In recent years, bridge health monitoring system has been widely used to deal with massive data produced with the continuous growth of monitoring time. However, how to effectively use these data to comprehensively analyze the state of a bridge and provide early warning of bridge structure changes is an important topic in bridge engineering research. This paper utilizes two algorithms to deal with the massive data, namely Kohonen neural network and long short-term memory (LSTM) neural network. The main contribution of this study is using the two algorithms for health state evaluation of bridges. The Kohonen clustering method is shown to be effective for getting classification pattern in normal operating condition and is straightforward for outliers detection. In addition, the LSTM prediction method has an excellent prediction capability which can be used to predict the future deflection values with good accuracy and mean square error. The predicted deflections agree with the true deflections, which indicate that the LSTM method can be utilized to obtain the deflection value of structure. What's more, we can observe the changing trend of bridge structure by comparing the predicted value with its limit value under normal operation.

Inspired by the sophisticated design of biological systems, interest in soft intelligent actuators has increased significantly in recent years, providing attractive strategies for the design of elaborate soft mechanical systems. For the construction of those soft actuators, carbon nanomaterials were extensively and successfully explored for the properties of highly conductive, electrothermal, and photothermal conversion. This review aims to trace the recent achievements for the material and structural design as well as the general mechanisms of the soft actuators, paying particular attention to the contribution of carbon nanomaterials resulted from their diversified interplaying properties, which realized the flexible and dexterous deformation responding to various environmental stimuli, including light, electricity and humidity. The properties and mechanisms of soft actuators are summarized and the potential for future applications and research are presented.

In this review, the latest progress of intelligent materials incorporated with acoustic metamaterials is summarized to provide an impetus for this highly interdisciplinary advancement towards low-frequency sound absorption.

The hollow slab bridge is a widely used bridge type for urban bridges. The slabs are prefabricated in a factory and are assembled on site, and then the hinge joints are poured on site. Shallow hinge joints have been used in most existing hollow slab bridges, which commonly bring inadequate connection to the adjacent slabs and probably result in bridge damage. Traditional detection and test methods for hinge joints interrupt traffic, which is inconvenient for local commuters. In the present study, a light-load field test method for hinge joints was proposed. The principles and procedures of the light-load test were concluded and provided based on the test results of 96 spans. The theoretical and measured lateral load distribution ratios were calculated and compared based on hinge joint plate theory. The damage evaluation method and damage classification for hinge joints were defined based on the test results of 1100 hinge joints. Furthermore, the accuracy of the proposed method was verified by a destructive experiment. The research results indicate that the light-load field test and the damage evaluation method for hinge joints are indeed convenient, reliable, and economical, and deserve practical spread and repetition in this area.