Interaction Effects Of Parameters Research Articles

Assessment of the Effect of Quench Probe Parameters on Cooling Behavior by Numerical Simulation

The cooling severity of liquid quenchants is generally assessed by measuring the cooling rate inside a metallic probe. In the present study, numerical simulation of heat transfer was carried out to assess the effect of quench probe parameters on the cooling behavior. Simulations were carried out for different combinations of size, geometry, material and boundary heat transfer coefficients. Factorial experiments were carried out to assess the significance of probe parameters on mean cooling rate of the probe during quenching. Factorial analysis results showed significant influence of size and material of the probe on the mean cooling rate during quenching. The percentage contribution of the size and material parameters to the overall effect of various parameters on the mean probe cooling rate were about 45 and 16 pct. respectively. Among the interaction effects of various parameters, the interaction among probe material and size was found to be most significant. Factorial experiments showed that the effect of probe geometry on the mean cooling rate was insignificant particularly for probes of higher thermal conductivity. It was found that for a given geometry, the cooling parameter (L2CR/α) increased exponentially with increase in Biot number (Bi). The effect of probe geometry on mean cooling rate was significant when Bi was greater than 0.8.

Valorization of the leaves of fennel (Foeniculum vulgare) as natural dyes fixed on modified cotton: A dyeing process optimization based on a response surface methodology

Dyes obtained from different natural sources have emerged as an important alternative to synthetic dyes due to their negative ecotoxicological effects on the environment. In this study, natural colourant from the leaves of fennel (Foeniculum vulgare) was valorized in the dyeing of cationized cotton fabrics. The influence of the main dyeing conditions (dye bath pH, dyeing temperature, and dyeing duration) on the performances of this dyeing process was studied. The dyeing performances of this process were appreciated by measuring the colour yield (K/S) and the fastness properties of the dyed samples. A surface design with the help of Minitab 15 software was used for optimization of the dyeing process and evaluation of interaction effects of different operating parameters. The optimum conditions for dyeing process were found to be pH of 8.22, dyeing temperature of 99.83°C and dyeing duration of 59.38min. In addition, it was found that the dye bath of cationized cotton with Croscolor DRT absorbed polyphenols compounds and reduced the Biological Oxygen Demand COD and BOD5 of the dyeing bath.

Experimental design for the optimization and robustness testing of a liquid chromatography tandem mass spectrometry method for the trace analysis of the potentially genotoxic 1,3‐diisopropylurea

This paper discusses a design of experiments (DoE) assisted optimization and robustness testing of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method development for the trace analysis of the potentially genotoxic 1,3-diisopropylurea (IPU) impurity in mometasone furoate glucocorticosteroid. Compared to the conventional trial-and-error method development, DoE is a cost-effective and systematic approach to system optimization by which the effects of multiple parameters and parameter interactions on a given response are considered. The LC and MS factors were studied simultaneously: flow (F), gradient (G), injection volume (Vinj), cone voltage (E(con)), and collision energy (E(col)). The optimization was carried out with respect to four responses: separation of peaks (Sep), peak area (A(p)), length of the analysis (T), and the signal-to-noise ratio (S/N). An optimization central composite face (CCF) DoE was conducted leading to the early discovery of carry-over effect which was further investigated in order to establish the maximum injectable sample load. A second DoE was conducted in order to obtain the optimal LC-MS/MS method. As part of the validation of the obtained method, its robustness was determined by conducting a fractional factorial of resolution III DoE, wherein column temperature and quadrupole resolution were considered as additional factors. The method utilizes a common Phenomenex Gemini NX C-18 HPLC analytical column with electrospray ionization and a triple quadrupole mass detector in multiple reaction monitoring (MRM) mode, resulting in short analyses with a 10-min runtime. The high sensitivity and low limit of quantification (LOQ) was achieved by (1) MRM mode (instead of single ion monitoring) and (2) avoiding the drawbacks of derivatization (incomplete reaction and time-consuming sample preparation). Quantitatively, the DoE method development strategy resulted in the robust trace analysis of IPU at 1.25 ng/mL absolute concentration corresponding to 0.25 ppm LOQ in 5 g/l mometasone furoate glucocorticosteroid. Validation was carried out in a linear range of 0.25-10 ppm and presented a relative standard deviation (RSD) of 1.08% for system precision. Regarding IPU recovery in mometasone furoate, spiked samples produced recoveries between 96 and 109 % in the range of 0.25 to 2 ppm.

