimize process parameters for densification. The measured porosity at the optimized printing (printing temperature = 177 °C, air gap = −0.05 mm, layer thickness = 0.3 mm) and sintering parameters (sintering temperature = 1045 °C, holding time = 4 h) is in good agreement with the predicted values. Air gap and sintering temperature have the greatest influence on the porosity, and other parameters within a certain range of on-demand adjustments do not have a significant effect. The ultimate tensile strength and elongation of the sintered samples under the optimal parameters are 153.9 ± 6.1 MPa and 31.36 ± 3.24%, respectively. No printing defects are found at the fracture and the elongation is good, showing the effectiveness of the parameter optimization.

EXPERIMENTAL AND OPTIMIZATION-BASED ANALYSIS TO MAXIMIZE MECHANICAL-RELATED ATTRIBUTES OF FRICTION STIR WELDED CDA101 CU ALLOY JOINTS

This paper deals with the identification of optimized process parameters for FSW of 6[Formula: see text]mm thick CDA 101 Cu alloy plates. Three distinctive parameters, the tool’s traverse speed, rotational speed, axial load, have been considered as self-reliant variables for formulating a numerical model based on nonlinear regression-type approach, with the objective of anticipating mechanical attributes of joints. From the surface- and contour-type plots, it was revealed that the axial load in combination with rotational speed has played a dominant role in influencing the tensile and yield strength of the CDA101 Cu alloy joints. At the same time, the traverse speed of the tool has played a dominant role in enhancing the ductility of the CDA101 joints through the generation of ample volumes of frictional heat, which in turn have facilitated both coarsening of grain structures and softening of materials in an ideal manner. Employing tool rotational speed, traverse speed and axial load in the ranges of 1750–1900[Formula: see text]rpm, 23–27[Formula: see text]mm/min and 5.75–6.5[Formula: see text]kN, respectively, was found to enhance the tensile strength of the CDA101 Cu alloy joints. FSW process parameters attained through the numerical meta-model of RSM have led to the attainment of the highest value of tensile strength of 209.5[Formula: see text]MPa together with a 141.4[Formula: see text]MPa yield strength with very minimal fitting errors of 0.28% and 0.52%, respectively. A collection of additional experimental data has been employed to verify the formulated empirical-based formula and additionally, an entirely different optimization technique namely PSO (i.e. particle swarm optimization) was implemented for comparison and validation purposes. The formulated meta-model of RSM generated the largest value of % of elongation of 14.23%, though the relative percent error was around 1.988%, which was slightly larger than that of the value (i.e. 14.11%) generated by PSO, with a relative error of 0.58%.

Manufacturing of Sustainable Composite Materials: The Challenge of Flax Fiber and Polypropylene.

The widespread use of synthetic composite materials has raised environmental concerns due to their non-biodegradability and energy-intensive production. This paper explores the potential of natural composites, specifically flax-polypropylene, as a sustainable alternative to traditional composites for semi-structural applications. In fact, the mechanical properties of flax-polypropylene composites are similar to synthetic ones (such as those made with E-glass fibers). However, processing challenges related to fiber-matrix interaction and material degradation necessitate suited process parameters for this sustainable type of material. For this reason, this review highlights the importance of optimizing existing manufacturing processes, such as hot press molding, to better accommodate the specific characteristics of polypropylene-flax composites. By refining the parameters and techniques involved in hot press molding, researchers should overcome current limitations and fully capitalize on its potential to produce composite materials of optimal quality. Therefore, a comprehensive literature assessment was conducted to analyze the properties and processing challenges of flax-polypropylene composites. Key process parameters affecting the material's performance are identified and discussed. By optimizing process parameters for flax-polypropylene composites, it is possible to develop a sustainable and high-performance material with a reduced environmental footprint. Further research is needed to scale up production and explore different applications for this sustainable composite material.

