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In addition, the response surface provided by the kinetic modeling was also analyzed.
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Construction of the robust domain from response-surfaces provided tolerance windows for the factors affecting the effectiveness of the method.
Response surface plots provided experimental data-based understanding of MJR parameters' effect, thus NP quality.
The response surface methodology provided important information on interactions between the factors and is recommended for similar adsorption systems.
The response surface equations provided relative significance of the variables on the membrane performances for the NF 90 membrane and the more permeable NF 270 membrane in terms of effluent quality, percent rejection, and membrane resistance.
In addition, the developed response surface models provided easy estimation of impact-induced responses of an UHPFRC-strengthened column, which have potential use as the surrogates of time-consuming FE simulations to efficiently examine the reliability and optimization of bridge columns under impact loadings.
The response surface methodology provides a relationship among the parameters which can be utilized in finding optimal values.
The response surface plots provide a method to visualize the relationship between responses and experimental levels of each variables and the type of interactions between two test variables [[22]].
Nevertheless, such a modelling approach using response surface methodology provides a rapid answer to heat resistance evaluation of a food-borne virus as a function of specific physical and chemical parameters of specific food products.
The effective application of a new analytical moment-based uncertainty evaluation technique proposed in combination with response surface methodology provides an accurate and numerically efficient evaluation of the fuel cell performance.
Building energy models (BEM) of single family homes are evaluated using a full factorial experimental design to create a response surface which provides a continuous function to evaluate the impact of four design variables on long-term thermal comfort indices, including Average Percent of People Dissatisfied (Average PPD), and Percentage Outside Thermal Comfort Zone (POS).
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