Growth kinetics evaluation of hydrothermally synthesized β-FeOOH nanorods

Based on the proposition that a quantitative and qualitative relationship between alcohol surface tension and particle growth exists, the effect of four different organic solvents on the growth kinetics of β-FeOOH (akaganeite) nanorods have been evaluated in this study. Two-stage growth of akaganeite nanorods have been observed in the presence of butanol and propanol as solvents. The first growth stage follows a typical power law representing Ostwald Ripening (OR) kinetic. The second stage of growth was found to be asymptotic and was fitted by the Oriented Attachment (OA) kinetics. HRTEM images of the synthesized nanoparticles also showed crystallographically specific oriented attachment based growth of the nanocrystals. Signs of OA mechanism was not observed from the TEM images of the particles synthesized using ethanol and methanol as solvents. The rate constants for each kinetic was evaluated and the rate constant for OR kinetics, kOR, was found to be significantly higher than the rate constant for OA kinetics, kOA, under the reported conditions for the four different solvents used. The rate constants were related to the surface tension of alcohol. A factorial trial was used to evaluate the significance of interaction effects of process parameters. By correlating the surface tension of solvents with different process parameters a generalized correlation has been developed to predict β-FeOOH aspect ratios for the first time. This correlation was validated by an independent study. This correlation takes three different process parameters into consideration in conjunction with the solvent surface tension to predict particle aspect ratios with acceptable confidence.

Rotary Ultrasonic Machining of Sapphire: Feasibility Study and Designed Experiments

Sapphire, widely used in high-speed integrated-circuit chips, thin-film substrates, and various electronic components, is regarded as one of the most difficult to cut materials owing to its great hardness and low fracture toughness. Rotary ultrasonic machining (RUM) has been regarded as an effective processing method for hard and brittle materials. In this paper, RUM process is introduced into the drilling of sapphire for the first time. The feasibility to machine sapphire using RUM is studied. Moreover, results of a designed experimental study into RUM of sapphire are presented to discuss the main effects as well as interaction effects of process parameters (ultrasonic power, spindle speed, and feedrate) on outputs. The process outputs investigated include cutting force and edge chipping size.

Investigation of green properties of iron/jet-milled grey cast iron compacts by response surface method

Grey cast iron powder was produced from grey cast iron scraps by jet milling method and mixed with commercial pure iron powder. The morphology of the produced powders and characteristics of the powder mixtures were investigated. The mathematical models were successfully developed to predict green properties of iron/jet-milled grey cast iron compacts using response surface methodology. Using response surface methodology, the effects of the percentage of jet-milled cast iron powder and compaction pressure on green density, green strength, and hardness of the green compacts were analyzed and the optimal combinations of the input process parameters were obtained to maximize the responses. The main and interaction effects of the input process parameters and also the validity of the models were evaluated by using analysis of variance method. Scanning electron microscopy micrographs of the powders and the fracture surfaces were provided to discuss the obtained responses. The results indicated that in addition to fast production rate and economical considerations, the iron/jet-milled grey cast iron powder compacts have adequate green properties for most of the different combinations of the input process parameters.

Multi-Factors Interaction Effects of Process Parameters on the Joint Strength of Laser Transmission Joining between PC and PA66

This paper presents a laser transmission joining (LTJ) experiment between thermoplastic Polycarbonate (PC) and glass reinforced nylon (PA66GF) using diode laser equipment. Laser transmission joining experimental design and experiment are carried out according to a single process parameters window. Response surface methodology (RSM) in Design-Expert v7 software is employed to develop mathematical models between LTJ process parameters and joint strength. The interaction effects of joining process parameters (line energy, spot diameter, clamp pressure) on the joint strength are investigated using analysis-of-variance (ANOVA), the result shows that the interaction effect of line energy and spot diameter has maximum influence on the joint quality. Finally, the predicted values from mathematical models developed by RSM are compared with the experimental values and it is found that they are nearly agreed with each other. The purpose of predicting joint strength based on reasonable process parameters is achieved.

Prediction and optimization of friction welding parameters for super duplex stainless steel (UNS S32760) joints

Friction welding finds widespread industrial use as a mass production process for joining materials. Friction welding process allows welding of several materials that are extremely difficult to fusion weld. Friction welding process parameters play a significant role in making good quality joints. To produce a good quality joint it is important to set up proper welding process parameters. This can be done by employing optimization techniques. This paper presents a multi objective optimization method for optimizing the process parameters during friction welding process. The proposed method combines the response surface methodology (RSM) with an intelligent optimization algorithm, i.e. genetic algorithm (GA). Corrosion resistance and impact strength of friction welded super duplex stainless steel (SDSS) (UNS S32760) joints were investigated considering three process parameters: friction force (F), upset force (U) and burn off length (B). Mathematical models were developed and the responses were adequately predicted. Direct and interaction effects of process parameters on responses were studied by plotting graphs. Burn off length has high significance on corrosion current followed by upset force and friction force. In the case of impact strength, friction force has high significance followed by upset force and burn off length. Multi objective optimization for maximizing the impact strength and minimizing the corrosion current (maximizing corrosion resistance) was carried out using GA with the RSM model. The optimization procedure resulted in the creation of nondominated optimal points which can aid the process operator to fix the input control variables. The selection of a point from the Pareto front will always be a trade-off between the corrosion resistance and impact strength of the weld depending on the application.