Enhancing bending strength in continuous drive friction welding of PEEK polymer cylinders through the innovative progressively increased welding area method

The continuous drive friction welding (CDFW) stands out for its low energy consumption within the welding realm. Polyetheretherketone (PEEK) represents a high-performance engineering thermoplastic, falling under the polyaryletherketone family. Renowned for its outstanding mechanical, thermal, and chemical attributes, PEEK finds utility across a diverse array of industries. However, the discovery of numerous voids at the weld interface has revealed limitations in the mechanical properties of PEEK welded samples. This study introduces an innovative approach named progressively increased welding area (PIWA) method, to mitigate voids within the weld interface. In general, the Taguchi method was used to optimize the process parameters of CDFW of dissimilar PEEK round rods to reduce random efforts by the trial-and-error method. It was found that the proposed PIWA method can definitely enhance the bending strength of rotational friction welded samples due to reduction of voids inside the weld interface. The optimal process parameters for the CDFW with the PIWA method involve a rotational speed of 2500 rpm, a cone angle of 120°, a cone top width of 8 mm, and a feed rate of 0.1 mm/s. The most influential factor affecting the bending strength of the PEEK welded samples is the feed rate, followed by cone angle, rotational speed, and cone top width. Specifically, the contribution ratios for feed rate, cone angle, rotational speed, and cone top width are about 71 %, 20 %, 7 %, and 2 %, respectively. The confirmation tests showed that the bending strength of the PEEK welded samples using optimal process parameters can be increased by approximately 68 % compared with the maximum bending strength of 180 MPa using the conventional method with a cone angle of 180° The proposed PIWA method has industrial applicability and practical value because this technique can enhance the mechanical properties of PEEK welded samples under low environmental pollution and energy consumption.

Achieving low-porosity AlSi10Mg cladding layers for the additive repair of aluminum alloy parts by directed energy deposition

Directed Energy Deposition (DED) has broad application prospects for repairing damaged aluminum alloy parts such as piston aero-engine casing. However, due to the low laser absorptivity and the complex thermal cycle process, it is challenging to obtain aluminum alloy cladding layers with high-quality morphology and low-porosity by DED method. In this work, a series of individual stages of DED process are studied during single-tracks overlapping and layers stacking. Correspondingly, the within layer scanning strategy, inter-layer stacking strategy, and process parameters are examined carefully. Using the proposed DED processing flow that combines substrate preheating with intermittent process, the deposited layers without balling and collapse are successfully achieved. Furtherly, the bi-directional scanning strategy for single-tracks overlapping within layer is proposed to compensate the thickness nonuniformity caused by heat accumulation. The inter defects identified as “lack of fusion” and “gas pores” are observed in the cladding layers with uniform surface. By analyzing the pore formation mechanism and considering the energy distribution and re-melting, the multi-layer offset stacking strategy is proposed to inhibit the porosity to 0.25 %. Combined with the optimized process parameters, the porosity is reduced up to 0.09 %, ensuring the density of the DED deposition coating. This work provides new pathway and direct guidance for fabricating high-quality AlSi10Mg cladding layers during the DED repairing of valuable aluminum alloy parts.

Precision Electrochemical Micro-Machining of Molybdenum in Neutral Salt Solution Based on Electrochemical Analysis

Molybdenum is an important material in modern industry, widely used in extreme environments such as rocket engine nozzles and microelectrodes due to its high melting point, excellent mechanical properties, and thermal conductivity. However, as a difficult-to-machine metal, traditional machining methods struggle to achieve the desired microstructures in molybdenum. Electrochemical machining (ECM) offers unique advantages in manufacturing fine structures from hard-to-machine metals. Studies have shown that molybdenum exhibits a fast corrosion rate in alkaline or acidic solutions, posing significant environmental pressure. Therefore, this study investigates the electrochemical machining of molybdenum in neutral salt solutions to achieve high-precision microstructure fabrication. First, the polarization curves and electrochemical impedance spectroscopy (EIS) of molybdenum in NaNO3 solutions of varying concentrations were measured to determine its electrochemical reaction characteristics. The results demonstrate that molybdenum exhibits good electrochemical reactivity in NaNO3 solutions, leading to favorable surface erosion morphology. Subsequently, a mask electrochemical machining technique was employed to fabricate arrayed microstructures on the molybdenum surface. To minimize interference between factors, an orthogonal experiment was used to optimize the parameter combination, determining the optimal machining process parameters. Under these optimal conditions, an array of micro-groove structures was successfully fabricated with an average groove width of 110 μm, a depth-to-width ratio of 0.21, an aspect ratio of 9000, and a groove width error of less than 5 μm.

