Multiple Quadratic Regression Model Research Articles

Optimization-Design and Atomization-Performance Study of Aerial Dual-Atomization Centrifugal Atomizer

The aerial atomizer is the most essential component of the plant protection UAV (unmanned aerial vehicle). However, the structural optimization of existing aerial atomizers lacks comprehensive consideration of spray parameters and structural parameters, and there is a shortage of available atomizer spray models, resulting in the unstable effect of UAV application. In our previous work, an aerial dual-atomization centrifugal atomizer was developed. In order to obtain an aerial atomizer with good atomization effect and its atomization model, structural optimization at different rotation speeds and flow rates of the atomizer, and its atomization performance, are studied in this paper. Firstly, with the droplet volume median diameter (VMD) and spectral width (SRW) as the evaluation index, through the single-factor, Plackett–Burman and Box–Behnken tests, the influence of rotation speed, flow rate, tooth number and tooth shape were studied. The regression models of the droplet VMD and SRW were established using multiple quadratic regression fitting of the test data. Secondly, in order to achieve the lowest droplet VMD and SRW, the response surface method and post-hoc multiple comparison method were used to obtain the optimized structure of the atomizer’s rotation ring at different rotation speeds (600–7000 r/min) and flow rates (500–1000 mL/min). Lastly, with the effective swath width (ESW) of the optimized atomizer as the evaluation index, through the Box–Behnken test, the influence of rotation speed, flow rate and spray height were studied. The multiple quadratic regression model of ESW was established with the test data. The test results indicated that rotation speed, flow rate and tooth number had a significant effect on droplet VMD and SRW; tooth shape had no significant effect on the droplet VMD and SRW, however, the square tooth shape had the best atomization effect; and rotation speed, flow rate and spray height had a significant effect on ESW. The optimized structural parameters were tooth shape: square, and tooth number: 20. The determination coefficient R2 of the regression model of VMD, SRW and ESW were 0.9976, 0.9770 and 0.9974, respectively, which indicates that the model was accurate, and can evaluate and predict the spray effect. This paper provides an optimized dual-atomization centrifugal atomizer, and its regression models of VMD, SRW and ESW for UAV applications can provide a reference for efficient UAV spraying.

Entropy Generation and Regression Analysis of Magnetohydrodynamic Stagnation Point Flow of a Casson Fluid with Radiative and Dissipative Heat Transfer and Hall Effects

The phenomenon of heat transfer is prevalent in industries and has an extensive range of applications. However, mostly the discussion of heat transfer problems is limited to the study of the first law of thermodynamics, which deals with energy conservation. It is just restricted to the quantity of energy, not to its quality; i.e., there is no difference between the work (high‐grade energy) and the heat (low‐grade energy). A measurement of the degree of randomness of energy in a system is known as entropy. It is unavailable for doing useful work because work takes place only from ordered molecular motion. Even though many boundary layer models exist in the literature to investigate the flow and heat transfer of various fluids along a stretching surface, they have not yet been used at their maximum ability. The main motive of the current research is to discuss entropy generation or its minimization during heat transfer. This work presents an entropy generation analysis for the transient three‐dimensional stagnation point flow of a hydromagnetic Casson fluid flowing over a stretching surface in the existence of Hall current, viscous dissipation, and nonlinear radiation. The physical configuration of the present work is described in terms of partial differential equations (PDEs) of nonlinear nature. Furthermore, these PDEs are converted into ordinary differential equations by using some relevant similarity transformations. An efficient numerical method named as the spectral quasilinearization method (SQLM) is used to solve this model. The expression of the Bejan number and volumetric entropy generation rate is also computed. A parametric analysis, including the essential physical parameters, is performed to examine the influences of distinct flow parameters on the velocity profile, temperature profile, Bejan number, entropy generation number, and the coefficients of skin friction and the Nusselt number. In order to further insight into the emerging physical quantities of engineering interest, multiple quadratic regression models are used to estimate the coefficients of skin friction and heat transfer.