An experimental investigation on Nd:YAG laser microchanneling on polymethyl methacrylate submerged in water

In this research work, an experimental investigation has been carried out on underwater laser microchanneling on polymethyl methacrylate, using a pulsed Nd:YAG laser system. The underwater laser processing has been used to minimize the heat-affected zone, microcracking and burr formation around the microchannel. The process parameters that have been taken into consideration are lamp current, pulse frequency, pulse width and cutting speed. The microchannel characteristics that have been taken into account as responses are microchannel width, microchannel depth, burr width and burr height. Response surface methodology has been used to develop the mathematical relationships between the process parameters and microchannel characteristics. The adequacies of the models have been tested using analysis of variance. The interaction effects of process parameters on the microchannel characteristics have been analyzed and discussed. In addition to that, single-objective and multiobjective optimization of the process parameters have been performed to obtain desired values of microchannel characteristics.

공정변수간의 교호작용을 고려한 모서리 접합두께 및 처짐량 예측 회귀식 도출

The thickness and deflection of melting parts of the glass edge reach the biggest effect on the intensity and thermal insulation performance. During the sealing process using a hydrogen mixed gas torch, the thickness and the deflection effect of the edge part are affected by process parameters. In order to analyze the correlative relationship of the thickness prediction and the deflection of the edge part according to the process parameters, data was obtained by conducting sealing experiments. The main effects and interaction effects of process parameters for the thickness and the shape of the glass edge parts were analyzed through the design of experiment. A mathematical experiment equation that can predict the thickness and deflection of the edge part according to the process parameters was developed by conducting multiple regression equations.

Application of response surface methodology for predicting springback in air bending of electro galvanised steel sheets

Springback in bending affects the geometry of the finished part and it must be predicted in advance to compensate, thus maintaining required tolerances in the finished part. Response surface methodology (RSM)-based models are more useful in industrial applications. Though the researches on application of RSM for other bending processes are available, it is limited in air bending and the attempts are only for uncoated steel sheets. This paper describes the method of developing a prediction model employing RSM and central composite design of experiments that establishes a relationship between springback and the parameters such as strain hardening exponent, coating thickness, die opening, die radius, punch radius, punch travel, and punch velocity in air bending of electro galvanised steel sheet. The results obtained from the model are in good accord with the experimental. Besides, the direct and interaction effect of parameters on springback have been studied based on the developed model.

Multivariate Data Analysis for Parameters Effect on CO2 Removal Efficiency

In this paper, both the main effects and interaction effects of parameters on CO2 removal efficiency were investigated. Flue gas stream data from a 500MW coal power plant has been used for the model development. The complete removal process is implemented in Aspen Plus with selected operating conditions and parameters using Monoethanolamine as solvent. The base case model is developed in Aspen Plus with specific parameter values to achieve 85% removal efficiency. The CO2 removal efficiency variation with different parameters; such as number of stages, inlet solvent flow rate, lean loading, temperature of the flue gas and solvent stream, absorber packing height and diameter and absorber pressure are considered as the most important parameters for sensitivity analyses. The data collected from simulations were analysed using Principal Component Analysis, Principal Component Regression and Partial Least Square-regression. The correlation between variables were studied, which indicate that inlet solvent flow rate, absorber packing height and diameter, absorber pressure and temperature of the solvent stream are positively correlated with CO2 removal efficiency whereas the lean loading and temperature of flue gas are negatively correlated with efficiency.