Autoencoder-based inverse design and surrogate-based optimization of an integrated wet granulation manufacturing process

In pharmaceutical manufacturing, integrating model-based design and optimization can be beneficial for accelerating process development. This study explores the utilization of Machine Learning (ML) techniques as a surrogate model for the optimization of a three-unit wet-granulation based flowsheet model for solid dosage form manufacturing. First, a reduced representation of a wet granulation flowsheet model is developed, incorporating a granulation and milling process, along with a novel dissolution model that accounts for the effect of particle size, porosity, and microstructure on dissolution rate. Two optimization approaches are compared, including an autoencoder-based inverse design and a surrogate-based forward optimization. Both methods address the bi-objective problem of maximizing dissolution time and product yield by identifying the optimal granulation and mill process parameters. For this case study, both approaches were effective and incurred a similar computational cost, averaging under 4 s. However, the autoencoder approach offers an advantage through dimensionality reduction, a feature not available in surrogate-based optimization. Dimensional reduction is particularly beneficial for complex process designs with numerous inputs and outputs. The lower dimensional representation helps improve process understanding through enhanced visualization of the process design space and facilitates feasibility studies involving multiple constraints. The autoencoder-based inverse design introduced in this work showcases an implementation of AI and ML in pharmaceutical process development, demonstrating the potential to enhance process efficiency and product quality in complex manufacturing scenarios.

Photo Electrocatalytic Water Splitting Using Sn Doped In2S3 Homologous Series Synthesized in Oxygen Deficient Flame

AbstractThe innovative development of reactive‐spray systems for gas‐phase production of metal sulfides are potential materials for next‐generation technologies. These flame‐synthesized sulfides (doped, functionalized, and heterogeneously mixed derivatives) hold significant potential as photocatalysts for water splitting. The knowledge acquired from nonaqueous precursor‐solvent and high‐temperature aerosol chemistries, optimal process parameters are established to generate In2‐(4/3)xSnxS3, solid‐solutions. The thermally driven reducing gas‐phase reactions are controlled through fuel/oxygen ratio. Particles characterizations (X‐ray diffraction, transmission electron microscopy (TEM) and imaging) revealed structural stability and crystallinity. The In2‐(4/3)xSnxS3, at higher Sn doping had enhanced photoexcitation. Donor‐acceptor levels within the material facilitated electron‐hole pair trapping, crucial for redox reactions. With suitable band gap energies for water oxidation (1.91.1 eV) closely matched flat band potentials (4.384.67 eV) for redox reactions. The powder characterization showed 8% In2O3 in InSn0.75S3 after photocatalysis due to S‐degradation in the initial light “on/off cycles”. The pioneering process of employing oxygen‐deficient reducing flame enabled a series of photo‐catalytically active metal sulfide nanoparticles with work function energies in the range of 5.195.37 eV. This synthesis strategy holds the potential for impactful advancements in both industry and R&D, addressing the urgent need for new materials capable of inducing water oxidation under visible light.

Synergistic regulation of microstructure, properties, and abrasive wear mechanism of a medium carbon dual phase steel for plowshares

In this study, a new medium carbon dual phase (DP) steel for plowshares is prepared. The quenching and partitioning process of the medium carbon steel is designed and optimised using the constrained carbon equilibrium model. The optimised process parameters are quenching temperature of 880 °C, quenching bath temperature of 190 °C and partitioning temperature of 350 °C. The microstructure of the acicular martensite matrix with 13% retained austenite was prepared, so that the good mechanical properties of tensile strength of 2007 MPa, yield strength of 1689 MPa, elongation of 11% and impact energy of 12 J are obtained. The multi-scale characterisation and abrasive wear experiments are carried out to investigate its microstructural evolution and wear mechanism under simulated working conditions. The results show that the coordinated deformation of retained austenite and martensite, as well as the trip effect, endows it with ultra-high strength and good plasticity. The recurring process of formation and spalling of the hardened layer is the main wear pattern of this medium carbon DP steel. The synergism of twinning formation and (Ti, Mo)C precipitation enhances wear resistance of this medium carbon DP steel.

