Problem 4: Beam Failure Modeling Learning objective: Create and manipulate 1D Arrays using a function in MATLAB. Engineering focus: Material Properties (civil, mechanical) Lead Team Member: Background: The Modulus of Rupture (MOR) is a measure of the pressure within a specimen at failure (often referred to as bending strength). This is usually determined using a 3-point test shown in the image. Wood samples are not homogeneous due to growth rings and specimen preparation. Two groups have completed MOR tests on 5 samples as shown in Table 1 below. Previous testing provides a typical average and standard deviation for Poplar Hardwood beams. 3-point Flexure test Force Loading pin Table 1. MOR (units: psi, pounds per square inch) Hardwood: Poplar Test 1 Test 2 Statistics 13,802 14,121 16,484 15,287 Average 11,904 12,206 13,952 10,851 7,847 Standard Deviation 10,635 17,936 3,216 Specimen Supporting pins www.substech.com = 5 a) Create a script (A3_P2_MOR.m) that completes the following: i) Create arrays for Test 1 (test1 MOR) and Test 2 (test2MOR) data. Concatenate Test 2 data to the end of Test 1 in a row array. Create and assign the average (averageMOR) and standard deviation (stdeXMOR) values above. Create the following logical arrays (1) bighMOR - which identifies the totalTestMOR, entries with MOR values greater than 1 standard deviation above the average. (2) lowMOR - which identifies the totalTestMOR entries with MOR values less than 1 standard deviation below the average. (3) normalMOR - which identifies the totalTestMOR entries with MOR values within 1 standard deviation above and below the average. Create the arrays for high Values, lowValues & pormalValues, using the logical arrays for indexing. vi) Use the sum command to calculate the percentage (normalpercent) of normal MoRvalues relative to the totalTestMOR values. Display as a percent. > Cut & Paste your A3_P2_MOR.m code below: Cut & Paste your Command Window output here