Durability is one of the most important properties of an asphalt mixture. A key factor affecting the durability of asphalt pavements is moisture damage. Moisture damage is generally considered to be the result of two main mechanisms; the loss of adhesion between bitumen and aggregate and the loss of cohesion within the mixture.

In this study, the moisture sensitivity of different kinds of aggregates and bituminous binders is examined by comparing the performance between five empirical test methods for loose mixtures -static immersion test, rolling bottle test (RBT), boiling water test (BWT), total water immersion test and the ultrasonic method -with more fundamental surface energybased test data. The RBT and BWT results showed that limestone aggregates perform better than granite aggregates and that, for unmodified binders, stiffer binders provide better moisture resistance compared with softer binder. Both tests were sensitive to aggregate type, binder type and anti-stripping agent type. Ranking of the mixtures by RBT and BWT was in general agreement with the surface energy-based tests, especially for mixtures that performed worst or best in RBT and BWT. The magnitude of the work of debonding in the presence of water was found to be aggregate type dependent which suggests the physico-chemical properties of aggregates may play a fundamental and more significant role in the generation of moisture damage, than bitumen properties.

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Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Objective functions related to natural frequencies, mode shapes, modal flexibility and modal strain energy have been used, and their performances have been analyzed in varying noise conditions. Three beams were analyzed: two of which were simulated beams with single and multiple damage scenarios and one was an experimental beam. In order to do this, SAP 2000 (v14, Computers and Structures Inc., Berkeley, CA, United States, 2009) is linked with MATLAB (r2015, The MathWorks, Inc., Natick, MA, United States, 2015). The genetic algorithm (GA), an evolutionary algorithm (EA), was used to update the damaged structure for damage detection. Due to the degradation of the performance of objective functions in varying noisy conditions, a modified objective function based on the concept of regularization has been proposed, which can be effectively used in combination with EA. All three beams were used to validate the proposed procedure. It has been found that the modified objective function gives better results even in noisy and actual experimental conditions.

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