Fuqing Yuan

The study on heavy metal distribution in the sediment of middle tidal flat in Yangtze Estuary, China

The heavy metal distribution in the tidal flat has great effect on the estuary environment. The study aims to find the heavy metal distribution mechanism in the sediment of a middle tidal flat in Yangtze Estuary, China. The effects of grain size, the redox cycle of Fe, Mn during early diagenesis and post-depositional migration, and humic acid on the distribution of heavy metals have been studied extensively. Surface and core sediments from middle tidal flat of eastern Chongming Island were collected and analyzed the content of element Al, Cu, Cr, Fe, Mn, Pb, Zn, Zr and humic acid. The results showed that grain size, the geochemistry of Fe, Mn during early diagenesis and post-depositional migration, and humic acid had significant effect on the distribution of heavy metals. Copper, Fe, Mn, Pb and Zn mainly accumulated in the fine particles. Copper, Pb and Zn had similar seasonal variation in surface sediment and similar vertical distribution in the four seasons with Al, Fe, Mn and humic acid. Copper, Pb and Zn remobilized after deposition together with redox-sensitive elements Fe and Mn and accumulated in the redox boundary. Peak value of heavy metals, Fe, Mn and humic acid was observed in the four seasons at different depths at the redox boundary. Zirconium and Cr had opposite distribution than the other heavy metals.

Reliability modeling of successive release of software using NHPP

This paper presents an effective reliability model for multi-release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jørgensen [1]. Most of OSS reliability models do not consider the unique characteristic of OSS in the model. This model, combine bugs removed from pre-commit test and parallel debugging test phases. Furthermore, the proposed model is based on the assumptions that the total number of fault removal of the new release depends on the reported faults from the previous release and on the faults generated due to adding some new adds-on to the existing software system. The parameters of model have been estimated using three releases of the Apache project. In addition, three models in the literature are selected to compare with the proposed model. Comparison indicates that the proposed model is a suitable reliability model that fits the data across all the releases of the Apache project.

Maintainability analysis of equipment using point process models

The maintenance cost can be reduced significantly by applying the maintainability principle in the design and operation phase. An effective maintainability prediction can help the designer to improve performance and safety of equipment. The analysis of historical repair by an affective statistical approach provides essential information for decision-making regarding the planning of operation and maintenance activities of the plant. However, the literature on field repair data is quite scarce and they are not detailed. This paper will try to provide step by step guideline for field repair data using point process models by a case study.

Performance evaluation for maximum likelihood and moment parameter estimation methods on classical two Weibull distribution

The two-parameter Weibull distribution is the most widely used distribution in reliability engineering. Parameter estimation is a key issue to apply the Weibull to practical engineering. This paper aims to compare the performance of the maximum parameter estimation method (MLE) and the moment parameter method. It firstly investigates some mathematical properties such as solution uniqueness, estimators equivariance and the confidence interval, that are important to practice. Later on their performances have been evaluated by using simulation. In the simulation, data sets ranged from extreme small to large have been considered. Weibull distribution with increasing, constant and deceasing failure rate have been chosen in the simulation to ensure the simulations results concrete.

Data-driven model development using Support Vector Machine for railway Overhead Contact Wire maintenance

The fault on Overhead Contact Wire (OCW) causes traffic disruptions in railway transportation. The inspection and maintenance on OCW is inconvenient as it locates highly above the ground. Condition monitoring system has been installed to monitor the status of the OCW automatically. Huge amount of data have been collected by these systems. However, a general problem of these systems is the analysis on these data is weak. The condition monitoring system has been devalued due to this. This paper aims to develop data driven Support Vector Machine (SVM) model to extract useful information from the huge amount of data. This data driven model evaluate the OCW status without requiring understanding the physical mechanism of the fault. Maintenance points are suggested based on the output of the SVM model.