Entropy generation analysis on convective radiative stagnation point flow of a Casson nanofluid in a non-Darcy porous medium with induced magnetic field and activation energy: the multiple quadratic regression model

The present article analyzes the entropy generation on the nonlinear thermally radiating magnetohydrodynamic Casson nanofluid flow closer to the stagnation point inside a non-Darcy porous medium with viscous dissipation, magnetic dissipation, mixed convection, and heat generation. The induced magnetic field's impact and the implications of the chemical reaction and the activation energy are also included in the study. A mathematical model based on the substantive problem is developed, consisting of nonlinear partial differential equations and compatible boundary conditions. The mathematical model is converted to a set of nonlinear ordinary differential equations with appropriate boundary conditions using a suitable similarity transformation, which is then solved using the spectral quasi-linearization method. A complete examination is executed for achieving in-depth information of different varying flow parameters' consequences on the flow field and the significant physical quantities using several graphs and tables. Using the regression models on the reduced Nusselt number NuxRex−1/2 and the reduced Sherwood number ShxRex−1/2, the maximum relative errors are shown as 0.15%–0.30% and 0.016024%–0.016225%, respectively. The present results signify that the larger velocity ratio parameter boosts the velocity along the x-axis and the transverse velocity for M = 3, but the transverse velocity for M = 1, temperature, and induced magnetic field follow a reverse pattern.

The Effects of Price Dispersion on Sales in the Automobile Industry: A Dynamic Panel Analysis

Price dispersion is an important indicator of pricing strategy and market efficiency. However, the relationship between price dispersion and sales has not been explored, especially for durable goods such as automobiles. In this study, we use a unique data set from Autohome comprising the actual transaction prices of buyers to assess the extent of price dispersion in the new automobile market. Based on an empirical analysis of over 222,592 price observations for 59 vehicle models collected over a period of 48 months, we find that the percentage difference ( PD) and coefficient of variation ( CV) of new automobile transaction prices are 43.4% and 9.9%, respectively. In addition, the empirical results show that the price dispersions lower for non-sedan type, Chinese car brands, and produced by state-owned companies. We further investigate whether the increase in the price dispersion of a new automobile has a positive impact on automobile sales using a multiple quadratic regression model. The findings show that price dispersion has positively impact of sales. More interestingly, negative quadratic effects are observed, indicating a concave-down-increasing relationship between price dispersion and sales. This implies that an extreme price dispersion is less helpful than a moderate price dispersion. These findings advance knowledge of consumer buying behavior and seller pricing strategies, with important theoretical contributions and practical implications for automobile companies.

Multi-objective optimization of disc brake structure based on heat transfer performance

As an important basis for its structural optimization design, the heat transfer performance has a key influence on the reliability of automobile brake. Based on the finite element method, the transient heat transfer of automobile disc brake is analyzed under the condition of dynamic convection heat transfer coefficient. According to the simulation results, the CCD (Central Composite Design) sampling scheme is used to transform the optimization variable and target variable into multiple design points in the decision space. The optimization variable includes the total thickness, the height of the ventilation slot, the angle between the sides of the ribs, the number of ribs while the target variable includes the mass and temperature peak. According to the multiple quadratic regression model, the response surface function is constructed, and the approximate model of optimization analysis is obtained. The error analysis shows that the response surface function is equipped with good fitting accuracy. In order to facilitate the extremum search, the optimization of the quality is transformed into the constraint condition, and the multi-objective optimization problem of the brake disc is transformed into the single objective optimization problem. Through the sequential quadratic programming method, the Pareto optimal solution set of the optimal mathematical model is found. The results show that the temperature peak value is reduced by 7.8 % under the condition where the quality of the ventilation plate is basically unchanged. By weighting the Pareto optimal solution sets of different quality intervals, a good result evaluation of ventilation panel optimization is achieved.

