Relevant bibliographies by topics / Quadratic Response Surface

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Quadratic Response Surface'

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Published: 8 September 2023

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Journal articles on the topic "Quadratic Response Surface"

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A.V, Dattatreya Rao, and Seshubabu P. "Quadratic response surface designs." International Journal of Advances in Computing and Information Technology 1, no. 2 (April 20, 2012): 174–81. http://dx.doi.org/10.6088/ijacit.12.10022.

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Shehzad, Muhammad Ahmed, Adnan Bashir, Muhammad Noor Ul Amin, Saima Khan Khosa, Muhammad Aslam, and Zubair Ahmad. "Reservoir Inflow Prediction by Employing Response Surface-Based Models Conjunction with Wavelet and Bootstrap Techniques." Mathematical Problems in Engineering 2021 (November 10, 2021): 1–9. http://dx.doi.org/10.1155/2021/4086918.

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Reservoir inflow prediction is a vital subject in the field of hydrology because it determines the flood event. The negative impact of the floods could be minimized greatly if the flood frequency is predicted accurately in advance. In the present study, a novel hybrid model, bootstrap quadratic response surface is developed to test daily streamflow prediction. The developed bootstrap quadratic response surface model is compared with multiple linear regression model, first-order response surface model, quadratic response surface model, wavelet first-order response surface model, wavelet quadratic response surface model, and bootstrap first-order response surface model. Time series data of monsoon season (1 July to 30 September) for the year 2010 of the Chenab river basin are analyzed. The studied models are tested by using performance indices: Nash–Sutcliffe coefficient of efficiency, mean absolute error, persistence index, and root mean square error. Results reveal that the proposed model, i.e., bootstrap quadratic response surface shows good performance and produces optimum results for daily reservoir inflow prediction than other models used in the study.
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Song, Wheyming Tina, and Chien-Chou Su. "CORRELATED SIMULATION EXPERIMENT IN QUADRATIC RESPONSE SURFACE DESIGNS." Journal of the Chinese Institute of Industrial Engineers 19, no. 3 (January 2002): 13–18. http://dx.doi.org/10.1080/10170660209509199.

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Hussey, James R., Raymond H. Myers, and Ernest C. Houck. "Pseudorandom Number Assignment in Quadratic Response Surface Designs." IIE Transactions 19, no. 4 (December 1987): 395–403. http://dx.doi.org/10.1080/07408178708975412.

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Hong, Kyung-Jin, Min-Soo Kim, and Dong-Hoon Choi. "Efficient approximation method for constructing quadratic response surface model." KSME International Journal 15, no. 7 (July 2001): 876–88. http://dx.doi.org/10.1007/bf03185266.

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Ainy Hafeez, Ainy Hafeez, Syed Mohsin Ali Kazmi Syed Mohsin Ali Kazmi, Muhammad Sulaiman Muhammad Sulaiman, and Chaudhry Haider Ali and Nadeem Feroze Chaudhry Haider Ali and Nadeem Feroze. "Optimization of Zinc Ions Removal by Modified Phoenix Dactylifera L. Seeds Using Response Surface Methodology." Journal of the chemical society of pakistan 41, no. 1 (2019): 78. http://dx.doi.org/10.52568/000719/jcsp/41.01.2019.

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The current study investigates the role of Phoenix Dactylifera L. (date palm) seeds as an effective biosorbent for removing Zn+2, a toxic heavy metal pollutant usually found in the waste streams of industries like fertilizer, mining and galvanizing etc. Date palm seeds were washed, dried, crushed in 170-300 um and modified by acidic treatment (0.1 MHNO3). The effect of most important parameters i.e., pH (3.5-6.1), initial zinc ion concentration (5-100mg/l), biosorbent dosage (0.1-1g) and contact time (0.5-60sec) have been studied via design expert software (version 8.0.6) of response surface methodology. The Box-Bhenken Design (BBD) was used in Response Surface Methodology (RSM) for designing the experiments and a number of 29 experiments were run. The model suggested by the design expert software was quadratic as it had maximum R2- value (0.9235) which indicated that the predicted values of quadratic model were best fitted to the experimental values. The significance of the factors was indicated by Analysis of Variance (ANOVA). The results showed that the metal uptake increased by increasing initial zinc concentration and decreasing in biosorbent dosage and pH while the contact time had negligible effect on the response surface. The parameters were numerically optimized and the optimum input parameters obtained were pH = 3.52, initial zinc ion concentration = 59.11ppm, biosorbent dosage = 0.1g and contact time = 60min with a metal uptake of 26.84mg/g. Therefore, (Phoenix Dactylifera L.) seeds substantially removed zinc ions under optimum conditions.
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Han, Feng, Zheng Liang Li, and Wen Liang Fan. "A New Adaptive Higher Order Response Surface Method." Advanced Materials Research 243-249 (May 2011): 5946–54. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5946.

