scholarly journals Optimizing Uniaxial Oil Extraction of Bulk Rapeseeds; Spectrophotometric and Chemical Analyses of the Extracted Oil under Pretreatment Temperatures and Heating Intervals

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1755
Author(s):  
Cimen Demirel ◽  
Abraham Kabutey ◽  
David Herák ◽  
Petr Hrabě ◽  
Čestmír Mizera ◽  
...  
Keyword(s):  
Response Surface ◽  
Acid Value ◽  
Statistical Technique ◽  
Deformation Energy ◽  
Oil Extraction ◽  
Heating Time ◽  
Optimization Parameters ◽  
Response Surface Regression ◽  
Processing Optimization ◽  
Experimental Runs

Optimizing the operating factors in edible oil extraction requires a statistical technique such as a response surface methodology for evaluating their effects on the responses. The examined input factors in this study were the diameter of pressing vessel, VD (60, 80, and 100 mm), temperature, TPR (40, 60, and 80 °C), and heating time, HTM (30, 60 and 90 min). The combination of these factors generated 17 experimental runs where the mass of oil, oil yield, oil extraction efficiency, and deformation energy were calculated. Based on the response surface regression analysis, the combination of the optimized factors was VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 60 (0) min); VD: 60 (−1) mm; TPR: 80 °C (+1) and HTM: 75 (+0.5) min and VD: 100 (+1) mm; TPR: 80 °C (+1) and HTM: 90 (+1). The absorbance and transmittance values significantly (p < 0.05) correlated with the wavelength and temperature, but they did not correlate significantly (p > 0.05) with heating time. The peroxide value did not correlate significantly with temperature, however, it correlated significantly with heating time. Neither the acid value nor the free fatty acid value correlated with both temperature and heating time. The findings of the present study are part of our continuing research on oilseeds’ processing optimization parameters.

Optimization of discharge printing of indigo denim using potassium permanganate via response surface regression

2018 ◽  
Vol 47 (3) ◽  
pp. 228-235 ◽  
Author(s):  
Amna Siddique ◽  
Tanveer Hussain ◽  
Waseem Ibrahim ◽  
Zulfiqar Ali Raza ◽  
Sharjeel Abid
Keyword(s):  
Reaction Time ◽  
Response Surface ◽  
Potassium Permanganate ◽  
Practical Implication ◽  
Statistical Technique ◽  
Significant Loss ◽  
Content Type ◽  
Wet Processing ◽  
Key Variables ◽  
Response Surface Regression

Purpose This paper aims to investigate the feasibility of potassium permanganate (KMnO4) as an efficient discharging agent for indigo-dyed denim fabrics and identification of key variables for its cost-efficient implication. Design/methodology/approach Response surface methodology, which is a statistical technique for the optimization of process variables, was used to study the effect of three key variables, i.e. KMnO4 concentration, printing paste pH and reaction time on whiteness and strength of discharged printed fabric. Regression models were developed to predict response variables, i.e whiteness, tensile strength and tear strength of discharge printed denim. Findings It was found that some captivating discharge printing effects could be produced using appropriate KMnO4 concentration, printing paste pH and reaction time without any significant loss in the fabric strength. Practical implications This study highlights the practical implication of KMnO4 to be used as a safe and effective discharging agent under different conditions and to optimize the parameters using statistical analysis to ensure minimum loss in textile properties. The use of denim has evolved over the decades from a rough and tough workwear to highly fashionable apparel. Various dry and wet processing techniques have been introduced in recent years for the value-addition of denim – discharge printing is one of them. As lab to bulk reproducibility requires some sort of experience and adjustments in main parameters, the practical feasibility on the bulk scale should be adjusted in advance by means of the lab scale experimentation. Originality/value The KMnO4 oxidation process is considered eco-friendly because manganese dioxide, which is formed when permanganate is reduced, can be recycled. Thus, the use of KMnO4 can be considered as an eco-friendly safe process for the discharging of indigo dyes.

Resistance Welding Process Development and Optimization for Recycled High-Density Polyethylene (HDPE)

2015 ◽  
Author(s):  
Peter F. Baumann ◽  
Lucas Sendrowski
Keyword(s):  
Tensile Strength ◽  
Response Surface ◽  
High Density Polyethylene ◽  
Heating Temperature ◽  
Base Material ◽  
Heating Time ◽  
High Density ◽  
Hot Plate ◽  
Initial Testing ◽  
Hot Plate Welding

Large recycled high-density polyethylene (HDPE) structural members, difficult to manufacture by extrusion processes, have been created by the hot plate welding of simple plastic lumber sections. Hot plate welding generates better joint strength than any other welding method currently employed in plastic manufacturing. However, to achieve the desired temperature of the thick plate to melt the polymer uniformly, the process needs a high amount of heat energy requiring furnace (or resistance) heating of a considerable mass. A new method which could combine the heating element and a thin plate into one source could be more efficient in terms of heat loss and thus energy used. The premise of this investigation is to replace the hot plate with a very thin piece of high resistance nickel-chromium alloy ribbon to localize the application of heat within a plastic weld joint in order to reduce energy loss and its associated costs. This resistance ribbon method uses electrical current to reach an adequate temperature to allow for the welding of the HDPE plastic. The ribbon is only slightly larger than the welding surface and very thin to reduce the loss of excess heat through unused surface area and thick sides. The purpose of this project was to weld recycled high-density polyethylene (HDPE) using resistance welding and to match the tensile strength results considered acceptable in industry for hot plate welding, that is, equal to or greater than 80% of the base material strength. Information obtained through literature review and previous investigations in our laboratories established welding (heating) temperature and time as testing factors. Designed experimentation considered these factors in optimizing the process to maximize the weld tensile strength. A wide-ranging full-factorial experimental design using many levels was created for the initial testing plan. Tensile strengths obtained after welding under the various condition combinations of weld temperature and time revealed a region of higher strength values in the response surface. After the wide-range initial testing, the two control parameters, heating temperature and heating time, were ultimately set up in a focused Face Centered Cubic (FCC) Response Surface Method (RSM) testing design and the tensile strength response was then analyzed using statistical software. The results obtained indicated a strong correlation between heating time and heating temperature with strength. All welded samples in the final testing set exhibited tensile strength of over 90% base material, meeting the goal requirements. A full quadratic equation relationship for tensile strength as a function of welding time and temperature was developed and the maximum tensile strength was achieved when using 280°C for 60 seconds.

