scholarly journals Linear and Non-linear Regression Analysis for the Adsorption Kinetics of SO2 in a Fixed Carbon Bed Reactor – A Case Study

2021 ◽  
Author(s):  
Anna M. Kisiela-Czajka ◽  
Bartosz Dziejarski
Keyword(s):  
Linear Regression ◽  
Activated Carbons ◽  
Coal Dust ◽  
Linear Regression Analysis ◽  
Heterogeneous Surface ◽  
Hard Coal ◽  
Linear Regression Method ◽  
Order Kinetic ◽  
Lignite Fly Ash ◽  
Non Linear

Kinetic parameters of SO2 adsorption on unburned carbons from lignite fly ash and activated carbons based on hard coal dust were determined. The model studies were performed using the linear and non-linear regression method for the following models: pseudo first and second-order, intraparticle diffusion, and chemisorption on a heterogeneous surface. The quality of the fitting of a given model to empirical data was assessed based on: R2, R, Δq, SSE, ARE, χ2, HYBRID, MPSD, EABS, and SNE. It was clearly shown that it is the linear regression that more accurately reflects the behaviour of the adsorption system, which is consistent with the first-order kinetic reaction – for activated carbons (SO2+Ar) or chemisorption on a heterogeneous surface – for unburned carbons (SO2+Ar and SO2+Ar+H2O(g)+O2) and activated carbons (SO2+Ar+H2O(g)+O2). Importantly, usually, each of the approaches (linear/non-linear) indicated a different mechanism of the studied phenomenon. A certain universality of the χ2 and HYBRID functions has been proved, the minimization of which repeatedly led to the lowest SNE values for the indicated models. Fitting data by any of the non-linear equations based on the R or R2 functions only, cannot be treated as evidence/prerequisite of the existence of a given adsorption mechanism.

Linear and Non-Linear Regression Analysis of Boron Adsorption Kinetics on New Radiation Grafted Fibrous Adsorbent

2014 ◽  
Vol 625 ◽  
pp. 245-248
Author(s):  
T.M. Ting ◽  
Mohamed Mahmoud Nasef ◽  
Kamaruddin Hashim
Keyword(s):  
Kinetic Model ◽  
Linear Regression ◽  
Linear Method ◽  
Second Order ◽  
Linear Regression Method ◽  
Order Kinetic ◽  
Fast Kinetics ◽  
Non Linear ◽  
Pseudo Second Order ◽  
Boron Adsorption

The kinetic behavior of a new adsorbent prepared by radiation induced grafting of vinyl benzyl chloride (VBC) onto nylon-6 fibers followed by functionalization with N-methyl-D-glucamine was investigated using pseudo second-order kinetic model. The linear method and non-linear regression methods were compared to determine the best fitting for the kinetic model describing the adsorption of boron by the new adsorbent. Four pseudo second-order kinetic linear equations were presented. A type-1 pseudo second-order linear method was found to fit best the experimental data. Non-linear regression method was found to be more appropriate to describe the boron adsorption by the fibrous adsorbent which has also shown fast kinetics.

scholarly journals Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia

2016 ◽  
Vol 9 (4) ◽  
pp. 22
Author(s):  
Areej A. Malibari ◽  
Amjad H. Gamlo
Keyword(s):  
Saudi Arabia ◽  
Linear Regression ◽  
Thermal Model ◽  
Cooling System ◽  
Linear Regression Analysis ◽  
Grid Method ◽  
Data Fitting ◽  
Regression Method ◽  
Linear Regression Method ◽  
Non Linear