Statistical modeling and optimization of process parameters for additive manufacturing of styrene–ethylene–butylene–styrene block copolymer parts using solvent cast 3D printing technique

AbstractAdditive manufacturing of thermoplastic elastomers is challenging using fused deposition modeling due to their high melt viscosity, low column strength, and poor fusion among layers. Solvent‐cast 3D printing (SC‐3DP) is an efficient alternative to successfully 3D print such materials. However, selection of suitable 3D printing parameters is crucial to realize parts with optimum physicomechanical properties. In this work, statistical modeling and SC‐3DP parameter optimization for styrene–ethylene–butylene–styrene (SEBS) block copolymer were performed. The effect of 3D printing process parameters on shrinkage, relative density, and tensile strength was analyzed using response surface methodology. Experiments were planned as per central composite design and analysis of variance was performed to evaluate the significant parameters. SEBS content in the polymer solution significantly affected the shrinkage of SC‐3DP samples. Moreover, relative density and tensile strength were significantly affected by print speed and layer height. A significant interaction between print speed and layer height was also noticed for tensile strength and relative density of printed samples. Multi‐objective optimization using genetic algorithm was also performed to minimize shrinkage and maximize relative density and tensile strength. Finally, a case study was conducted comparing the physicomechanical properties of SC‐3DP samples printed at optimized process parameters and compression molded samples.Highlights Statistical models were developed using response surface methodology. Genetic algorithm based multi‐objective optimization was performed. Optimum solvent‐cast 3D printing (SC‐3DP) process parameters were determined.

Experimental investigation on the surface topographical improvement of selective laser melted SS316L using abrasive flow finishing

Selective laser melting (SLM) offers a precise fabrication of intricate geometries that are not achievable with conventional manufacturing processes. However, surface imperfections like adhered powder particles, waviness, and other anomalies impede the intended functional application and demand additional post-processing steps. Abrasive flow finishing (AFF) process is extensively used for enhancing the surface topography of SLM-built parts by reciprocating a viscoelastic polymer abrasive medium. The cost of commercial abrasive media is expensive, needs costlier and heavy equipment, has little tolerability, and releases hazardous gases during its preparation. In this work, a biopolymer-based abrasive media is developed in-house and employed to examine the surface topographical changes of SLM-built SS316L flat features. Compared to commercial abrasive media, the cost of the developed abrasive media is much lower, does not require expensive equipment, and is eco-friendly. The effect of extrusion pressure, number of finishing cycles, and size of the abrasive particles on the percentage change in areal surface roughness (%ΔSa) and waviness (%ΔWa) was studied. From the analysis of variance, irrespective of %ΔSa and %ΔWa, it was found that the number of cycles was the most contributing process parameter, followed by extrusion pressure and abrasive particle size. The optimised process parameters resulted in a maximum %ΔSa and %ΔWa of about 90.1 % and 66.25 %, respectively, from the initial as-built areal surface roughness of 6.6 ± 0.2 μm and areal surface waviness of 7.7 ± 0.4 μm.

Physicochemical and Morphological Changes in Long-Grain Brown Rice Milling: A Study Using Image Visualization Technologies

This study evaluated the changes in physicochemical properties and appearance quality of long-grain rice during the grinding process using image technologies and aimed to provide reference for future research. The brown rice milling process was divided into three stages, and flatbed scanning, scanning electron microscopy (SEM), X-ray micro-computed tomography (micro-CT), low-field nuclear magic resonance (LF-NMR), and headspace–gas chromatography–ion mobility spectrometry (HS–GC–IMS) were employed to examine the physicochemical and volatile properties of the samples. Results revealed a continuous increase in the degree of milling, with a broken rice rate and a whiteness value increasing by 50.84% and 21.13%, respectively, compared with those during the initial stage; dietary fiber and vitamin B1 contents were reduced by 54.41% and 66.67%, respectively. The image results visualized showed that the cortex of brown rice was gradually peeled off with the increase in milling degree; the cortical thickness was gradually reduced, the endosperm was gradually exposed, and the surface was smoother and shinier. T2 populations exhibited a shift toward longer relaxation times, followed by a decrease in relaxation time during the milling process. Additionally, 31 target compounds impacting rice flavor, mainly ketones, alcohols, and esters, were identified, and the concentration of volatile substances in the B region decreased with the reduction in the bran layer; the concentration of volatile substances in the C region provided rice flavor, which increased with the milling process. This study showed changes in the physicochemical properties and appearance quality of long-grain brown rice during milling. Furthermore, the use of various image processing techniques offers significant insights for optimizing processing parameters and enhancing overall quality and taste.

