Mathematical model of postharvest variation in tomato color based on optimized response surface methodology

2021 ◽  
Author(s):  
Jia‐Wei Han ◽  
Qing‐Shan Ren ◽  
Zeng‐Tao Ji ◽  
Xin‐Ting Yang
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Response Surface

DRY SLIDING WEAR BEHAVIOR OPTIMIZATION OF STIR CAST LM6/ZrO2 COMPOSITES BY RESPONSE SURFACE METHODOLOGY ANALYSIS

2016 ◽  
Vol 40 (3) ◽  
pp. 351-369 ◽  
Author(s):  
G. Karthikeyan ◽  
G.R. Jinu
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Wear Behavior ◽  
Wear Test ◽  
Stir Casting ◽  
Dry Sliding Wear ◽  
Experimental Conditions ◽  
Weight Percentage ◽  
The Mathematical Model

LM6 was reinforced with various percentages of ZrO2 particles by using stir casting method. The prepared samples were subjected to tensile and wear test at variable loads by using a pin-on-disc wear tester. The curve fitting technique was used to develop the respective linear, logarithmic, polynomial, power law equations. The wear worn surface and surface roughness of the specimen were studied. Response Surface Methodology (RSM) was used to minimize the number of experimental conditions and develop the mathematical model between the key process parameters namely weight percentage of ZrO2, load and sliding distance. Analysis of Variance technique was applied to check the validity of the developed model. The mathematical model developed for the specific wear rate was predicted at 99% confidence level and some useful conclusions were made.

scholarly journals Analysis of boride layer thickness of borided AISI 430 by response surface methodology

2019 ◽  
Vol 9 (3) ◽  
pp. 39-44
Author(s):  
Turker Turkoglu ◽  
Irfan Ay
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Layer Thickness ◽  
Boride Layer ◽  
Layer Formation ◽  
Face Centered ◽  
Boriding Process ◽  
Aisi 430 ◽  
Central Composite

The boriding process is a thermochemical surface treatment which can be applied to many iron and non-ferrous materials and improves the properties of the material such as hardness, wear resistance. In the present study, the layer thickness values of the boronized AISI 430 material were optimized using the Response Surface Methodology. Mathematical model was constructed using parameters such as temperature and time and the results were analyzed comparatively. As a result of the analysis, the optimum layer thickness value for AISI 430 material was obtained as 39.0183 µm for 1000 ºC and 5.9h and it was determined that the boriding temperature and time are effective on the boride layer formation process of AISI 430 material. Finally, the Response Surface Methodology and Face Centered Central Composite Design have been effectively applied to the boriding process.

scholarly journals Application of Response Surface Methodology for Modeling of Postweld Heat Treatment Process in a Pressure Vessel Steel ASTM A516 Grade 70

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Prachya Peasura
Keyword(s):  
Heat Treatment ◽  
Mathematical Model ◽  
Tensile Strength ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Pressure Vessel ◽  
Postweld Heat Treatment ◽  
Pressure Vessel Steel ◽  
Vessel Steel ◽  
Postweld Heat

This research studied the application of the response surface methodology (RSM) and central composite design (CCD) experiment in mathematical model and optimizes postweld heat treatment (PWHT). The material of study is a pressure vessel steel ASTM A516 grade 70 that is used for gas metal arc welding. PWHT parameters examined in this study included PWHT temperatures and time. The resulting materials were examined using CCD experiment and the RSM to determine the resulting material tensile strength test, observed with optical microscopy and scanning electron microscopy. The experimental results show that using a full quadratic model with the proposed mathematical model isYTS=-285.521+15.706X1+2.514X2-0.004X12-0.001X22-0.029X1X2. Tensile strength parameters of PWHT were optimized PWHT time of 5.00 hr and PWHT temperature of 645.75°C. The results show that the PWHT time is the dominant mechanism used to modify the tensile strength compared to the PWHT temperatures. This phenomenon could be explained by the fact that pearlite can contribute to higher tensile strength. Pearlite has an intensity, which results in increased material tensile strength. The research described here can be used as material data on PWHT parameters for an ASTM A516 grade 70 weld.

