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It was assumed that strain is uniform on the composite cross section, and that is possible to refer mechanical properties to the dry woven: this approach is accepted by many authors (Chen & Teng 2001) and by some guidelines, such as Italian CNR-DT 200/2004.

Therefore, it was possible to calculate the nominal tensile stress on the textile, defined as the load and cross section area ratio. By coupling the strain measures (obtained from the strain-gauge on the unbonded region) with the load values, and by assuming the linear

Test 1 Test 2 Test 3 Test 1 Test 5

Figure 5. Experimental failure loads per unit width.

Test 1 Test 2 Test 3 Test 1 Test 5

Figure 5. Experimental failure loads per unit width.

elastic behaviour of the composite, it was also possible to evaluate Young's modulus of the reinforcement for each sample through a best fitting (Eq. 1):

where a = nominal tensile stress, P = axial load on the composite strips, bf = single strip width, t = equivalent textile thickness, e = axial strain measured by the strain-gauge and Ef = composite elastic modulus.

Tables 3-4 also report the composite elastic modulus values, Ef , and the nominal tensile stresses at failure, au . The experimental mean elastic moduli result higher than the producer's values (22% for carbon reinforcement and 25% for glass one). The mean maximum stress reached by reinforcement is around 64% of tensile strength for carbon, and 68% for glass.

As the reinforcement axial stiffness per unit width, Eftf, was known for each specimen, failure loads per unit width, P/2bf, were tabulated versus the axial stiffness. Trend lines were fitted, referring to all data or to each set (carbon and glass). The expression adopted for the trend lines is given in Equation 2:

where ci e c2 are regression constants, which values are reported in Table 5. It can be observed that the fitting of all data shows a better correlation than the fitting of each single set.

By assuming the relationship between the failure load and the square root of the axial stiffness per unit width (Eq. 7), it was possible to reduce the number of free parameters in Equation 2, by imposing the exponent value c2 equal to 0.5. Results (carbon data set, glass data set and all data) are given in Table 5, whereas Figures 6-7 compare the trend lines with the experimental data. Regression coefficient for GFRP are slightly higher than CFRP (around 16%) and this

Table 5. Regression constants of load vs axial stiffness (both per unit width) trend lines.

Table 6. Predictions of failure load.

Table 5. Regression constants of load vs axial stiffness (both per unit width) trend lines.

Data set

c1

c2

R2

All data

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