Compression creep behaviour of jute-polypropylene blended needle-punched nonwoven

This paper discusses the compression creep behaviour of jute-polypropylene blended needle-punched nonwoven. It is essential to know the compression creep behaviour of the needle-punched fabrics too, because of their various applications like geotextiles and carpets. Needle-punched fabric samples were prepared based on the three factors, three levels Box Behnken design of experiment to study the individual as well as interaction effects of process parameters of fabric weight, needling density and blend proportion of jute and polypropylene fibre blend on fabric thickness and compression creep. This study reveals that the initial thickness of fabric decreases prominently with the increase in needling density at low fabric weight and has hardly any effect at high fabric weight (450 g/m2). However, around 43% increase in fabric thickness occurs at high jute content level (60%). At low fabric weight, the effect of the needling density on compression creep is highly prominent when polypropylene content is more than 50% in the blend. However, its effect is negligible when jute content is higher than 50% in the blend. The creep initially decreases with the increase in fabric weight up to a certain limit and thereafter it increases. The minimum value of compression creep of around 14% is obtained at 375 g/m2 fabric weight with 150 punches/cm2 needling density at the level of 60% jute content.

Modeling and optimization of joint quality for laser transmission joint of thermoplastic using an artificial neural network and a genetic algorithm

A central composite rotatable experimental design(CCRD) is conducted to design experiments for laser transmission joining of thermoplastic-Polycarbonate (PC). The artificial neural network was used to establish the relationships between laser transmission joining process parameters (the laser power, velocity, clamp pressure, scanning number) and joint strength and joint seam width. The developed mathematical models are tested by analysis of variance (ANOVA) method to check their adequacy and the effects of process parameters on the responses and the interaction effects of key process parameters on the quality are analyzed and discussed. Finally, the desirability function coupled with genetic algorithm is used to carry out the optimization of the joint strength and joint width. The results show that the predicted results of the optimization are in good agreement with the experimental results, so this study provides an effective method to enhance the joint quality.

Parametric Evaluation of Design Input Parameters on the Mechanistic-Empirical Pavement Design Guide Predicted Performance

The objective of this study was to conduct a sensitivity analysis to identify the input parameters with the greatest effects on the predicted pavement performance from the Mechanistic-Empirical Pavement Design Guide (MEPDG). Three levels of analysis (low, medium, and high) with five input parameters (traffic level, hot-mix asphalt (HMA) thickness, E*, base course thickness, and subgrade type) were evaluated through a full factorial design. The main influence of each individual input parameter and the combinational interaction effects of the input parameters on the predicted distress response were quantified. It was determined that the traffic level input parameter was the main effect on all predicted pavement distresses in the MEPDG. The second main effect for international roughness index (IRI), fatigue cracking, and total pavement rutting was HMA thickness. For asphalt concrete (AC) rutting, the mixture dynamic modulus ranked second for the main effect followed by HMA thickness. For top-down cracking, it was observed that the base course thickness ranked second for the main effect followed by the HMA dynamic modulus. The influence of base thickness on top-down cracking was not expected but it may be due that the MEPDG adopted a traditional fatigue cracking model to describe this failure mechanism.

Compression behaviour of jute–polypropylene blended needle-punched nonwoven under wet conditions

The subject of this paper is the compression behaviour of jute–polypropylene blended needle-punched nonwoven under wet conditions. It is essential to know the compression behaviour of the needle-punched fabrics under wet conditions because of its various applications like geotextiles and carpets. Needle-punched fabric samples were prepared based on the three-factor three-level Box–Behnken design of experiment to study the individual as well as interaction effects of process parameters of fabric weight, needling density and blend proportion of jute and polypropylene fibre blend on compression properties under wet conditions. Initial thickness, percentage compression, percentage thickness loss and percentage compression resilience are the compression properties considered. The compression properties under wet conditions were compared with their respective dry conditions. This study reveals that most of the wet samples show a slightly higher value of initial thickness, percentage compression and thickness loss than dry samples, irrespective of processing variables, though for compression resilience value it is vice versa. The effect of blend does not have much influence on percentage compression in wet conditions. There is optimum level of needling density (around 250 punches/cm2) and blend proportions (around 75% polypropylene) for minimum percentage thickness loss of wet fabric under higher fabric weight. The compression resilience increases with increase in the content of polypropylene in the blend of polypropylene and jute. Optimum compression properties (highest percentage compression and compression resilience with minimum percentage thickness loss) can be achieved at fabric weight of 450 g/m2 with the combination of around 250 punches/cm2 needling density and around 75% polypropylene content.