OPTIMASI PENGOMPOSAN SAMPAH ORGANIK RUMAH TANGGA MENGGUNAKAN KOMBINASI AKTIVATOR EM4 DAN MOL TERHADAP RASIO C/N

2012 ◽  
Vol 10 (2) ◽  
pp. 70 ◽  
Author(s):  
S Subandriyo ◽  
Didi Dwi Anggoro ◽  
H Hadiyanto
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Organic Waste ◽  
Variable Parameter ◽  
Contour Plot ◽  
Fermentation Time ◽  
Contour Plots ◽  
Parameter Values ◽  
The Relationship

ABSTRAK Penelitian ini menggunakan sampah organik rumah tangga berupa campuran sampah organik dari dapur dan kebun dengan penambahan aktivator EM4, MOL dan campuran EM4/MOL. Rancangan penelitian yang digunakan yaitu perbandingan kombinasi volume campuran aktivator EM4 dan MOL dan waktu fermentasi. Data hasil percobaan diplotkan dalam sebuah model matematis dan selanjutnya dioptimasi menggunakan software Statistica 6.0 dengan metode Response Surface Methodology (RSM). Dari hasil penelitian diperoleh model matematika untuk hubungan penggunaan kombinasi aktivator EM4 dan MOL  untuk nilai C/N : Y= 20,47 – 3,53X1 – 1,20X2 – 3,80X12 – 0,31X22 – 0,08X1X2.Hasil kondisi optimum variabel pengomposan terhadap nilai parameter hasil kompos yang diperoleh dari Grafik response fitted surface dan contour plot yang dihasilkan menunjukkan jenis optimasi proses nilai C/N maksimal terjadi pada 21% (warna coklat tua) pada campuran EM4/MOL 0,6 sampai dengan 1,2 dan waktu fermentasi 14 sampai dengan 30 hari. Kata kunci : sampah organik rumah tangga, pengomposan, response surfase methodology, rasio C/N. ABSTRACT This research using household organic waste that is a mixture of organic waste from the kitchen and garden with the addition of an activator EM4, MOL and mixed EM4/MOL. The research design used is a combination of volume mix ratio and activator EM4/MOL and the fermentation time. The data results was plotted on a mathematical model and then optimized using the software Statistica 6.0 Response Surface Methodology methods (RSM).The results obtained by use of a mathematical model for the relationship activator combination EM4 and MOL for a C/N: Y= 20,47 – 3,53X1 – 1,20X2 – 3,80X12 – 0,31X22 – 0,08X1X2.The optimum conditions for composting variable parameter values compost obtained from Graph fitted response surface and contour plots that indicates the type of process optimization resulting of C/N ratio maximum occurred in 21% (dark brown color) in a mixture EM4/MOL of 0.6 to 1.2 and fermentation time 14 to 30 days. Keywords: household organic waste, composting, response surface methodology, the C/N ratio

Investigating and Modeling the Machinability of Al 6061 Using Response Surface Methodology

2015 ◽  
Vol 761 ◽  
pp. 267-272
Author(s):  
Basim A. Khidhir ◽  
Ayad F. Shahab ◽  
Sadiq E. Abdullah ◽  
Barzan A. Saeed
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Effect Of Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process

Decreasing the effect of temperature, surface roughness and vibration amplitude during turning process will improve machinability. Mathematical model has been developed to predict responses of the surface roughness, temperature and vibration in relation to machining parameters such as the cutting speed, feed rate, and depth of cut. The Box-Behnken First order and second-order response surface methodology was employed to create a mathematical model, and the adequacy of the model was verified using analysis of variance. The experiments were conducted on aluminium 6061 by cemented carbide. The direct and interaction effect of the machining parameters with responses were analyzed. It was found that the feed rate, cutting speed, and depth of cut played a major role on the responses, such as the surface roughness and temperature when machining mild steel AISI 1018. This analysis helped to select the process parameters to improve machinability, which reduces cost and time of the turning process.