A comparative evaluation of the effects of copper and nickel on the growth of the freshwater fish Cyprinus carpio and amelioration by Pistia stratiotes

The main objectives of this research were to identify if the presence of the aquatic weed Pistia stratiotes in the medium could influence the growth of the fish Cyprinus carpio when chronically exposed to sub-lethal concentrations of Cu (0.05 and 0.1 mg/L) and Ni (0.5 and 1.0 mg/L) in the presence of the weed and to compare between effects of Cu and Ni. Experiments were conducted in cement tanks for 90 days. Accumulation of Cu and Ni in water, sediment, fish and weed was determined by Atomic Absorption Spectrophotometer at the end of the experiments. The data were taken as factors to evaluate the interaction between the treatments of metals and weed and their impact on the growth of the fish. Multiple quadratic regression models followed by surface response plots were used to evaluate the interactions and their effects on the growth of C. carpio. The results indicated that the presence of the weed could reduce the accumulation of Cu and Ni in the sediment and fish and thus could ameliorate the ill effects of these metals on the growth of the fish. But there was a difference in growth response between the metals. By using the quadratic polynomial regression model and the surface response plot, it was revealed that Cu produced more deleterious effects on the growth of C. carpio than Ni. The weed interacted better with Cu than Ni, but for both the metals, the weed failed to prevent adverse effects on the growth of fish at a higher concentration of the metals used. The quadratic polynomial regression model followed by the surface response plot is a powerful tool to analyze the interaction between the weed and the treatments of metals and to compare the adverse effects of Cu and Ni on the growth of C. carpio.

Cottonseed Kernel Powder as a Natural Health Supplement: An Approach to Reduce the Gossypol Content and Maximize the Nutritional Benefits

Cottonseed is one of the important by-products of the cotton crop. Researchers claim that cottonseed with less than 0.45% of gossypol is quite good for human consumption and animal feeding because it is a rich source of protein, edible oil, and energy. Total and free gossypols are the influencing parameters that reduce the edible nature of the cottonseed. In the present work, multiple quadratic regression models have been prepared to predict the reduction in the free and total gossypol percent. This response surface method (RSM)-based approach was applied to investigate the combined effect between input parameters such as acetone level, time of extraction, liquid-to-solid ratio (LSR), and the number of extraction cycles, whereas output responses are free and total gossypol reduction percentage. Analysis of Variance (ANOVA) has been performed to determine the highly significant parameter. The optimum combination of input parameters was determined using the RSM-based desirability approach, and confirmatory experiments were performed to validate the combination. Results revealed that the number of extraction cycles and liquid-to-solid ratio significantly affects the reduction of free and total gossypol levels. The values of r-square were found above 0.9, which indicates that the developed models are suitable and reliable for predicting free and total gossypol reduction percentage.

Research on Recovery Mechanism and Process of Waste Thermosetting Phenolic Resins Based on Mechanochemical Method

The present study analyzed the recovery mechanism of the thermosetting phenolic resin waste, optimizing the recovery process parameters, based on the mechanochemical recovery method. The physical and chemical structure of the ultrapulverized phenolic resin powder was characterized by the low‐field NMR (nuclear magnetic resonance), IR (infrared spectroscopy), and SEM (scanning electron microscopy). The recovery process parameters were designed by using the response surface analysis method, and the multiple quadratic regression model was established and the multiobjective process parameter was optimized. The results show that the body network structure of the material is destroyed during the crushing process. The intensity of the internal cross‐linking signal is reduced and tends to be stable at about 60%, when the particle size exceeds 120 mesh. The cross‐linking bonds methylene (‐CH2‐) in the main chain of the molecular chain and the C‐O bond in the methylol group on the branch are broken. The tensile strength of the recycled sheet made of the phenolic resin powder is 8.27 MPa, and the bending strength is 17.76 Mpa through the mechanical properties test. The influences on the change rate of the cross‐linking signal intensity and the yield of the recycled powder are in the following order: rotation speed, feed size, time, and feed volume. The best recovery parameters are as follows: rotation speed of 2820 r/min, time of 80 min, feed particle diameter of 0.43 mm, and feed volume of 60 g.