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Response surface method has won numerous concerns in the reliability analysis of structure due to its simplicity and practicability, especially quadratic response surface taking no account of cross terms is most widely used. However, for the complex ultimate state curved surface corresponding to strongly nonlinear, the approximate accuracy of quadratic response surface is apparently not enough, causing a biggish error in estimation of reliability. Although, theoretically, higher order response surface method can resolve this problem, the sharp increase of undetermined coefficient reduces calculation efficiency, and even, cannot achieve. Therefore, on the basis of univariate analysis of multivariable function, an algorithm which can reasonably determine higher order response surface form is presented in this article, able to effectively reduce the number of undetermined coefficients in response surface, so as to reduce computational difficulties and put forward improving measures for possible problems; In addition, based on the tactics of number-theoretic setpoint, a type of scheme of number-theoretic selecting point applicable to response surface method has been developed. Finally, through the analysis of examples, the suggested algorithm was validated, with the result showing that the algorithm has good accuracy and efficiency.
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Law, Poh Gaik, Noor Haida Sebran, Ashraf Zin Zawawi, and Azlan Shah Hussain. "Optimization Study of Biomass Hydrogenation to Ethylene Glycol Using Response Surface Methodology." Processes 8, no. 5 (May 15, 2020): 588. http://dx.doi.org/10.3390/pr8050588.

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Statistical-based study using response surface methodology (RSM) was conducted to study the effects of process parameters towards biomass hydrogenation. Using Malaysian oil palm empty fruit bunches (EFB) fibres as feedstock, the central composite design (CCD) technique was employed and 18 runs were generated by CCD when four parameters (mass ratio of binary catalyst, hydrogen pressure, temperature and mass ratio of catalyst to feedstock) were varied with two center points to determine the effects of process parameters and eventually to get optimum ethylene glycol (EG) yield. RSM with quadratic function was generated for biomass hydrogenation, indicating all factors except temperature, were important in determining EG yield. Analysis of variance (ANOVA) showed a high coefficient of determination (R2) value of >0.98, ensuring a satisfactory prediction of the quadratic model with experimental data. The quadratic model suggested the optimum EG yield should be >25 wt.% and the EG yield results were successfully reproduced in the laboratory.
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Qin, Li, Wei Lin Peng, and Wei Han. "High-Order RSM for Dynamic Reliability of UHV Transmission Tower." Applied Mechanics and Materials 799-800 (October 2015): 1295–98. http://dx.doi.org/10.4028/www.scientific.net/amm.799-800.1295.

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As transmission tower system has the characteristics of large-span and spatial truss structure, the study of the reliability is also developed on the basis of space truss research and large-span structure system. As simple and suitable, RSM (response surface method), in particular, quadratic response surface without considering the cross term is often used in reliability calculation. However, strong nonlinear limit that corresponding to a complex surface, the accuracy of quadratic response surface is inadequate, causing greater reliability estimation error. High-order response surface solves it well. To this end, based on univariate analysis of multivariate function, a reasonable algorithm as to assure that the form of higher-order response surface is proposed; on the algorithm is verified by given examples, the result shows better accuracy and efficiency .
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Gengec, E., M. Kobya, E. Demirbas, A. Akyol, and K. Oktor. "Electrochemical treatment of Baker's yeast wastewater containing melanoidin: optimization through response surface methodology." Water Science and Technology 65, no. 12 (June 1, 2012): 2183–90. http://dx.doi.org/10.2166/wst.2012.130.

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Effluents from Baker's yeast production plant contain a high percentage of color and a large amount of organic load. In the present study, Baker's yeast wastewater (BYW) is treated with the electrocoagulation (EC) process using Al electrodes. Operating parameters (pH, current density, color intensity and operating time) are optimized by response surface methodology (RSM). Quadratic models are developed for the responses which are removal efficiencies of color, chemical oxygen demand (COD) and total organic carbon (TOC) and operating cost (OC). Optimum operating parameters and responses are determined as initial pH 5.2, current density of 61.3 A/m2 and operation time of 33 min, and 71% of color, 24% of COD, 24% of TOC removal efficiencies and OC of 0.869 €/m3, respectively. The quadratic model fits for all responses very well with R2 (>0.95). This paper clearly shows that RSM is able to optimize the operating parameters to maximize the color, COD and TOC removal efficiencies and minimize the OC.
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Dissertations / Theses on the topic "Quadratic Response Surface"

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Oliveira, Patricia Candioto Migliari. "Modelagem e otimização de fermentadores para obtenção de etanol." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266343.

