In-service Structural Health Monitoring of a Full-scale Composite Horizontal Tail

In-service structural health monitoring（SHM） technologies are critical for the utilization of composite aircraft structures. We developed a Lamb wave-based in-service SHM technology using built-in piezoelectric actuator/sensor networks to monitor delamination extension in a full-scale composite horizontal tail. The in-service SHM technology combine of damage rapid monitoring（DRM） stage and damage imaging diagnosis（DID） stage allows for real-time monitoring and long term tracking of the structural integrity of composite aircraft structures. DRM stage using spearman rank correlation coeffi cient was introduced to generate a damage index which can be used to monitor the trend of damage extension. The DID stage based on canonical correlation analysis aimed at intuitively highlighting structural damage regions in two-dimensional images. The DRM and DID stages were trialed by an in-service SHM experiment of CFRP T-joint. Finally, the detection capability of the in-service SHM technology was verified in the SHM experiment of a full-scale composite horizontal tail. Experimental results show that the rapid monitoring method effectively monitors the damage occurrence and extension tendency in real time; damage imaging diagnosis results are consistent with those from the failure model of the composite horizontal tail structure.

Evaluation of economic loss from energy-related environmental pollution： a case study of Beijing

With the growth of energy consumption, energy-related environmental pollution has become increasingly serious, which in turn causes enormous economic loss because of public health damage, corrosion of materials, crop yield reduction, and other factors. Evaluating economic loss caused by energy-related environmental pollution can contribute to decision making in energy management. A framework for evaluating economic loss from environmental pollution produced during energy production, transportation, and consumption is proposed in this paper. Regarding SO2, PMlo, and solid waste as the main pollutants, economic losses from health damage, materials corrosion, crop yield reduction, and solid waste pollution are estimated based on multiple concentration-response relationships and dos^response functions. The proposed framework and evaluation methods are applied to Beijing, China. It is evident that total economic loss attributable to energy-related environ-mental pollution fluctuated during 2000-2011 but had a general growth trend, with the highest value reaching 2.3× 108 CNY （China Yuan） in 2006. Economic loss caused by health damage contributes most to the total loss among the four measured damage types. The total economic loss strongly correlates with the amount of energy consumption, especially for oil and electricity. Our evaluation framework and methods can be used widely to measure the potential impact of environmental pollution in the energy lifecycle.