Sentence examples for error in strength from inspiring English sources

Table 7 also presents the percentile error in strength predictions as given by Eq. 4: % {text{ Error}} = frac{{F_{th} - F_{u} }}{{F_{u} }}; times ;100 (4).

Open image in new window Fig. 14 Average of absolute percentile error in strength predictions of FRP-confined heat-damaged columns.

It is shown to be consistent with the behavior from the tests and finite element analyses with errors in strength of up to 13% for the range of gusset configurations considered.

For the aspect ratio of H/D = 0.5 recommended by ISRM and ASTM, the error in tensile strength may be up to 15% for both typical rocks and asphalts, whereas for longer cylinders with H/D up to 2 the error ranges from 15% for highly compressible materials, and to 60% for nearly incompressible materials.

The estimation error in tensile strength by Yamashita et al. (2009) was 0.8 MPa at this site.

Based on average values of the absolute percentile error in model strength predictions of the FRP wrapped heat-damaged specimens presented in Fig. 14, it seems that the best performing models are those proposed by Ozbakkaloglu and Lim (2013), ACI 440.2R (2008) and Lam and Teng (2003).

Using the new inverse analysis approach on the S355 bulk material resulted in an error within 3% of the experimental yield strength and strain hardening exponent data, which compares to an approximate 9% error in the yield strength and an 8% error in the strain hardening exponent using a more conventional approach to the inverse analysis method.

The standard error in estimating compressive strength from the UPV varies from 1.6MPa to 2.34 MPa.

Less than 15% error in the line strength is observed between the measured data and HITRAN database.

While it is known that all three of these methods (two correction formulas and the cohort method) contain sources of error, a strength in using multiple methods as we have done here is to produce a range of estimates that can achieve more plausible results.

It can be seen that with 1 day electrical conductivity measurement, the error in estimating 50 days strength was <31%% and the error in estimating 15 days was <18%%.