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Orientador: Rubens Maciel Filho
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
Made available in DSpace on 2018-08-08T18:46:56Z (GMT). No. of bitstreams: 1 Oliveira_PatriciaCandiotoMigliari_D.pdf: 1584587 bytes, checksum: 8622cb86aacfe987908422e98c40d2c8 (MD5) Previous issue date: 2007
Resumo: O trabalho envolveu modelo estruturado adaptado de um modelo estruturado de crescimento para processo de fermentação contínua realizado em um bioreator do tipo torre com células imobilizadas para produção de etanol. O modelo estruturado utilizado inclui equações de balanço para as rotas metabólicas fermentativa e respiratória, assim como termos cinéticos para o efeito de inibição pelo etanol, substrato e saturação celular no pellet. Os parâmetros cinético do modelo estruturado foram otimizados através da metodologia desenvolvida por Rivera (2005) onde envolve a aplicação de Algoritmo Genético, Planejamento Fatorial Fracionário proposto por Plackett Burman (1946) e Algoritmo Quasy Newton. Os resultados obtidos na simulação do modelo utilizando os parâmetros otimizados por esta metodologia representou de forma efetiva o modelo. A otimização do processo teve inicio com a Análise de Superfície de Resposta, que consistiu em um planejamento fatorial em estrela de dois níveis (-1 e +1) com um ponto central. A metodologia por Superfície de Resposta mostrou-se uma ferramenta poderosa para otimização preliminar das variáveis operacionais no sentido de que seus resultados foram usados como estimativas iniciais para o procedimento formal de otimização, SQP (Programação Quadrática Sucessiva). Esta metodologia de Superfície de resposta possibilita visualização do comportamento das variáveis que se quer otimizar, identificando a região do ponto ótimo, o que não é possível pelo método SQP. A metodologia SQP foi implementada com sucesso no modelo determinístico, obtendo as melhores condições de operação para as variáveis manipuláveis
Abstract: The work involved adapted of a structured model of growth structured model for process of continuous fermentation accomplished in a bioreator of the type tower with immobilized cells for etanol production. The used structured model includes reaction rate equations for the respiratory and glicolitic metabolic pathways, as well as kinetic terms for the inhibition effect for the etanol, substrate and cellular saturation in the pellet. The kinetic of the structured model parameters went optimized through to methodology developed by Rivera (2005) where it involves the application of Genetic Algorithm, methodology of Plackett¿Burman (1946) and Algorithm Quasi Newton. The results obtained in the simulation of the model using the parameters optimized for this methodology represented in an effective way the model. The optimization of the process had I begin with the Analysis of Surface of Answer, that consisted of a planning fatorial in star of two levels (-1 and +1) with a central point. The methodology for Surface of Answer a powerful tool was shown for preliminary optimization of the operational variables in the sense that its results were used as initial estimates for the formal procedure of optimization, SQP. This methodology of answer Surface facilitates visualization of the behavior of the variables that if that otimizar, identifying the area of the great point, what is not possible for the method SQP. The methodology SQP was implemented with success in the model deterministic, obtaining the best operation conditions for the variables manipulated.
Doutorado
Desenvolvimento de Processos Químicos
Doutor em Engenharia Química
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Khalid, Adeel S. "Development and Implementation of Rotorcraft Preliminary Design Methodology using Multidisciplinary Design Optimization." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14013.

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A formal framework is developed and implemented in this research for preliminary rotorcraft design using IPPD methodology. All the technical aspects of design are considered including the vehicle engineering, dynamic analysis, stability and control, aerodynamic performance, propulsion, transmission design, weight and balance, noise analysis and economic analysis. The design loop starts with a detailed analysis of requirements. A baseline is selected and upgrade targets are identified depending on the mission requirements. An Overall Evaluation Criterion (OEC) is developed that is used to measure the goodness of the design or to compare the design with competitors. The requirements analysis and baseline upgrade targets lead to the initial sizing and performance estimation of the new design. The digital information is then passed to disciplinary experts. This is where the detailed disciplinary analyses are performed. Information is transferred from one discipline to another as the design loop is iterated. To coordinate all the disciplines in the product development cycle, Multidisciplinary Design Optimization (MDO) techniques e.g. All At Once (AAO) and Collaborative Optimization (CO) are suggested. The methodology is implemented on a Light Turbine Training Helicopter (LTTH) design. Detailed disciplinary analyses are integrated through a common platform for efficient and centralized transfer of design information from one discipline to another in a collaborative manner. Several disciplinary and system level optimization problems are solved. After all the constraints of a multidisciplinary problem have been satisfied and an optimal design has been obtained, it is compared with the initial baseline, using the earlier developed OEC, to measure the level of improvement achieved. Finally a digital preliminary design is proposed. The proposed design methodology provides an automated design framework, facilitates parallel design by removing disciplinary interdependency, current and updated information is made available to all disciplines at all times of the design through a central collaborative repository, overall design time is reduced and an optimized design is achieved.
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Lo, Ming-Huang, and 羅明煌. "Bayes estimate of the single factor quadratic response surface under the noninfmative prior." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/47001337830263587154.