Optimization of Lactose Content in the Row Milk by Colorimetry via Response Surface Methodology

2014 ◽  
Vol 997 ◽  
pp. 38-42
Author(s):  
Jian Ting Ning ◽  
Jun Rui Wu ◽  
Xi Qing Yue
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Reaction Time ◽  
Response Surface ◽  
Reaction Temperature ◽  
Raw Milk ◽  
Single Factor ◽  
Optimum Extraction ◽  
Single Factor Experiment

The lactose content in the raw milk by colorimetry was introduced in the paper.On the single-factor experiment basis, it used response surface methodology to establish a quadratic mathematical model of lactose content. After analyzing the significance of the various factors and interactions, the results showed the optimum extraction conditions of detecting lactose content by colorimetry were as follows: reaction temperature 100°C, reaction time 5.2min, amount of precipitation 2.9 mL. In order to verify the method’s accuracy, five kinds of raw milk were chosen to test. The results showed the recoveries were between 97.122%-101.294%, so it is feasible to determine the content of lactose in raw milk.

scholarly journals FACTORS AFFECTING REFRIGERATOR-FREEZERS ENERGY CONSUMPTION

2017 ◽  
Vol 19 (2) ◽  
pp. 57-67 ◽  
Author(s):  
R. Saidur Saidur ◽  
H.H. Masjuki ◽  
T.M.I. Mahlia ◽  
A.R. Nasrudin
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Energy Consumption ◽  
Response Surface ◽  
Room Temperature ◽  
Combined Effect ◽  
Factors Affecting ◽  
Door Opening ◽  
Several Variables ◽  
The Mathematical Model

Two frost-free household refrigerator-freezers, one with 492 liter capacity and one with 460 liter capacity were tested in the laboratory to determine the sensitivity of several variables those influence consumption refrigerator-freezers energy consumption greatly. The effects of single variables such as room temperature, thermostat setting positions, and door openings on the energy  consumption were investigated. Using Response Surface Methodology (RSM), a mathematical model has been developed to investigate the combined effect of room temperature, thermostat setting positions, and door opening on the energy consumption of refrigerator-freezers. From the mathematical model, it has been observed that room-temperature has the highest effect on the energy consumption followed by the thermostat setting position. The door opening has lowest on the energy consumption. More detailed tests were performed under different room temperature, thermostat setting positions, and door opening conditions and presented in this paper.

scholarly journals Development of Mathematical Model for Cassava Starch Properties Using Response Surface Methodology

2019 ◽  
Vol 8 (08) ◽  
pp. 2631-2646
Author(s):  
T. Krishnakumar ◽  
M. S. Sajeev ◽  
Namrata A. Giri ◽  
Chintha Pradeepika ◽  
Venkatraman Bansode
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Cassava Starch ◽  
Starch Properties

Optimization of Malachite Green by KOH-Modified Grapefruit Peel Activated Carbon: Application of Response Surface Methodology

2014 ◽  
Vol 529 ◽  
pp. 611-615 ◽  
Author(s):  
Liu Dan Luo ◽  
Hai Yi Huang ◽  
Jian Hong Bi ◽  
Lang Lang Tan ◽  
Hua Zhang ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Response Surface Methodology ◽  
Activated Carbon ◽  
Response Surface ◽  
Malachite Green ◽  
Potassium Hydroxide ◽  
Single Factor ◽  
Grapefruit Peel ◽  
Central Composite ◽  
Single Factor Experiment

Response surface methodology (RSM) was utilized to optimize the best adsorbent conditions on Malachite Green in wastewater by the activated carbon which has been prepared from grapefruit peel with potassium hydroxide activating. Built on single-factor experiment, adsorbent dosage, pH, initial MG concentration and temperature were chosen as influencing factors during adsorption. The experimental mathematical model was arranged according to central composite design (CCD). The results shown that the best conditions were pH 9, initial MG concentration of 2000 mg/L, 1 g/L dosage of KAC and 40°C. Maximum absorption was 1944.35 mg/L.

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