OPTIMIZATION OF EDTA ENHANCED SOIL WASHING ON MULTIPLE HEAVY METALS REMOVAL USING RESPONSE SURFACE METHODOLOGY

This research presents the optimization of soil washing conditions in the removal of multiple heavy metals (Cu-Pb-Zn-Cd) under the using of ethylenediaminetetraacetic acid (EDTA). The optimum combination of washing parameters in a bench-scale soil washing experiments is determined by response surface methodology (RSM). Central composite design is applied after single factor experiment, EDTA concentration, solid-to-liquid ratio and washing time are evaluated variables for the removal processes, and the regression models of HMs are constructed. The results show that, EDTA concentration and solid-to-liquid ratio are significant factors for this process. Subsequently, 50% of Cu removal was set as the optimum target to optimize the combined conditions, through the building of multiple quadratic regression models, the optimal condition combination is determined that EDTA concentration is 0.0026 mol·L-1, solid-to-liquid ratio is 1:22, washing time is 3.89 h, the extraction rate of Pb, Zn, Cd is predicted to be 78%, 75% and 71%, respectively.

Directional, stabilizing, and disruptive trait selection as alternative mechanisms for plant community assembly.

How plant functional traits (e.g., seed mass) drive species abundance within communities remains an unsolved question. Borrowing concepts from natural selection theory, we propose that trait-abundance relationships can generally correspond to one of three modes of trait selection: directional (a rectilinear relationship, where species at one end of a trait axis are most abundant), stabilizing (an n-shaped relationship), and disruptive (a u-shaped relationship). Stabilizing selection (i.e., the functional convergence of abundant species) would result from positive density-dependent interactions (e.g., facilitation) or due to generalized trade-offs in resource acquisition/use, while disruptive selection (i.e., the divergence of abundant species) would result from negative density-dependent interactions (e.g., competition) or due to environmental heterogeneity. These selection modes can be interpreted as proxies for community-level trait-fitness functions, which establish the degree to which traits are truly "functional". We searched for selection modes in a desert annual-plant community in Argentina (which was divided into winter and summer guilds) to test the hypothesis that the relative importance of disruptive mechanisms (competition, disturbances) decreases with the increase of abiotic stress, a stabilizing agent. Average density was analyzed as a function of eight traits generally linked to resource acquisition and competitive ability (maximum plant height, leaf size, specific leaf area, specific root length), resource retention and stress tolerance (leaf dissection, leaf dry matter content, specific root volume), and regeneration (seed mass) using multiple quadratic-regression models. Trait selection was stabilizing and/or directional when the environment was harshest (winter) and disruptive and/or directional when conditions were milder (summer). Selection patterns differed between guilds for two important traits: plant height and seed mass. These results suggest that abiotic stress may drive within-community functional convergence independently of the trait considered, opposing the view that some traits may be inherently convergent while others divergent. Our quadratic model-based approach provides standardized metrics of both linear and nonlinear selection that may allow simple comparisons among communities subjected to contrasting environmental conditions. These concepts, rooted in natural selection theory, may clarify the functional link between traits and species abundance, and thus help untangle the contributions of deterministic and stochastic processes on community assembly.

An economical, environmental, and social comparison between vacuum and gravity sewers in decentralized sanitation systems, with Egypt as a case study

The conventional gravity sewer is the most commonly used rural sewerage system in developing countries. However, this system has many technical, economic, environmental, and social disadvantages. Vacuum sewers could serve as a good competitor as an alternative system to conventional gravity sewers. A sample of 33 rural villages with populations of <10,000 people is selected from Egypt. A statistical analysis was done using SPSS and STATISTICA software where population and area variables had the most significant effect on the calculation of investment, operation, and maintenance costs. It was found that investment costs for the vacuum system were mostly lower than for the conventional one, while operational and maintenance costs played significant roles. Prediction models were obtained based on multiple quadratic regression models. It was found that the vacuum system was economically competitive in large villages with low population densities. Environmentally and socially, the vacuum sewers proved to be better than gravity sewers.