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Lee, Chang Cha, and 李長洽. "A Study of the Bayesian Estimation of the Stationary Point of Single Factor Quadratic Response Surface." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/91597397214303533460.

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碩士
中原大學
工業工程研究所
81
The stationary point of a response surface function bears the location and magnitude coordinates of the maximum or minimum response value. In the context of industrial applications, the precise determination of the location parameter implies achievment of an optimal process settings rendering an optimal yield and minimal cost. In this research, we systematically consider nine different combinations of priors. It covers the range from completely non- informative, to partially informative and comprehensively informative, we develop the posterior distributions for the parameters of interest. We evaluate the marginal posterior distribution of concerned parameters through characteristic model. We use a set of observations and explore their point estimates and related statistics, namely posterior mean, mode, variance, and HPD. Both numerical and Gibbs sampling methods are used. We also carry out a robust analysis over different combinations of priors and also different hyperparameters setup. It's found that the priors which have thick tails or greater variance is more robust than the others. Besides, we compare the computing time between traditional numerical method and Gibbs sampling method. In acceptable precision, the computing time of numerical method is ten times of Gibbs sampling. It is therefore justified that the Gibbs sampling can be used as a good alternative of numerical method.
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Dayal, Akshit. "Robust Optimization of Nanometer SRAM Designs." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7589.

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Technology scaling has been the most obvious choice of designers and chip manufacturing companies to improve the performance of analog and digital circuits. With the ever shrinking technological node, process variations can no longer be ignored and play a significant role in determining the performance of nanoscaled devices. By choosing a worst case design methodology, circuit designers have been very munificent with the design parameters chosen, often manifesting in pessimistic designs with significant area overheads. Significant work has been done in estimating the impact of intra-die process variations on circuit performance, pertinently, noise margin and standby leakage power, for fixed transistor channel dimensions. However, for an optimal, high yield, SRAM cell design, it is absolutely imperative to analyze the impact of process variations at every design point, especially, since the distribution of process variations is a statistically varying parameter and has an inverse correlation with the area of the MOS transistor. Furthermore, the first order analytical models used for optimization of SRAM memories are not as accurate and the impact of voltage and its inclusion as an input, along with other design parameters, is often ignored. In this thesis, the performance parameters of a nano-scaled 6-T SRAM cell are modeled as an accurate, yield aware, empirical polynomial predictor, in the presence of intra-die process variations. The estimated empirical models are used in a constrained non-linear, robust optimization framework to design an SRAM cell, for a 45 nm CMOS technology, having optimal performance, according to bounds specified for the circuit performance parameters, with the objective of minimizing on-chip area. This statistically aware technique provides a more realistic design methodology to study the trade off between performance parameters of the SRAM. Furthermore, a dual optimization approach is followed by considering SRAM power supply and wordline voltages as additional input parameters, to simultaneously tune the design parameters, ensuring a high yield and considerable area reduction. In addition, the cell level optimization framework is extended to the system level optimization of caches, under both cell level and system level performance constraints.
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Book chapters on the topic "Quadratic Response Surface"

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Enkhbat, Rentsen, and Yadam Bazarsad. "General Quadratic Programming and Its Applications in Response Surface Analysis." In Springer Optimization and Its Applications, 121–37. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-89496-6_6.

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Huang, G., Y. Zhuge, T. Benn, and Y. Liu. "Optimisation of Limestone Calcined Clay Cement Based on Response Surface Method." In Lecture Notes in Civil Engineering, 103–12. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3330-3_13.

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AbstractLimestone calcined clay cement (LC3) is a new type of cement that contains Portland cement, calcined clay, and limestone. Compared with traditional cement clinker, LC3 reduces CO2 emissions by up to 40%, and is a promising technology for the cement industry to achieve its emission target. We used a numerical approach to predict the optimum composition of LC3 mortar. The experiments were performed using central composite rotational design under the response surface methodology. The method combined the design of mixtures and multi-response statistical optimization, in which the 28-day compressive strength was maximized while the CO2 emissions and materials cost were simultaneously minimized. The model with a nonsignificant lack of fit and a high coefficient of determination (R2) revealed a well fit and adequacy of the quadratic regression model to predict the performance of LC3 mixtures. An optimum LC3 mixture can be achieved with 43.4% general purpose cement, 34.16% calcined clay, 20.6% limestone and 1.94% gypsum.
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Guo, Jiaxu, Shaowei Hu, Xuan Zhao, Xiu Tao, and Ying Nie. "Compressive Strength Performance of Additives for Cement-Based Grouting Material with Low Water-Binder Ratio by Response Surface Methodology." In Lecture Notes in Civil Engineering, 368–79. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1260-3_34.

