بهینه سازی نسبت های مخلوط با استفاده از طراحی آزمایش آماری با روش سطح پاسخ
خلاصه
1. مقدمه
2. مبانی نظری RSM برای مواد بر پایه سیمان
2.1 روش کلی با استفاده از RSM در بهینه سازی طراحی آزمایشی
2.2 طراحی مدل مرتبه اول
2.3 طرح های مدل مرتبه دوم
2.4 ارزیابی و اعتبارسنجی مدل برازش
3. بررسی ادبیات RSM در بهینه سازی طراحی مخلوط
3.1 طرح های بهینه سازی در کاربردهای مواد مبتنی بر سیمان
3.2 طرح های بهینه سازی برای کاربردهای بتن پایدار
4. خلاصه و بحث
4.1 انتخاب استراتژی طراحی
4.2 انتخاب عوامل و پاسخ ها
4.3 انتخاب دامنه تجربی
4.4 چالش های فعلی برای کاربردهای بتن پایدار
5. نتیجه گیری و آینده نگر
تقدیر و تشکر
پیوست اول.
ضمیمه B.
منابع
Abstract
1. Introduction
2. Theoretical basis of RSM for cement-based materials
2.1 General procedure using RSM in experimental design optimization
2.2 Designs of the first-order model
2.3 Designs of the second-order model
2.4 Evaluation and validation of the fitting model
3. Literature survey of RSM in mixture design optimization
3.1. Optimization designs in cement-based materials applications
3.2. Optimization designs for sustainable concrete applications
4. Summary and discussion
4.1 Selection of design strategy
4.2 Selection of factors and responses
4.3 Selection of experimental domain
4.4 Current challenges for the applications of sustainable concrete
5. Conclusions and Prospective
Acknowledgements
Appendix A.
Appendix B.
References
Abstract
A comprehensive review of the statistical experimental optimization problem concerning the mixture design of various cement-based materials is presented herein. This review summarizes and discusses over 80 applications of optimum design regarding the basic test information under response surface method (RSM), including influence factor and corresponding response, statistical method, and coefficient of determination. The statistical experimental design reported in previous studies has shown that RSM is a sequential procedure to provide a suitable approximation for the mixture optimization. Then, linear, quadratic and interactive relationships of the statistical model can be evaluated available. Especially, the multi-objective optimization issues with multiple or competing performance requirements for various cement-based materials have also been reported, by considering fluidity, strength development, environmental impact, cost and durability. Overall, the results from existing publications have demonstrated that statistical inference and analysis of variance (ANOVA) are suitable for mix proportion design and process optimization of cement-based materials. The W/B ratio and mixture components are the prevalent factors in experimental design optimization, and then the fluidity and strength as the most popularly used response. Thus, theoretical optimum mixture proportioning can be used to predict valuable fresh and hardened properties. Finally, a critical discussion of the selection of design strategy, independent factors and their responses, and the experimental region involved in statistical experimental design, is provided. Based on this review, we conclude that the multi-objective optimization approaches need a further systematic study, and further studies of sustainable concrete optimization are needed by comparing the different chemical composition and particle characteristics.
1. Introduction
The cement-based materials are prepared by using various types and quantities of individual constituents. These mixture proportions play an important role in fresh- and hardened-state performance, such as fluidity, rheological properties, strength development and durability. Therefore, many research studies have been dedicated to experimental optimization of cement and concrete mixtures.