RELAÇÃO ENTRE ATRIBUTOS FÍSICOS E QUÍMICOS DOS SOLOS E A PRODUTIVIDADE DE CAPIM DOURADO NA REGIÃO DO JALAPÃO, TO

Na região do Jalapão, no Estado do Tocantins, existem grandes áreas contínuas de Neossolos Quartzarênicos, com desenvolvimento do capim dourado (Syngonanthus nitens),espécie nativa utilizada na confecção de artesanatos nessa região, possuindo destacada importância na economia local. O objetivo deste estudo foi verificar a relação entre os atributos físicos e químicos dos solos e a produtividade de capim dourado nos Campos Limpos Úmidos associados às Veredas no Parque Estadual do Jalapão. Foram coletadas amostras de solo e escapos de capim dourado e realizadas medições de declividade do terreno ao longo de caminhamento ou transeções perpendiculares às linhas de drenagem das Veredas selecionadas para o estudo. Foram identificados três tipos principais de solos ao longo das transeções: Neossolo Quartzarênico órtico típico, Neossolo Quartzarênico hidromórfico típico e Organossolo Háplico fíbrico típico. A produtividade de capim dourado foi analisada por meio de modelos de regressão múltipla, envolvendo 26 variáveis dos solos. Em razão da significância, o modelo final ficou constituído por seis dessas variáveis: pH, Mg2+, Ca2+, areia fina, argila e umidade do solo. O modelo de regressão quadrática múltipla envolvendo essas seis variáveis contemplou R2 de 0,85 e R2 ajustado de 0,81 da relação avaliada, onde a umidade dos solos foi a variável mais importante.

Microwave-low-pressure process (MWLP): An effective technology applied in extraction of total polyphenols

Abstract: The microwave-low-pressure process (MWLP) of total polyphenols from Chaenomeles speciosa fruit was studied, and the advantages of MWLP were further evaluated by comparing with ultra high pressure (UHP) and microwave-assisted extraction (MAE). The influences of liquid/solid ratio, extraction time, pressure, and ethanol concentration on the performance of MWLP were investigated. Thereafter, the interactive variables were further optimized by the stepwise multiple quadratic regression model on the basis of the previous univariate analysis. The results showed that temperature as an intermediate variable in MWLP significantly affected the yields of polyphenols and 3-o-caffeoyl-quinic acid, which was determined by pressure and ethanol concentration. The optimized parameters were proved to be valid because the results predicted by the stepwise multiple quadratic regression model equations fit well with the experimental results. Compared with UHP, the predominance of MWLP was that the extraction time was shortened and the cost of extraction equipment was lowered. MWLP is an effective technology since MWLP was superior to MAE based on extraction yield, solvent loss and reproducibility. Keywords: Microwave-low-pressure process (MWLP), total polyphenols, Chaenomeles speciosa fruit, model optimization, performance evaluation DOI: 10.3965/j.ijabe.20130604.010 Citation: Hu Z Q, Jia L L, Yue T L. Microwave-low-pressure process (MWLP): An effective technology applied in extraction of total polyphenols. Int J Agric & Biol Eng, 2013; 6(4): 84－95.

Multiple Regression Prediction Model for Cutting Forces in Turning Carbon-Reinforced PEEK CF30

Among the thermoplastic polymers available, the reinforced polyetheretherketone with 30% of carbon fibres (PEEK CF 30) demonstrates a particularly good combination of strength, rigidity, and hardness, which prove ideal for industrial applications. Considering these properties and potential areas of application, it is necessary to investigate the machining of PEEK CF30. In this study, response surface methodology was applied to predict the cutting forces in turning operations using TiN-coated cutting tools under dry conditions where the machining parameters are cutting speed ranges, feed rate, and depth of cut. For this study, the experiments have been conducted using full factorial design in the design of experiments (DOEs) on CNC turning machine. Based on statistical analysis, multiple quadratic regression model for cutting forces was derived with satisfactory -squared correlation. This model proved to be highly preferment for predicting cutting forces.