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AbstractIn order to research the influence and the function mechanism of calcium formate and defoaming agent on the compressive strength of cement-based grouting material with low water-binder ratio at different ages, quadratic polynomial regression models were established by RSM, and the mix proportion was optimized. The function mechanism of additives was analysed by macroscopic mechanical properties and microstructure. The results indicated that the response surface method is scientific in optimizing the mix proportion of cement-based grouting material. The optimal mix proportion was obtained as fallow: the calcium formate was 0.64%, the water-binder ratio was 0.21 and the defoaming agent was 0.26%, with taking 1d, 3d, 28d compressive strength as the optimization objective. Calcium formate is highly significant for the early compressive strength of cement-based grouting materials with low water-binder ratio, while the water-binder ratio and defoaming agent are highly significant for that of the middle and late period. Calcium formate promotes the formation of CSH gel and $$\mathrm{Ca}{\left(\mathrm{OH}\right)}_{2}$$ Ca OH 2 crystallization in the early period, and the defoaming agent can effectively reduce macropores. The results can provide an optimization method for the mix proportion design of cement-based grouting material and a theoretical reference for its mechanical properties.
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"11. Quadratic Response Surface Models." In Analysis Messy Data ,Volume 2, 154–68. Boca Raton London New York Washington, D.C.: CRC Press, 1989. http://dx.doi.org/10.1201/9781315172194-12.

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Zhang, Yang, and Yue Wu. "Introducing Machine Learning Models to Response Surface Methodologies." In Response Surface Methodology in Engineering Science [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98191.

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Traditional response surface methodology (RSM) has utilized the ordinary least squared (OLS) technique to numerically estimate the coefficients for multiple influence factors to achieve the values of the responsive factor while considering the intersection and quadratic terms of the influencers if any. With the emergence and popularization of machine learning (ML), more competitive methods has been developed which can be adopted to complement or replace the tradition RSM method, i.e. the OLS with or without the polynomial terms. In this chapter, several commonly used regression models in the ML including the improved linear models (the least absolute shrinkage and selection operator model and the generalized linear model), the decision trees family (decision trees, random forests and gradient boosting trees), the model of the neural nets, (the multi-layer perceptrons) and the support vector machine will be introduced. Those ML models will provide a more flexible way to estimate the response surface function that is difficult to be represented by a polynomial as deployed in the traditional RSM. The advantage of the ML models in predicting precise response factor values is then demonstrated by implementation on an engineering case study. The case study has shown that the various choices of the ML models can reach a more satisfactory estimation for the responsive surface function in comparison to the RSM. The GDBT has exhibited to outperform the RSM with an accuracy improvement for 50% on unseen experimental data.
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J. Zhang, Jian. "In Search of Optimal Laser Settings for Lithotripsy by Numerical Response Surfaces of Ablation and Retropulsion." In Response Surface Methodology in Engineering Science [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96271.

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Even though ureteroscopic laser lithotripsy (URSL) has become the preferred treatment option for urolithiasis due to shorter operation time and a better stone-free rate, the optimum laser pulse settings for URSL with the shortest operative times remain unknown. In this chapter, two sets of design of experiments (DOE) were conducted with response surface methodology: 1) the quantitative responses of calculus ablation and retropulsion in terms of the pulse energy, pulse width, and the number of pulses of a prototype Chromium (Cr3+), Thulium (Tm3+), Holmium (Ho3+) triple doped yttrium aluminum garnet (CTH:YAG) laser system. The ablation or retropulsion is inversely proportional to the pulse width, and the pulse width has a higher impact coefficient for the ablation than for the retropulsion. The quadratic fit of the response surface for the volume of ablation has a nonlinear relationship with the pulse width and number of pulses. 2) the laser setting optimization of laser lithotripsy of a commercially available CTH: YAG laser system. The experimental setup is based on a benchtop model first introduced by Sroka’s group. Comparing to frequency, the laser pulse energy or peak power has a higher impact coefficient to stone retropulsion as compared to stone ablation in CTH: YAG laser lithotripsy. The most efficient way to curtail stone retropulsion during laser lithotripsy is to lower the laser pulse peak power.
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N. Njoku, Chigoziri, and Samuel K. Otisi. "Application of Central Composite Design with Design Expert v13 in Process Optimization." In Response Surface Methodology - Research Advances and Applications [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.109704.