The investigation of physical explanation for proportional hazard model (PHM) for typical failure mechanisms

Proportional hazard model (PHM) is a common reliability model in reliability engineering. This model considers the operating condition as covariates. The operating condition is assumed to affect the failure rate proportionally. In the state-of-art applications, this PHM is used as a data-driven model. Nevertheless, some literature argue the PHM has the advantage of physical explanation for its covariates. This paper chooses important failure mechanisms from engineering system to derive the failure model from the physical perspective. Later on, the model is extended to statistical model from the statistical point of view, with the aim to explain the PHM model. For these specific failure mechanisms, the paper investigates the accuracy of the PHM model compared with the physical model. A numerical example is presented to demonstrate the difference between the physical model and the classical PHM model.

The effect of drinking water quality on the health and longevity of people-A case study in Mayang, Hunan province, China

Drinking water is an important source for trace elements intake into human body. Thus, the drinking water quality has a great impact on peoples health and longevity. This study aims to study the relationship between drinking water quality and human health and longevity. A longevity county Mayang in Hunan province, China was chosen as the study area. The drinking water and hair of local centenarians were collected and analyzed the chemical composition. The drinking water is weak alkaline and rich in the essential trace elements. The daily intakes of Ca, Cu, Fe, Se, Sr from drinking water for residents in Mayang were much higher than the national average daily intake from beverage and water. There was a positive correlation between Ni and Pb in drinking water and Ni and Pb in hair. There were significant correlations between Cu, K in drinking water and Ba, Ca, Mg, Sr in the hair at the 0.01 level. The concentrations of Mg, Sr, Se in drinking water showed extremely significant positive relation with two centenarian index 100/80% and 100/90% correlation. Essential trace elements in drinking water can be an important factor for local health and longevity.

Modelling the transport of oil after a proposed oil spill accident in Barents Sea and its environmental impact on Alke species

Accidental oil spills can have significant effect on the coastal and marine environment. As the oil extraction and exploration activities increase in the Barents Sea, it is of increasingly importance to investigate the potential oil spill incidents associated with these activities. In this study, the transport and fate of oil after a proposed oil spill incident in Barents Sea was modelled by oil spill contingency and response model OSCAR. The possibility that the spilled oil reach the open sea and the strand area was calculated respectively. The influence area of the incident was calculated by combining the results from 200 simulations. The possibility that the spilled oil reach Alke species, a vulnerable species and on the National Red List of birds in Barents Sea, was analyzed by combining oil spill modelling results and the Alke species distribution data. The results showed that oil is dominated with a probability of 70-100% in the open sea to reach an area in a radius of 20km from the release location after 14 days of release. The probability reduces with the increasing distances from the release location. It is higher possibility that the spilled oil will reach the Alke species in the strand area than in the open sea in the summer. The total influence area of the release is 11 429 km2 for the surface water and 1528 km2 for the coastal area.

Safety measurement for the road transport in northern Norway in wintertime

Northern Norway has adverse geographical and weather condition in wintertime for road transport. Accidents occurs frequently in some areas and the safety of the transport in these areas has been a big concern. This paper analyze the reasons of the accidents and explore the economic and effective method to reduce the accidents. Considering the existing installed system preventing the accidents and the specialty of the geographical condition, this paper suggests developing highly integrated and automatic intelligent system to monitor the road surface and the driver behavior.

The Possibilities And Challenges Of Using Industrial Rest Products On Mine Waste Management In The Arctic

Acid Rock Drainage (ARD) generated from oxidation of sulphide-bearing mine waste is one of the main pollution problems associated with mining activities. Dry cover and water cover are normally used methods to prevent the formation of ARD. However, in the Arctic region, the harsh cold climate, the vulnerability of ecosystems and the drastic climate change make the waste management methods different from other non-Arctic regions. This paper reviewed several successful case studies of dry cover and water cover applications with industrial rest products and further discussed the possibilities and challenges of using industrial rest products to manage mine waste in the Arctic region.