Luffa Seed Oil Extraction: Response Surface and Neuro-Fuzzy Modelling Performance Evaluation and Optimization

2021 ◽  
Author(s):  
Kenechi Nwosu-Obieogu ◽  
Goziya W. Dzarma ◽  
Chijioke B. Ugwuodo ◽  
Linus I. Chiemenem ◽  
Kelechi N. Akatobi
Keyword(s):  
Performance Evaluation ◽  
Response Surface ◽  
Seed Oil ◽  
Oil Extraction ◽  
Fuzzy Modelling ◽  
Neuro Fuzzy

The Impact of Moral Expectancy Violations on Audiences’ Parasocial Relationships With Movie Heroes and Villains

2019 ◽  
pp. 009365021988651 ◽  
Author(s):  
James Alex Bonus ◽  
Nicholas L. Matthews ◽  
Tim Wulf
Keyword(s):  
Response Surface ◽  
Statistical Technique ◽  
Longitudinal Survey ◽  
Formation Processes ◽  
Expectancy Violations ◽  
Parasocial Relationships ◽  
Disposition Theory ◽  
Immoral Behavior ◽  
Before And After ◽  
The Impact

Integrating the predictions of disposition theory and expectancy violations theory, a longitudinal survey assessed adults’ parasocial relationships with characters in a popular movie franchise before and after the release of the latest film installment of that franchise. Consistent with disposition theory, characters’ immoral behavior in the film weakened participants’ parasocial relationships with those characters. However, analyses conducted using a novel statistical technique (i.e., response surface analysis) revealed that further shifts in the strength of these relationships occurred when characters subverted participants’ expectations regarding their typical moral behavior. Specifically, participants’ relationship with the film’s primary villain strengthened when he was perceived as behaving more morally than expected, whereas their relationship with the film’s primary hero weakened when he was perceived as behaving either more or less morally than expected. These findings highlight the need for more nuanced examinations of disposition formation processes.

scholarly journals Establishing the Correlations for Eco-Efficiency Index of Various Types of Structural Concrete Used in the Malaysian Housing Using Response Surface Method

2020 ◽  
Vol 10 (12) ◽  
pp. 4372
Author(s):  
Mohd Samsudin Abdul Hamid ◽  
Nasir Shafiq ◽  
Osamah Kiwan
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Linear Trend ◽  
Efficiency Index ◽  
Statistical Technique ◽  
Consumption Pattern ◽  
Residential Housing ◽  
Structural Concrete ◽  
Sustainable Environment ◽  
Surface Method

The concept of a sustainable environment generally refers to the development that creates a balance between the resources consumption pattern and the rate of depletion of natural resources. For determining the level of sustainability of any project, three types of impacts are assessed: economic, environmental, and social. This paper presents an analytical study that focused on establishing a correlation of eco-efficiency index for low-rise reinforced concrete residential housing in Malaysia. A statistical technique using the response surface method was performed, with the help of design expert software. The data was verified using regression analysis and represented by R2 value, standard deviation, and coefficient of variation. By using economic factors, environmental factors, and the eco-efficiency index, 3D model graphs were developed for structural concrete containing fly ash, and blast furnace slag (BFS), which was assigned to the structural members in a single and double story housing. The study has concluded that the correlations established between the cost and carbon emission, economic & environmental scores, and the eco-efficiency index have shown a linear trend for single story housing and a cubic for the double story housing.

Optimizing the Pomelo Oils Extraction Process by Microwave-Assisted Hydro-Distillation Using Soft Computing Approaches

2018 ◽  
Vol 279 ◽  
pp. 217-221 ◽  
Author(s):  
Tran Thien Hien ◽  
Nguyen Phu Thuong Nhan ◽  
Nguyen Duy Trinh ◽  
Van Thi Thanh Ho ◽  
Long Giang Bach
Keyword(s):  
Response Surface Methodology ◽  
Essential Oil ◽  
Response Surface ◽  
Soft Computing ◽  
Microwave Power ◽  
High Reliability ◽  
Extraction Process ◽  
Oil Extraction ◽  
Microwave Assisted ◽  
Number Of Factors

Pomelo (Citrus grandis .Linn Osbeck) oils is becoming more and more popular for everyone because it has great benefits. However, the efficiency of essential oil extraction process depends on the method and is influenced by a number of factors. Microwave-assisted hydro-distillation and Response Surface Methodology are selected for extracting and optimizing the factors affect the yield of the pomelo oil. The pomelo oil has the optimum yield was 4.5% when extracted with a water and peels ratio of 3,119: 1 (ml/g) for time extraction of 117.336 (minutes) at a microwave power of 403.115 (W) with high reliability (R2 = 0.9831)

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