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This chapter is focused on the study application of central composite design, in response surface methodology. We have reviewed this concept and applied it to optimize Biodiesel yield from transesterification of methanol and vegetable oil with a catalyst derived from eggshell using design expert 13. This optimization was carried out with reaction conditions of reaction time, methanol to oil ratio, catalyst loading, and reaction temperature. Data used as an instance was collected and analyzed from the work of Tshizanga et al. and the result obtained for a randomized experiment showed at a 95% confidence level that all the factors affected the product’s output. About 91% yield was obtained and operating parameters were optimized at a temperature of around 61%. Methanol to oil ratio of 22.13, and catalyst loading of around 3.7 wt%. This chapter provided a step-by-step guide on how to carry out this experiment using design expert 13, a reduced Quadratic model with a significant P-value of 0.0325 shows the model is significant, as indicated by an f-value of 3.57. An F-value might be caused by noise only in 3.25% of cases. The run was reduced to 18 compared to the 20 runs originally used by Tshizanga et al.
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Nathalal Dabhi, Mukesh. "Enzymatic Process for Pigeon Pea." In Legumes Research - Volume 1. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.100853.

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Pigeon pea is generally used as a dhal i.e., in split form therefore, it is important to check its splitting i.e., hulling efficiency and maximum dhal recovery. Pre-treatments are commonly given for loosening and removing of the seed coat with retaining its edible portion. Enzymes viz. xylanase, pectinase and cellulose were applied to evaluate the dehusking properties of pigeon pea grains. The effect of four enzymatic parameters, i.e., enzyme concentration (20–50 mg 100 g−1 dry matter), incubation time (4–12 h), incubation temperature (35–55°C) and tempering water pH (4.0–6.0) on dehusking efficiency were optimized with statistical package response surface methodology (RSM). In which the hulling efficiency with a high value for the coefficient of determination R2 (0.92) described satisfactorily quadratic model. It predicted 76.54–82.80% hulling efficiency, 20.70–25.30% protein content and 12.42–15.10 min cooking time at optimized enzyme concentration of 27.64–31.34%, incubation time 7–9 h, incubation temperature 43–45°C and 5–6 pH value for different varieties of pigeon pea as compared to 66.00–78.30% hulling efficiency, 18.74–21.81% protein content and 13.23–18.00 min cooking time for traditional oil treatment. It shown that increased hulling efficiency and protein content and decreased cooking time for enzyme pretreated pigeon pea compared to the oil pretreated method.
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Esonye, Chizoo, Okechukwu Donminic Onukwuli, Akuzuo Uwaoma Ofoefule, Cyril Sunday Ume, and Nkiruka Jacintha Ogbodo. "Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate Law Based Chemical Kinetics of Its Consecutive Irreversible Methanolysis." In Prunus. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93880.

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For successful industrial scale-up and effective cost analysis of transesterification process, presentation of complimentary research data from process optimization using statistical design techniques, chemical kinetics and thermodynamics are essential. Full factorial central composite design (FFCCD) was applied for the statistical optimization of base methanolysis of sea almond (Terminalia catappa) seed oil using response surface methodology (RSM) coupled with desirability function analysis on quadratic model. Reaction time had the most significant impact on the biodiesel yield. Optimum conditions for biodiesel yield of 93.09 wt% validated at 92.58 wt% were 50.03°C, 2.04 wt% catalyst concentration, 58.5 min and 4.66 methanol/oil molar ratio with overall desirability of 1.00. Ascertained fuel properties of the FAME were in compliance with international limits. GC–MS, FTIR and NMR characterizations confirmed unsaturation and good cold-flow qualities of the biodiesel. Based on power rate law, second-order kinetic model out-performed first-order kinetic model. Rate constants of the triglyceride (TG), diglycerides (DG) and monoglycerides (MG) hydrolysis were in the range of 0.00838–0.0409 wt%/min while activation energies were 12.76, 15.83 and 22.43 kcal/mol respectively. TG hydrolysis to DG was the rate determining step. The optimal conditions have minimal error and would serve as a springboard for industrial scale-up of biodiesel production from T. catappa seed oil.
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Conference papers on the topic "Quadratic Response Surface"

1

Lee, Yongbin, Sunghun Jung, and Dong-Hoon Choi. "Progressive Quadratic Response Surface Modeling Using Inherited Latin-Hypercube Design." In 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7092.