<p><strong>Objectives: </strong>The consumption of electricity and its costs are expected to be increased in Saudi Arabia due to its rapid growth in population. As the Kingdom is characterized by extreme hot climate, a massive amount of electricity consumed by the residential sector goes to power air conditioners. To control this huge amount of energyconsumedin homes, thermal models have been generated with two or more parameters. <strong>Methodology: </strong>The households’ surveys have been conducted in order to collect the data. The Non-linear regression analysis has been carried out to obtain the outcomes of study. Moreover, household surveys have been conducted for data collection. The grid algorithm and the non-linear regression have been used to learn the parameters in the model to simulate the weather in Saudi Arabia. The temperature loggers have been placed in the houses to observe the behavior of residents of using cooling system. The web forecast has been used to analyze the temperature of cities on hourly basis. <strong>Results: </strong>Simple thermal model has been built using two parameters by applying the grid and non-linear regression methods for data fitting. Then the thermal model with envelope has also been created using four parameters by applying non-linear regression method for data fitting. <strong>Conclusion: </strong>It has been evaluated through outcomes that thermal model with envelope is better as compared to simple thermal model. Moreover, the data fitting by non-linear regression method has also been observed to perform better than data fitting by grid method.</p>

scholarly journals CURVAS DE SECAGEM E AVALIAÇÃO DA ATIVIDADE DE ÁGUA DA BANANA PASSA

2004 ◽  
Vol 22 (1) ◽  
Author(s):  
MILTON CANO-CHAUCA ◽  
AFONSO M. RAMOS ◽  
PAULO C. STRINGHETA ◽  
JOSÉ ANTONIO MARQUES ◽  
POLLYANNA IBRAHIM SILVA
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Moisture Content ◽  
Water Activity ◽  
Linear Regression Analysis ◽  
Sorption Isotherms ◽  
Exponential Model ◽  
Drying Time ◽  
Non Linear ◽  
Drying Curves

Curvas de secagem de banana passa foram determinadas, utilizando-se três temperaturas do ar de secagem. Os resultados indicaram que para reduzir o teor de umidade do produto até 23,5% foram necessários tempos de secagem de 51, 36 e 30 horas paras as temperaturas de 50, 60 e 70ºC, respectivamente. O modelo exponencial U/Uo = exp(-kt) foi ajustado para os dados experimentais mediante análise de regressão não-linear, encontrandose alto coeficiente de regressão linear. Determinou-se a atividade de água do produto ao longo do processo de secagem para as três temperaturas testadas. Estudou-se a correlação entre a atividade de água e o teor de umidade do produto, determinando-se as isotermas de dessorção da banana passa a 25ºC. Observou-se que a atividade de água diminuiu em função do tempo de secagem e do teor de umidade para as três temperaturas de secagem. Os dados experimentais foram ajustados mediante regressão não-linear ao modelo polinomial e a seguinte equação foi obtida: U = -1844,93 + 7293,53Aa – 9515,52Aa2 + 4157,196Aa3. O ajuste mostrou-se satisfatório (R2 > 0,90). DRYING CURVES AND WATER ACTIVITY EVALUATION OF THE BANANA-PASSES Abstract Banana drying curves were determined by utilizing three drying air temperatures. The results indicated that to reduce the moisture content of the product until 23.5% it were necessary drying times of 51, 36 and 30 hours for temperatures of 50, 60 and 70ºC, respectively. The exponential model U/Uo = exp(-kt) was adjusted for the experimental data by means of non linear regression analysis, and a high coefficient of linear regression was found. The water activity of the product was determined throughout the drying process for the three tested temperatures. The correlation between the water activity and moisture content of the product was studied, and the sorption isotherms were determined at 25º C. It was observed that the water activity decreased in function to the drying time and moisture content for the three drying temperatures. The experimental data were adjusted by means of non linear regression to the polynomial model and the following equation was obtained: U = - 1844.93 + 7293.53A a – 9515.52 Aa 2 + 4157.196A a 3. The final adjust was satisfactory (R2 > 0.90).

A NEW PARAMETER ESTIMATION METHOD FOR ONLINE SOFT TISSUE CHARACTERIZATION

2016 ◽  
Vol 16 (08) ◽  
pp. 1640019 ◽  
Author(s):  
JAEHYUN SHIN ◽  
YONGMIN ZHONG ◽  
JULIAN SMITH ◽  
CHENGFAN GU
Keyword(s):  
Soft Tissue ◽  
Linear Regression ◽  
Tissue Characterization ◽  
Soft Tissues ◽  
Unscented Kalman Filter ◽  
Estimation Method ◽  
Regression Method ◽  
Linear Regression Method ◽  
Non Linear