Research on the thermal energy environment and process parameters of milling process in ceramic art design

In ceramic art design, milling technology is the key processing technology, which directly affects the quality and artistic expression of ceramic products. However, the thermal energy environment generated in the milling process has a significant impact on the material characteristics and machining results. This study aims to explore the influence of the thermal energy environment on the ceramic art design during the milling process, optimize the process parameters, and improve the processing efficiency and product quality. Experiments with different milling speed, feed rate and cutting depth were designed to compare and analyze the change of thermal environment by combining experiment and simulation. The influence of thermal energy on ceramic machining quality was evaluated by monitoring the temperature distribution in the cutting process with thermal imaging technology and combining with the experimental data of material properties. The experimental results show that the temperature increase in milling process is closely related to the cutting speed and feed rate, and proper control of the thermal energy environment can significantly reduce the crack generation rate and improve the surface finish of ceramic materials. The optimized process parameters make the temperature control in the milling process within the ideal range, thus realizing the processing of high quality ceramic products. Through reasonable optimization of process parameters, the heat energy in the processing process can be effectively controlled, which helps to improve the overall quality and artistic value of ceramic works.

Fluoride removal using a rotating anode electro-coagulation reactor: Parametric optimization using response surface methodology, isotherms and kinetic studies, economic analysis and sludge characterization

The presence of fluoride in drinking water can cause various diseases, such as dental fluorosis and skeletal fluorosis. The present study aims to intensify the fluoride removal using a rotating anode electro-coagulation (EC) reactor with providing the proper hydrodynamics conditions. This fluoride removal is modeled and optimized using Response Surface Methodology (RSM) and central composite design (CCD) with varying operational parameters (rotation speed: 20–80 RPM, current: 0.2–1.0 A, initial fluoride concentration: 8–40 mg/L and time: 15–75 min). The maximum fluoride removal is obtained as 96.87% (predicted) and 95.40% (experimental) for the optimized process parameters, initial concentration of 32 mg/L, 0.8 A current, 60 min, and 60 RPM of rotating speed. Kinetic analysis reveals that the removal process adheres to a second-order kinetic model, suggesting that the rate of fluoride removal is dependent on the concentration of fluoride ions present. Isothermal studies indicate that the effective sorption of fluoride onto the generated flocs follows a sips isotherm. The optimal cost analysis is carried out to determine the operational cost as 0.256 USD/m3 for F removal of 93.49% at initial concentration 24 mg/L, time 50 min, current 0.7 A, and rotation 70 rpm and presenting a cost-effective solution for fluoride mitigation. Further, characterizations of the resultant sludge through X-Ray Diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FTIR), and the Toxicity Characteristic Leaching Procedure (TCLP) confirmed the safe disposal potential of the sludge. The findings show a promising approach for fluoride removal, combining high efficiency, economic viability, and environmental safety.

High temperature electropalsticity in Aermet100 steel by decoupling electron wind effect

Aermet100 ultra-high strength steel (UHSS) is one of the highest strength-plasticity-matched metallic materials. It is widely used in critical load-bearing components in aerospace and weaponry. Compared to traditional forging processes, electropulsing assisted forming technology significantly enhances manufacturing efficiency and forming limits. Particularly in the forming of hard-to-deform materials into complex structures, it demonstrates significant application potential. However, quantitative studies on the decoupling of electron wind effects during high-temperature deformation and their impact on microstructural evolution, deformation mechanisms, and mechanical properties remain few reported, resulting in limiting the ability to select optimal process parameters in electropulsing assisted forming technology to precisely control material structure and properties. In this paper, the impact of varying degrees of electron wind effects on flow stress through high-temperature compression tests was investigated. The evolution of the microstructure was analyzed in conjunction with the thermodynamic and kinetic mechanisms of recrystallization. Moreover, the hitherto unexplained relationship between the activation of slip systems and texture components in Aermet100 UHSS is examined. Results indicate that with the enhancement of the electron wind effect, the flow stress of Aermet100 UHSS is reduced by 59.4 %. The electron wind effect not only reduces the activation energy for recrystallization but also enhances vacancy concentration, dislocation climb diffusion flux, and driving force, thus promoting continuous dynamic recrystallization. Furthermore, as the intensity of the electron wind effect increases to 0.85 Ew and above, S and Brass textures are observed for the first time. It is notable that the Dillamore texture, Brass texture, and S texture respectively activate specific slip systems (1‾ 10)[11 1‾], (0 1‾1‾)[11 1‾] and (110)[1‾ 11‾] during the hot deformation process of Aermet100 UHSS. This investigation sheds new insight into tailoring high temperature electroplasticity by regulating electron wind effects.

