{"title":"基于响应面法的d -最优混合设计优化钢结构膨胀型防火涂料配方中的阻燃剂","authors":"Jian Hu","doi":"10.12783/dteees/eece2019/31567","DOIUrl":null,"url":null,"abstract":"Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Many experiments in research and development in the paint preparation involve mixture components. These are experiments with mixtures in which the experimental factors are the components of a mixture and the response variable depends on the relative proportion of each components, but not on the absolute amount of the mixture. Thus the mixture components cannot be varied independently. Optimizing the formulations for a preparation of intumescent fire-resistant coating requires the fire resistant effectiveness of several fire retardants combinations to be determined. We discuss the design and analysis of these types of experiments, presents a D-optimal design methodology for computer aided experimental design for fire retardant coating formulations involve mixture components, exemplifies the benefits of using design of experiments(DOE) together with statistical software package to facilitate the formulating of recipe for structural steelworks. Goal of this paper is to encourage greater utilization of information technology in paint preparation research and development. Introduction The use of fire-resistant coatings is one of the most efficient ways to protect materials against fire[1]. Intumescent fire-resistant systems are chemical compounds which, when heated, melt, bubble and form a foamed char which acts as insulation for underlying steel structures[2]. Intumescent fire-retardant coatings composition usually contain three fundamental active ingredients: a carbon source (such as pentaerythritol-PER), a blowing agent (most often melamine-MEL), an acid source (generally ammonium polyphosphate-APP), and they are linked together by a binder such as polymer materials. Optimizing the formulations for a preparation of intumescent fire-resistant coating(IFRC) requires the fire resistant usefulness of several fire retardants collaboration to be confirmed. Three fire retardants were tested in this study: ammonium polyphosphate, pentaerythritol and melamine. Their fire resistant effects were evaluated using the fire-resistance tests of the International Organization for Standardization (ISO) [3]. From a limited number of experiments, a D-optimal mixture design was used to give a maximum of information. The main objective of the research presented here was to carry out multivariate analysis upon data from the experiment design based on Design Expert® software. We analyze our investigation results with the help of the MODDE software and to formulate coatings convincing requirements of the ISO 834-1:1999. Multivariate analysis is a statistical tool that can be used to determine the contributing effect(s) of and identify relationships between independent variables and dependant variables in a multivariable system. A dependant variable is an uncontrolled variable which is being predicted or explained by one or more independent variables. An independent variable is a quantity which can be controlled (altered) and used as a predicting or explanatory variable for a dependant variable. 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Many experiments in research and development in the paint preparation involve mixture components. These are experiments with mixtures in which the experimental factors are the components of a mixture and the response variable depends on the relative proportion of each components, but not on the absolute amount of the mixture. Thus the mixture components cannot be varied independently. Optimizing the formulations for a preparation of intumescent fire-resistant coating requires the fire resistant effectiveness of several fire retardants combinations to be determined. We discuss the design and analysis of these types of experiments, presents a D-optimal design methodology for computer aided experimental design for fire retardant coating formulations involve mixture components, exemplifies the benefits of using design of experiments(DOE) together with statistical software package to facilitate the formulating of recipe for structural steelworks. Goal of this paper is to encourage greater utilization of information technology in paint preparation research and development. Introduction The use of fire-resistant coatings is one of the most efficient ways to protect materials against fire[1]. Intumescent fire-resistant systems are chemical compounds which, when heated, melt, bubble and form a foamed char which acts as insulation for underlying steel structures[2]. Intumescent fire-retardant coatings composition usually contain three fundamental active ingredients: a carbon source (such as pentaerythritol-PER), a blowing agent (most often melamine-MEL), an acid source (generally ammonium polyphosphate-APP), and they are linked together by a binder such as polymer materials. Optimizing the formulations for a preparation of intumescent fire-resistant coating(IFRC) requires the fire resistant usefulness of several fire retardants collaboration to be confirmed. Three fire retardants were tested in this study: ammonium polyphosphate, pentaerythritol and melamine. Their fire resistant effects were evaluated using the fire-resistance tests of the International Organization for Standardization (ISO) [3]. From a limited number of experiments, a D-optimal mixture design was used to give a maximum of information. The main objective of the research presented here was to carry out multivariate analysis upon data from the experiment design based on Design Expert® software. We analyze our investigation results with the help of the MODDE software and to formulate coatings convincing requirements of the ISO 834-1:1999. Multivariate analysis is a statistical tool that can be used to determine the contributing effect(s) of and identify relationships between independent variables and dependant variables in a multivariable system. A dependant variable is an uncontrolled variable which is being predicted or explained by one or more independent variables. 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Optimization of Fire Retardants in a Formulations of Intumescent Fire Retardant Coatings for Steel Structure via a D-optimal Mixture Design Based on Response Surface Methodology
Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Many experiments in research and development in the paint preparation involve mixture components. These are experiments with mixtures in which the experimental factors are the components of a mixture and the response variable depends on the relative proportion of each components, but not on the absolute amount of the mixture. Thus the mixture components cannot be varied independently. Optimizing the formulations for a preparation of intumescent fire-resistant coating requires the fire resistant effectiveness of several fire retardants combinations to be determined. We discuss the design and analysis of these types of experiments, presents a D-optimal design methodology for computer aided experimental design for fire retardant coating formulations involve mixture components, exemplifies the benefits of using design of experiments(DOE) together with statistical software package to facilitate the formulating of recipe for structural steelworks. Goal of this paper is to encourage greater utilization of information technology in paint preparation research and development. Introduction The use of fire-resistant coatings is one of the most efficient ways to protect materials against fire[1]. Intumescent fire-resistant systems are chemical compounds which, when heated, melt, bubble and form a foamed char which acts as insulation for underlying steel structures[2]. Intumescent fire-retardant coatings composition usually contain three fundamental active ingredients: a carbon source (such as pentaerythritol-PER), a blowing agent (most often melamine-MEL), an acid source (generally ammonium polyphosphate-APP), and they are linked together by a binder such as polymer materials. Optimizing the formulations for a preparation of intumescent fire-resistant coating(IFRC) requires the fire resistant usefulness of several fire retardants collaboration to be confirmed. Three fire retardants were tested in this study: ammonium polyphosphate, pentaerythritol and melamine. Their fire resistant effects were evaluated using the fire-resistance tests of the International Organization for Standardization (ISO) [3]. From a limited number of experiments, a D-optimal mixture design was used to give a maximum of information. The main objective of the research presented here was to carry out multivariate analysis upon data from the experiment design based on Design Expert® software. We analyze our investigation results with the help of the MODDE software and to formulate coatings convincing requirements of the ISO 834-1:1999. Multivariate analysis is a statistical tool that can be used to determine the contributing effect(s) of and identify relationships between independent variables and dependant variables in a multivariable system. A dependant variable is an uncontrolled variable which is being predicted or explained by one or more independent variables. An independent variable is a quantity which can be controlled (altered) and used as a predicting or explanatory variable for a dependant variable. Independent