Decision-making under risk assessment involves dealing with the matter of uncertainty, especially in projects such as tunnel construction. Risk control should include not only measures to reduce the possible consequence of incident, but also exploration measures (information collecting measures) to reduce the uncertainty of the incident. The classical risk assessment model in engineering is $R=P\times C$ which only takes account of the assessment and decision-making of possible consequences. It cannot provide theoretical guidance for taking exploration measures. The paper presents an advanced methodology to assess the effectiveness of exploration measures in decision-making. The methodology classifies risk into two attributes: hazard (expected value) and uncertainty (entropy). On this basis, a generalized model of decision-making under risk assessment is proposed. This model extends the use of the classical assessment model to a more general case. The reason for taking exploration measures and assessment of such measures’ effectiveness could be explained well by this developed model. This model can also serve as a descriptive model for many risk problems and provide a decision-making basis for a variety of risk types. Moreover, the assessment process and calculation method are applied with some case studies.

Reinforced concrete structural elements, as an important component of buildings and structures, require inspection for the purposes of crack detection which is an important part of structural health monitoring. Now existing crack detection methods usually use a single technology and can only detect internal or external cracks. In this paper, the authors propose a new sensing system combining BOFDA (Brillouin optical frequency‐domain analysis) and FBG (fiber Bragg grating) technology, which are used to detect internal and surface cracks and their development in reinforced concrete structures, and an attempt is made to estimate the width of surface cracks. In these experiments, a special reinforced concrete beam structure was designed by the author for crack detection under load. Four continuous distributed optical fibers are fixed on the steel skeleton, which is located within the reinforced concrete beam. Three FBG sensors are fixed on the lower surface of the beam, near its centre. By analysing the sensor data, it can be found that the BOFDA‐distributed fiber can be used to detect internal cracking before surface cracking, and the difference between scans can be used to judge the time of onset of internal cracking, but the relative error in position is about 5%, while the FBG sensor can detect the cracking time of microcracks on the lower surface in near‐real‐time and can be used to calculate the crack width. Through the experiment, it is found that if the combination of BOFDA and FBG technology is adopted, we can initially use the strain data obtained by multiple groups of BOFDA monitoring to predict the general location of the internal cracks, then to monitor the exact location of the surface cracks by FBG in the medium term, and to estimate the width of the final expansion of the cracks finally.