Integrated framework of multi−physics mechanism models for gas−powder flow, molten pool evolution and part deformation in high alloy steel additive manufacturing process

Multi−physics numerical models for metal additive manufacturing (MAM) could replace the expensive trial−and−error experiments, reveal the mechanisms of printing process, and provide an effective means of optimizing process parameters and mitigating part defects. However, the existing simulations of MAM process seldom consider the coupling effects between multiple recursive processes. There is an urgent need to overcome the dilemma of limiting MAM process simulation to a localized single sub−process. For directed energy deposition (DED) additive manufacturing process, the integrated simulation framework proposed in this study consists of a gas−powder flow model, a heat and fluid flow model, and a sequentially coupled thermal–mechanical model, which can be used to predict the feedstock feeding process, the evolution of molten pool, and the residual deformations of metal part, respectively. The accurate results of the three recursive sub−processes can be obtained by delivering the validated parameters between models. Corresponding experiments are conducted to verify the accuracy of the integrated framework based on 12CrNi2 alloy powders. The deviation of the predicted focal distance of powder streams is 5.14 %, and the deviations of the predicted molten pool height and width are all less than 8.5 %. The integrated framework could rapidly and accurately predict the residual deformation tendency and the position where the maximum deformation occurs. For single−track and eight−layer line deposition, the deviations of the predicted maximum deformation are all within 0.1 mm. The integrated framework could efficiently provide accurate and comprehensive solutions for optimizing DED process.

Evolution and modeling of texture changes and drying kinetics of bamboo shoots under high-humidity air-impingement blanching.

This study investigated the effect of hot water blanching (HWB), high-humidity air-impingement blanching (HHAIB), different HHAIB blanching times (2, 4, 6, 8, and 10min), and different HHAIB blanching temperatures (80, 85, 90, and 95°C) on texture quality, lignin content, weight loss, color, microstructure, and drying kinetics of bamboo shoots. After HWB treatment, the lignin content of bamboo shoots was apparently lower than that of HHAIB and the samples obtained the highest weight loss value of 6.13%. Both the texture values (brittleness and chewiness) and lignin content of bamboo shoots exhibited an overall downward trend as the HHAIB blanching time and blanching temperature increased. Specifically, the lignin content of bamboo shoots decreased from 5.59% to 4.58% with an increase in HHAIB blanching time from 2 to 10min and dropped from 5.48% to 4.63% as HHAIB blanching temperature increased from 80 to 85°C, respectively. The lignin content was proved to be positively correlated (p<0.05) with texture attributes (brittleness and chewiness). A second polynomial model was obtained for fitting the variation kinetics of lignin content during thermal processing. Reducing the HHAIB blanching time and blanching temperature would obtain a lower weight loss and a better color performance (ΔE and L*). Additionally, microstructure observation revealed that the distribution density of microchannels initially increased and then decreased with the extension of blanching time, while it continuously became firmer as HHAIB blanching temperature increased. Overall, the optimal processing parameters were achieved under the HHAIB blanching temperature of 85°C for 6min, ensuring a high-quality performance of bamboo shoot products.

A nanomodified-ultrasonic method to improve the shear strength of adhesively bonded composite joints

Adhesive bonding method has become prevalent in joining composite structures in the aerospace and automotive industries. The bonding quality is critical in terms of service safety. This research proposed a nanomodified-ultrasonic method to enhance the shear strength of adhesively composite joints. Functional multi-walled carbon nanotubes (MWCNTs) were dispersed into the adhesive, followed by the ultrasonic vibration during the bonding process. Orthogonal experiments considering different combinations of the NWCNT concentrations, ultrasonic power, and ultrasonic time were conducted to investigate the effect of different factors and to obtain the optimal processing parameters. Results indicate that the nanomodified-ultrasonic method is beneficial to the composite bonded joint and a maximum increase of 75.1% in shear strength was achieved. Furthermore, the bondline before testing and fracture surface were critically analyzed to illustrate the enhancement mechanisms.