Response surface optimization of a dynamic dye adsorption process: a case study of crystal violet adsorption onto NaOH-modified rice husk

The adsorption of crystal violet from aqueous solution by NaOH-modified rice husk was investigated in a laboratory-scale fixed-bed column. A two-level three factor (2(3)) full factorial central composite design with the help of Design Expert Version 7.1.6 (Stat Ease, USA) was used for optimisation of the dynamic dye adsorption process and evaluation of interaction effects of different operating parameters: initial dye concentration (100-200 mg L(-1)), flow rate (10-30 mL min(-1)) and bed height (5-25 cm). A correlation coefficient (R (2)) value of 0.999, model F value of 1,936.59 and its low p value (<0.0001) along with lower value of coefficient of variation (1.38 %) indicated the fitness of the response surface quadratic model developed during the present study. Numerical optimisation applying desirability function was used to identify the optimum conditions for a targeted breakthrough time of 12 h. The optimum conditions were found to be initial solution pH=8.00, initial dye concentration=100 mg L(-1), flow rate=22.88 mL min(-1) and bed height=18.75 cm. A confirmatory experiment was performed to evaluate the accuracy of the optimised procedure. Under the optimised conditions, breakthrough appeared after 12.2 h and the column efficiency was determined as 99 %. The Thomas model showed excellent fit to the dynamic dye adsorption data obtained from the confirmatory experiment. Thereby, it was concluded that the current investigation gives valuable insights for designing and establishing a continuous wastewater treatment plant.

Seasonal Variation of Cumulative CO2 Emission from a Vertisol Under Apricot Orchard in Semi-Arid Southeast Turkey

Understanding the factors affecting the CO2 emission from agricultural practices is crucial for global warming. A study was performed in an apricot orchard field in the experimental farm of the Harran University, Southeast Turkey, to i) quantify weekly and seasonal variations of the CO2 emissions from a Vertisol under apricot orchard; ii) evaluate the difference in CO2 emission between the area under trees and rows; and iii) assess the relationships between the amounts of CO2 emissions and environmental parameters for better use and management of the soils from the view point of carbon balance and flux in a semi-arid environment under drip irrigation. Soil CO2 emission measurements were performed during May 2008 and May 2010, from both under tree crowns (CO2-UC) and between tree rows (CO2-BR), on a weekly basis in southeast Turkey with a semi-arid climate. CO2 emissions were statistically correlated with weather and soil parameters such as air temperature, relative humidity, rainfall, soil water content, and soil temperature at various depths from 5 to 100 cm. The weekly emissions ranged from 82 to 1110 kg CO2 ha−1 week−1 and from 96 to 782 kg CO2 ha−1 week−1 in CO2-UC and CO2-BR, respectively. Increase in CO2 emission in the second year was due to increases in mean air and soil temperatures. The weekly and monthly cumulative CO2 emissions were positively correlated with the air and soil temperatures. Multiple linear regression analysis explained 35% and 83% variations in average weekly and monthly CO2 emissions, by using meteorological data. Including the interaction effects of meteorological parameters in regression equations nearly doubled the variance explained by the regression models. According to stepwise regression analysis, soil and air temperatures were found to have the most significant impact on the temporal variability of the soil CO2 emission.

Research on Surface Topography and Tool Wear in Micro-Turn-Milling of Micro-Screw

Turn-milling technology can replace turning with milling to high speed machining rotationally body parts. So, micro-turn-milling has superiority on the productivity and the quality of workpieces, and is more suitable to machine micro-shaft parts and desirable miniature parts based on the turn-milling technology. Micro-turn-milling can be used for the machining of micro-parts in its hardened state. In this paper, the influence of cutting parameters on surface topography and tool wear is presented in micro-turn-milling of micro-screw. The interaction effect of parameters to surface topography and tool wear is investigated. The results show that micro-turn-milling technology has its peculiar advantages in realizing high-speed cutting and ensuring machining quality.

Adsorption of crystal violet from aqueous solution onto sugarcane bagasse: central composite design for optimization of process variables

The adsorption of crystal violet (CV) from aqueous solution by sugarcane bagasse (SCB), an agro-industrial residue, was investigated in a batch experimental setup. A two level four factor (24) full factorial central composite design (CCD) with the help of Design Expert Version 7.1.6 (Stat-Ease, USA) was used for adsorption process optimization and evaluation of interaction effects of different operating parameters: agitation speed (80–180 rpm), initial solution pH (4.0–8.0), initial dye concentration (100–200 mg L–1), and adsorbent dose (2–5 g L–1). A multiple coefficient of determination (R2) value of 0.98, model F value of 266.36 and its low P-value (&amp;lt;0.0001) along with lower value of coefficient of variation (2.70%) indicated the fitness of the response surface quadratic model developed during the present study. Numerical optimization applying desirability function was used to identify the optimum conditions for maximum removal of CV. The optimum conditions were found to be agitation speed = 165 rpm, initial solution pH = 8.0, initial dye concentration = 200 mg L–1 and adsorbent dose = 2.0 g L–1. A confirmatory experiment was performed to evaluate the accuracy of the optimization procedure and maximum CV removal of 93.21% was achieved under the optimized conditions.