Sustained growth of the largest uninhabited alluvial island in the Changjiang Estuary under the drastic reduction of river discharged sediment

The evolution of the Changjiang Delta is obviously affected by current rapidly rising sea level and drastically declining river discharge,and it is also vital for the sustainable development of Shanghai and the Changjiang River Economic Belt,which represent China’s economic development leader and major national strategic area,respectively.In this paper,the growth pattern of Jiuduansha Island,the largest uninhabited alluvial island in the Changjiang Estuary,is studied in terms of the change in elevation,position and area over the past 50 years through using satellite-derived instantaneous shoreline positions and high/low tide exposure areas based on 497 satellite images from 1974 to 2020;and the influencing factors and future development patterns are further discussed by comparison with other alluvial islands or sandbars in the estuary.The results show that Jiuduansha Island has maintained a rapid or even accelerated area growth rate,although the sediment discharge of the Changjiang River has sharply decreased in recent decades.This sustained growth is mainly attributed to the existence of the estuarine turbidity maximum zone,coarsening fluvial sediment,onshore sediment replenishment by tide,cone-like geomorphology of Jiuduansha Island,and siltation promotion effect of vegetation.The growth rate of the low tide exposure area of Jiuduansha Island increased from 1.9 km^(2)a^(−1) in 1974–1990 to 3.0 km^(2)a^(−1) in 1990–2020,and the growth rate of the high tide exposure area reached as high as 3.7 km^(2)a^(−1) in 1994–2020.The implementation of the Deep-Water Channel Project has significantly affected the evolution of Jiuduansha Island,including shifting the heads of Shangsha and Zhongxiasha from severe retreat to rapid accretion,and promoting tidal flat progradation seaward of the Jiangyanansha and Zhongxiasha,but restricting the growth of the low tide exposure area of Jiuduansha Island.

A statistical-based online cross-system fault detection method for building chillers

Practical applications of data-driven fault detection(FD)are limited by their portability.The costs of model training and validation are extremely high when each system requires a model retrained on its own fault and fault-free data.Therefore,this paper proposes a statistical-based online cross-system FD method to address the problem of model portability.The proposed FD model can be cross-utilized between building chillers with various specifications while it only needs to update the original fault detection model by the normal operation data of the new chiller system,thus saving huge fault experimental costs for the fault detection of new chiller.First,a theoretical basis for the proposed cross-system fault detection method is presented.Then,experiments were conducted on three building chillers with different specifications.Both fault and fault-free data were collected from the three chillers.The development and validation of the proposed cross-system fault detection method are then conducted.Results show that the cross-system fault detection models perform well when used with different chillers.For instance,when the fault detection model of system#1 was cross-utilized to system#2,the detection accuracies of refrigerant leakage,refrigerant overcharge,and reduced evaporator water flow were 99.73%,90.17%,and 96.94%,respectively.Compared with original models,the detection accuracies were improved by 33.78%,84.07%,and 65.56%,respectively.Therefore,the proposed cross-system fault detection method has potential for online application to practical engineering FD.