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From page 76... ... 76 Introduction The application of statistically based experimental design enables investigating a test space containing a large number of possible combinations of factors with a relatively small number of tests. The goal of this methodology is to conduct an experiment to determine the combination of the available and appropriate raw materials that will best produce the desired performance in a concrete mixture. Read the entire page →
From page 77... ... 77 designs are created so that each factor level is balanced with every other factor level such that an independent estimate of each factor effect is possible. The method allows for relatively simple statistical analysis and reasonably good estimates of the factor effects because all mixtures are used in the estimation of each factor effect. Read the entire page →
From page 78... ... 78 c. Note: If two levels are examined in an amount factor, a trend can be established to describe the influence of the factor. Read the entire page →
From page 79... ... 7. Amount Constants (information from Worksheet S1.1) Read the entire page →
From page 80... ... 80 conducted in Step 6. Also, the electrical conductivity (AASHTO T 277/ASTM C 1202) Read the entire page →
From page 81... ... selected to produce the desired slump, and the w/cm is chosen based on a target strength or durability requirements. In combination, the water content and w/cm determine the cementitious materials content. Read the entire page →
From page 82... ... 82 The definitions of low, medium, and high were determined with Worksheet S3.2, which is completed in Table S3.5. (An example of a compound factor based on two type levels and two amount levels is given in Table S3.6.) Read the entire page →
From page 83... ... 83 Worksheets for Step 3 Factor Level 1 Level 2 Level 3 Type Factors Source Factors Amount Factors Type Constants Source Constants Amount Constants Worksheet S3.1. Factors and levels to test. Read the entire page →
From page 84... ... 84 Factor 1, Factor 2 Type Amount Type 1, Low Level Type 1, Medium Level Type 1, High Level Type 2, Low Level Type 2, Medium Level Type 2, High Level Type 3, Low Level Type 3, Medium Level Type 3, High Level Worksheet S3.2. Compound factor table. Read the entire page →
From page 85... ... 85 Mixture Factor 1 (3-Level) Factor 2 (2-Level) Read the entire page →
From page 86... ... 86 Factor Level 1 Level 2 Level 3 Type Factors Source Factors Amount Factors Type Constants Source Constants Amount Constants Table S3.4. Completed Worksheet S3.1, factors, levels, and constants to test for hypothetical case study. Read the entire page →
From page 87... ... 87 Factor 1, Factor 2 Type of SCM Amount of SCM Type 1, Low Level Type 1, Medium Level Type 1, High Level Type 2, Low Level Type 2, Medium Level Type 2, High Level Type 3, Low Level Type 3, Medium Level Type 3, High Level Factor 1, Factor 2 Type of SCM Amount of SCM Type 1, Low Level Type 1, Medium Level Type 1, High Level Type 2, Low Level Type 2, Medium Level Type 2, High Level Type 3, Low Level Type 3, Medium Level Type 3, High Level Note: Type 3 and medium are ignored because each factor only has two levels. Table S3.5. Read the entire page →
From page 88... ... 88 Mixture First SCM Type First SCM Amount Amount of Silica Fume w/cm 1 Fly Ash C Low (15%) 0% 0.45 2 Fly Ash C Medium (25%) Read the entire page →
From page 89... ... 89 An 8-mixture design matrix for one three-level factor and one to four two-level factors. Mixture Factor 1 (3-Level) Read the entire page →
From page 90... ... 90 A 12-mixture design matrix for 8 to 11 two-level factors. Mixture Factor 1 (2-Level) Read the entire page →
From page 91... ... A 16-mixture design matrix for 1 three-level factor and 5 to 12 two-level factors. Mixture Factor 1 (3-Level) Read the entire page →
From page 92... ... 92 A 16-mixture design matrix for two three-level factors and three to nine two-level factors. Mixture Factor 1 (3-Level) Read the entire page →
From page 93... ... 93 A 16-mixture design matrix for four three-level factors and one to three two-level factors. Mixture Factor 1 (3-Level) Read the entire page →
From page 94... ... 94 An 18-mixture design matrix for five three-level factors and one to three two-level factors. Mixture Factor 1 (3-Level) Read the entire page →
From page 95... ... 95 An 18-mixture design matrix for six three-level factors and one to two two-level factors. Mixture Factor 1 (3-Level) Read the entire page →

From page 76...

... 76 Introduction The application of statistically based experimental design enables investigating a test space containing a large number of possible combinations of factors with a relatively small number of tests. The goal of this methodology is to conduct an experiment to determine the combination of the available and appropriate raw materials that will best produce the desired performance in a concrete mixture.