Numerical and Experimental Analysis of A Vertical-Axis Eccentric-disc Variable-Pitch Turbine(VEVT)

A combined experimental and numerical investigation is carried out to study the performance of a vertical-axis eccentric-disc variable-pitch turbine(VEVT).A scheme of eccentric disc pitch control mechanism based on doubleblock mechanism is proposed.The eccentric control mechanism and the deflection angle control mechanism in the pitch control structure are designed and optimized according to the functional requirements of the turbine,and the three-dimensional model of the turbine is established.Kinematics analysis of the eccentric disc pitch control mechanism is carried out.Kinematics parameters and kinematics equations which can characterize its motion characteristics are derived.Kinematics analysis and simulation are carried out,and the motion law of the corresponding mechanical system is obtained.By analyzing the force and motion of blade of VEVT,the expressions of the important parameters such as deflection angle,attack angle and energy utilization coefficient are obtained.The lateral induced velocity coefficient is acquired by momentum theorem,the hydrodynamic parameters such as energy utilization coefficient are derived,and the hydrodynamic characteristics of VEVT are also obtained.The experimental results show that the turbine has good energy capture capability at different inflow velocities of different sizes and directions,which verifies that VEVT has good self-startup performance and high energy capture efficiency.

Detecting the presence of natural forests using airborne laser scanning data

Centuries of forest exploitation have caused significant loss of natural forests in Europe,leading to a decline in populations for many species.To prevent further loss in biodiversity,the Norwegian government has set a target of protecting 10%of the forested area.However,recent data from the National Forest Inventory(NFI)reveals that less than 2%of Norway's forested area consists of natural forests.To identify forests with high conservation value,we used vertical and horizontal variables derived from airborne laser scanning(ALS)data,along with NFI plot measurements.Our study aimed to predict the presence of natural forests across three counties in southeastern Norway,using three different definitions:pristine,near-natural,and semi-natural forests.Natural forests are scarce,and their underrepresentation in field reference data can compromise the accuracy of the predictions.To address this,we assessed the potential gain of including additional field data specifically targeting natural forests to achieve a better balance in the dataset.Additionally,we examined the impact of stratifying the data by dominant tree species on the performance of the models.Our results revealed that semi-natural forests were the most accurately predicted,followed by near-natural and pristine forests,with Matthews correlation coefficient values of 0.32,0.24,and 0.17,respectively.Including additional field data did not improve the predictions.However,stratification by species improved the accuracy of predictions for near-natural and semi-natural forests,while reducing accuracy for pristine forests.The use of horizontal variables did not improve the predictions.Our study demonstrates the potential of ALS data in identifying forests with high conservation value.It provides a basis for further research on the use of ALS data for the detection and conservation of natural forests,offering valuable insights to guide future forest preservation efforts.