Dynamic soft tissue characterization is of importance to robotic-assisted minimally invasive surgery. The traditional linear regression method is unsuited to handle the non-linear Hunt–Crossley (HC) model and its linearization process involves a linearization error. This paper presents a new non-linear estimation method for dynamic characterization of mechanical properties of soft tissues. In order to deal with non-linear and dynamic conditions involved in soft tissue characterization, this method improves the non-linearity and dynamics of the HC model by treating parameter [Formula: see text] as independent variable. Based on this, an unscented Kalman filter is developed for online estimation of soft tissue parameters. Simulations and comparison analysis demonstrate that the proposed method is able to estimate mechanical parameters for both homogeneous tissues and heterogeneous and multi-layer tissues, and the achieved performance is much better than that of the linear regression method.

scholarly journals Multivariate analytical methods for simultaneous estimation of Atenolol and Hydrochlorothiazide in bulk and tablet dosage form

2021 ◽  
Vol 6 (4) ◽  
pp. 205-208
Author(s):  
Sreenivasa Charan Archakam ◽  
Keerthisikha Palur ◽  
Praveen Kumar Arava
Keyword(s):  
Linear Regression ◽  
Matrix Method ◽  
Linear Regression Analysis ◽  
Molar Absorptivity ◽  
Simultaneous Estimation ◽  
Linear Regression Method ◽  
Spectrophotometric Methods ◽  
The Matrix ◽  
Ft Ir ◽  
Tablet Dosage

The present study aimed to develop simple, accurate and precise FTIR and UV spectrophotometric methods for the quantification of Atenolol and Hydrochlorothiazide in bulk and tablet dosage forms. FT-IR method like classical least squares (CLS) was developed within the range of 2366.69-3433.44; 1564.40-1673.30 cm- UV methods like Cramer’s matrix method (method-I) and linear regression analysis (Method II) were developed and they are based upon constructing the matrix set by using molar absorptivity values at 275.60 nm and 270.40 nm. The assay values for FTIR- CLS method were 102% and 108 % for Atenololand Hydrochlorothiazide respectively. Cramer’s matrix method results were found to be 95.15% and 104% for Atenolol and Hydrochlorothiazide respectively and for linear regression method they were found to be 98.50% and 106% (w/w).

scholarly journals EXPLORATION OF INTERCALATED KAOLINITE CLAY FOR THE UPTAKE OF BASIC DYE BY ADSORPTION − EQUILIBRIUM, KINETICS AND THERMODYNAMIC STUDIES

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
C. E. Chigbundu ◽  
K. O. Adebowale
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Goodness Of Fit ◽  
Linear Regression Analysis ◽  
Dye Adsorption ◽  
Batch Adsorption ◽  
Sem Images ◽  
Kaolinite Clay ◽  
Non Linear ◽  
The Impact

Dyes are complex and sensitive organic chemicals which exposes microbial populations, aquatic lives and other living organisms to its toxic effects if their presence in water bodies or industrial effluents are not properly handled. This work therefore, comparatively studied the adsorption efficiencies of natural raw kaolinite (NRK) clay adsorbent and dimethyl sulphoxide (DMSO) faciley intercalated kaolinite clay (DIK) adsorbent for batch adsorption of Basis Red 2 (BR2) dye. The impact of varying the contact time, temperature and other operating variables on adsorption was also considered. The two adsorbents were characterized using SEM images, FTIR and XRD patterns. Linear and non-linear regression analysis of different isotherm and kinetic models were used to describe the appropriate fits to the experimental data. Error analysis equations were also used to measure the goodness-of-fit. Langmuir isotherm model best described the adsorption as being monolayer on homogenous surfaces while Kinetic studies showed that Elovich model provides the best fit to experimental data. The adsorption capacities of NRK and DIK adsorbents for the uptake of BR2 were 16.30 mg/g and 32.81 mg/g, respectively (linear regression) and 19.30 mg/g and 30.81 mg/g, respectively (non-linear regression). The thermodynamic parameter, ∆G showed that BR2 dye adsorption onto the adsorbents were spontaneous. DIK adsorbent was twice efficient compared with NRK for the uptake of BR2 dye.

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