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2

Wahab, M. M. A., V. J. Kurian, M. S. Liew, Z. Nizamani, and D. K. Kim. "Structural Reliability Analysis Using Quadratic Polynomial Response Surface and Finite Element in MATLAB." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54543.

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Many aging jacket platforms are being pushed for continued use beyond their design life due to advancement in oil extracting technology and economic reasons. Thus reassessment to determine the platform safety is vital. But no exact guide on methods to assess the safety of the aging platforms is available. Hence, development of reliability analysis methodologies is an active research area. Meanwhile, reassessment deals with numerous uncertainties especially in the load and resistance variables of a jacket platform. Response Surface methodology, a limit state approximation technique was deployed by many in many engineering fields to apprehend inherent uncertainty. Hence in this work, a reliability analysis methodology that combines simple response surface and finite element approach in MATLAB is adopted. The approach assumes a physical transfer function utilizing explicit multivariate expressions and random variables. Also, this avoids large number of finite element simulation required for any probabilistic analysis. The methodology developed allows for reliability analysis to be performed based on easy to program procedures. It also addresses the platform and environmental specific uncertainty variables to distinguish the distinctive characteristics of the cases. Upon execution of multiple finite element simulations, response of components and systems are formulated using quadratic polynomial response surface expressions, which eventually are utilized in the limit state functions. Later using numerical techniques in a separate computational routine the reliability indices are estimated. Utilizing the developed method, component and system level reliability indices are obtained. The developed methodology also has been verified with method currently available in the practice as well as with typical simulation method i.e. Monte Carlo Simulation.
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Perez, Victor, John Renaud, and Layne Watson. "Reduced Sampling for Construction of Quadratic Response Surface Approximations Using Adaptive Experimental Design." In 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-1587.

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4

Korngold, Jacob C., and Gary A. Gabriele. "Multidisciplinary Analysis and Optimization of Discrete Problems Using Response Surface Methods." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0023.

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Abstract The objective of this paper is to present a new algorithm to efficiently optimize multidisciplinary, coupled non-hierarchic systems with discrete variables. The algorithm decomposes the system into contributing disciplines, and uses designed experiments within the disciplines to build local response surface approximations to the discipline analysis. First and second order Global Sensitivity Equations are formulated and approximated by experimental data to build approximations to the global design space. The global approximation is optimized using branch and bound or simulated annealing. Convergence is rapid for systems with near quadratic behavior. The algorithm is demonstrated on a unique multidisciplinary learning tool, the Design and Manufacturing Learning Environment. This environment provides multimedia simulation for product life cycle disciplines, including design, manufacturing, marketing, and sales.
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Norman, Narcrisha, and Sonya Smith. "Reducing Large Viking I Based Martian Entry, Descent and Landing Response Surface Methodology Produced Quadratic Models." In 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-3997.

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Maofeng Yang, Hailong You, Xinzhang Jia, and Dan Wang. "An Effective Method to Extract Probability Distribution of Circuit Performance Modeled by Quadratic Response Surface Model." In 2008 International Symposium on Information Science and Engineering (ISISE). IEEE, 2008. http://dx.doi.org/10.1109/isise.2008.212.

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7

Tang, Xiao, Jiaqi Luo, and Feng Liu. "Adjoint-Response Surface Method in Aerodynamic Shape Optimization of Turbomachinery Blades." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56170.

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An adjoint-response surface method is developed to give global representation of cost function in a parametrized design space for turbomachinery blades. Radial basis function (RBF) based and quadratic polynomial (QP) based response surface models are constructed using both the values of cost function and its adjoint gradients with respect to geometry control parameters. The method is tested on a quasi-three dimensional NACA0012 blade row, then applied to the transonic Rotor 67. In preliminary design optimization stage, when the number of undetermined control parameters is large, the QP based model can provide a global image of the cost function in high dimensional design space with a small amount of sample points. In two-parameter fine optimization stage, high resolution can be achieved with the RBF based models. This gradient-enhanced response surface method is useful in guiding designers to discover the global optimum which may be missed by local gradient methods in a complicated design space. It may also be used as substitute of CFD flow solver in time consuming iterative design and optimization.
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Sharma, Naveen, Vaibhav Sharma, and Andallib Tariq. "Performance Optimization of Trapezium Rib Parameters Using Response Surface Methodology." In ASME 2017 Gas Turbine India Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gtindia2017-4881.

