MATERIALS ENGINEERING CONCEPTS - Materials for Civil and Construction Engineers - page 27

difficult to deal with than technical design problems. Thus, engineers should
understand that there are many factors beyond the technical needs that must
be considered when selecting materials and designing public projects.

1.6 Material Variability

It is essential to understand that engineering materials are inherently vari-
able. For example, steel properties vary depending on chemical composition
and method of manufacture. Concrete properties change depending on type
and amount of cement, type of aggregate, air content, slump, method of cur-
ing, etc. The properties of asphalt concrete vary depending on the binder
amount and type, aggregate properties and gradation, amount of compaction,
and age. Wood properties vary depending on the tree species, method of cut,
and moisture content. Some materials are more homogeneous than others, de-
pending on the nature of the material and the method of manufacturing. For
example, the variability of the yield strength of one type of steel is less than
the variability of the compressive strength of one batch of concrete. There-
fore, variability is an important parameter in defining the quality of civil
engineering materials.
When materials from a particular lot are tested, the observed variability is
the cumulative effect of three types of variance: the inherent variability of the
material, variance caused by the sampling method, and variance associated
with the way the tests are conducted. Just as materials have an inherent vari-
ability, sampling procedures and test methods can produce variable results.
Frequently, statisticians call variance associated with sampling and testing
error. However, this does not imply the sampling or testing was performed in-
correctly. When an incorrect procedure is identified, it is called a blunder. The
goal of a sampling and testing program is to minimize sampling and testing
variance so the true statistical features of the material can be identified.
The concepts of precision and accuracy are fundamental to the under-
standing of variability. Precision refers to the variability of repeat measure-
ments under carefully controlled conditions. Accuracy is the conformity of
results to the true value or the absence of bias. Bias is a tendency of an esti-
mate to deviate in one direction from the true value. In other words, bias is
a systematic error between a test value and the true value. A simple analo-
gy to the relationship between precision and accuracy is the target shown in
Figure 1.18. When all shots are concentrated at one location away from the cen-
ter, that indicates good precision and poor accuracy (biased) [Figure 1.18(a)].
When shots are scattered around the center, that indicates poor precision
and good accuracy [Figure 1.18(b)]. Finally, good precision and good accuracy
are obtained if all shots are concentrated close to the center [Figure 1.18(c)]
(Burati and Hughes 1990). Many standardized test methods, such as those
of the American Society for Testing and Materials (ASTM) and the Ameri-
can Association of State Highway and Transportation Officials (AASHTO),