Beneficial use of dredged sediments as a resource for mine reclamation: A case study of Lake Dianchi's management in China.

Dredging is one of the most effective methods for inhibiting the endogenous contamination of natural lakes. However, both the amount and the scope of dredging will be restricted if the disposal of the dredged sediment incurs considerable environmental and economic costs. The use of dredged sediments as a post-mining soil amendment for mine reclamation benefits both sustainable dredging and ecological restoration. This study incorporates a field planting experiment with a life cycle assessment to confirm the practical effectiveness of sediment disposal via mine reclamation, as well as its environmental and economic superiority over other alternative scenarios. The results show that the sediment offered plentiful organic matter and nitrogen for mine substrate, stimulating plant growth and increasing photosynthetic carbon fixation density, followed by enhanced plant root absorption and an improved soil immobilization effect on heavy metals. A 2:1 ratio of mine substrate to sediment is recommended to significantly promote the yield of ryegrass while reducing levels of groundwater pollution and soil contaminant accumulation. Due to the significant reduction in electricity and fuel, mine reclamation had minimal environmental impacts on global warming (2.63 × 10-2 kg CO2 eq./kg DS), fossil depletion (6.81 × 10-3 kg oil eq./DS), human toxicity (2.29 × 10-5 kg 1,4-DB eq/kg DS), photochemical oxidant formation (7.62 × 10-5 kg NOx eq./kg DS), and terrestrial acidification (6.69 × 10-5 kg SO2 eq./kg DS). Mine reclamation also had a lower cost (CNY 0.260/ kg DS) than cement production (CNY 0.965/kg DS) and unfired brick production (CNY 0.268/kg DS). The use of freshwater for irrigation and electricity for dehydration were the key factors in mine reclamation. Through this comprehensive evaluation, the disposal of dredged sediment for mine reclamation was verified to be both environmentally and economically feasible.

A velocity-guided Harris hawks optimizer for function optimization and fault diagnosis of wind turbine.

Harris hawks optimizer (HHO) is a relatively novel meta-heuristic approach that mimics the behavior of Harris hawk over the process of predating the rabbits. The simplicity and easy implementation of HHO have attracted extensive attention of many researchers. However, owing to its capability to balance between exploration and exploitation is weak, HHO suffers from low precision and premature convergence. To tackle these disadvantages, an improved HHO called VGHHO is proposed by embedding three modifications. Firstly, a novel modified position search equation in exploitation phase is designed by introducing velocity operator and inertia weight to guide the search process. Then, a nonlinear escaping energy parameter E based on cosine function is presented to achieve a good transition from exploration phase to exploitation phase. Thereafter, a refraction-opposition-based learning mechanism is introduced to generate the promising solutions and helps the swarm to flee from the local optimal solution. The performance of VGHHO is evaluated on 18 classic benchmarks, 30 latest benchmark tests from CEC2017, 21 benchmark feature selection problems, fault diagnosis problem of wind turbine and PV model parameter estimation problem, respectively. The simulation results indicate that VHHO has higher solution quality and faster convergence speed than basic HHO and some well-known algorithms in the literature on most of the benchmark and real-world problems.