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In the present work, transient liquid crystal thermography (LCT) has been used for capturing the temperature field as well as the local heat transfer distribution inside a rectangular duct. Experiments have been carried out in an open loop airflow system at a Reynolds number (based on the channel hydraulic diameter) of 58850 and for rib height to channel hydraulic diameter ratio of 0.125. This investigation emphases headed for assessing the potential impact of design parameters such as chamfering angle and rib pitch to height ratio of the trapezium ribbed rectangular duct on the thermo-hydraulic performances, which forms the basis of analysis while using response surface methodology (RSM). The chamfering angle has been varied from 0 to 20° in a step of 5°, while the rib pitch to height ratio is varied from 8 to 12 in a step of 2. The quadratic model generated by RSM is used to predict the optimal performance parameters. The results show that different geometrical parameters have to be considered simultaneously in order to improve the performance of ribbed-duct. Eventually, based on this analysis, the optimum levels of design parameters for trapezium rib corresponding to the highest augmentation Nusselt number, the lowest friction factor, and the highest thermo-hydraulic performance have been determined. Finally, the desired correlations for all performance parameters have been developed using RSM. The comparison of predicted values with the experimental values has been carried out, which is found to be in harmony with the experimental values in the uncertainty range of ±5%., which are found to predict the performance parameters with reasonably good accuracy.
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9

Mansour, Rami, and Mårten Olsson. "The Response Surface Single Loop Reliability-Based Design Optimization Method With Reliability Requirement on System Failure." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60505.

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In reliability-based design optimization (RBDO), an optimal design which minimizes an objective function while satisfying a number of probabilistic constraints is found. As opposed to deterministic optimization, statistical uncertainties in design variables and design parameters have to be taken into account in the design process in order to achieve a reliable design. In the most widely used RBDO approaches, the First-Order Reliability Method (FORM) is used in the probability assessment. This involves locating the Most Probable Point (MPP) of failure, or the inverse MPP, either exactly or approximately. If exact methods are used, an optimization problem has to be solved, typically resulting in computationally expensive double loop or decoupled loop RBDO methods. On the other hand, locating the MPP approximately typically results in highly efficient single loop RBDO methods since the optimization problem is not necessary in the probability assessment. However, since all these methods are based on FORM, which in turn is based on a linearization of the deterministic constraints at the MPP, they may suffer inaccuracies associated with neglecting the nonlinearity of deterministic constraints. In a previous paper presented by the authors, the Response Surface Single Loop (RSSL) Reliability-based design optimization method was proposed. The RSSL-method takes into account the non-linearity of the deterministic constraints in the computation of the probability of failure and was therefore shown to have higher accuracy than existing RBDO methods. The RSSL-method was also shown to have high efficiency since it bypasses the concept of an MPP. In RSSL, the deterministic solution is first found by neglecting uncertainties in design variables and parameters. Thereafter quadratic response surface models are fitted to the deterministic constraints around the deterministic solution using a single set of design of experiments. The RBDO problem is thereafter solved in a single loop using a closed-form second order reliability method (SORM) which takes into account all elements of the Hessian of the quadratic constraints. In this paper, the RSSL method is used to solve the more challenging system RBDO problems where all constraints are replaced by one constraint on the system probability of failure. The probabilities of failure for the constraints are assumed independent of each other. In general, system reliability problems may be more challenging to solve since replacing all constraints by one constraint may strongly increase the non-linearity in the optimization problem. The extensively studied reliability-based design for vehicle crash-worthiness, where the provided deterministic constraints are general quadratic models describing the system in the whole region of interest, is used to demonstrate the capabilities of the RSSL method for problems with system reliability constraints.
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10

Azghani, M. R., F. Farahmand, A. Meghdari, F. Hakkak, and M. Parnianpour. "Controllability and Maintenance of Human Trunk Response Surface for Isometric Extension Strength." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24313.

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From an ergonomic point of view, quantitative assessment of the feasibility of the task performance is an intricate process, which combines the multidimensional task demand profile with the individual’s multidimensional performance capacity profile. Trunk muscle strength is affected by the trunk posture but it is not clear how the variability of trunk muscle is affected by the trunk posture or exertion level. A validated triaxial dynamometer, Sharif-LIST, was used for to model the surface response of trunk muscle extension strength variability as a function of trunk posture in the sagittal, coronal and transverse planes in standing position. Fifteen healthy males with no history of low back pain in the previous year participated in this study. A full factorial method was used to design the experiments to fit a second-order model of response surface method (RSM) with block effect (BE). For the first time in the literature, the results of this study indicate that the quadratic RSM model is suitable to represent the trunk extension strength variability in terms of its coefficient of variation (CV) and standard deviation (SD) of maximum trunk torque as a function of trunk posture in coronal and sagittal planes (R2 = 0.6, p<0.5). These results showed that in the positions with higher trunk strength values, the higher standard deviation and lower coefficient of variation were observed which is consistent with previous findings.
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