Adaptive Turbine Blade Shape Control via CFD
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Solution Overview
Problem
Existing energy conversion systems face challenges in generating control signals responsive to fluid flow pressure and efficiently changing the three-dimensional shape of turbines to optimize energy conversion, particularly in wind power generation, where increasing blade control leads to increased load weight and decreased wind force reception.
Innovation Solution
An energy conversion device comprising a blade with a primary measuring device to measure fluid flow reactions, a controller using computational fluid dynamics to generate control signals, and an actuator that changes the blade's three-dimensional shape based on these signals, incorporating memory for storing environmental and locational information to optimize turbine shape adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If control mechanisms are added to increase electricity generation, then energy conversion efficiency is improved, but load weight increases
Solution Approach 1:
The patent replaces complex mechanical control systems with a computational approach. Sensors measure blade responses to fluid flow, and a controller uses computational fluid dynamics (CFD) calculations to determine optimal blade shapes. This substitution eliminates the need for heavy mechanical actuators and control mechanisms, achieving energy optimization through information processing rather than mechanical intervention.
Solution Approach 2:
The patent changes the physical parameters of the blade by adjusting its three-dimensional shape based on CFD calculations. The controller modifies blade geometry parameters (such as curvature, thickness distribution, and cross-sectional shape) to optimize energy conversion. This allows dynamic adaptation to varying fluid flow conditions without adding heavy control machinery.
2Productivity
If the number of wind generators is increased, then total energy production is improved, but wind force received by each generator decreases
Solution Approach 1:
The patent makes the blade shape dynamic rather than static. The blade's three-dimensional shape is continuously adjusted based on real-time measurements of fluid flow conditions and blade responses. This dynamic adaptation allows each turbine to optimize its performance for current wind conditions, maximizing energy capture even when spaced closely together in large arrays.
Solution Approach 2:
The patent implements a feedback control system where sensors continuously measure the blade's response to fluid flow, and this information is fed back to the controller. The controller uses this feedback along with CFD calculations to adjust the blade shape optimally. This closed-loop feedback enables each turbine to independently optimize its performance regardless of the number of turbines in the array.
3Productivity
If blade shape is changed to optimize energy conversion, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical shape-changing mechanisms with a computational approach. Instead of using multiple actuators and mechanical linkages to adjust blade geometry, the system uses sensors to measure blade responses and a controller with CFD capabilities to calculate optimal shapes. The complexity is shifted from mechanical components to computational algorithms, reducing physical device complexity while maintaining shape adjustment capability.
4Productivity
If measurement and control systems are added to change turbine shape, then energy conversion is improved, but manufacturing complexity increases
Solution Approach 1:
The patent employs a universal controller that performs multiple functions: it receives sensor data, executes CFD calculations, determines optimal blade shapes, and controls shape adjustment. This multi-functional approach consolidates what would otherwise require separate systems for measurement, computation, decision-making, and actuation, simplifying the manufacturing process while enabling sophisticated energy optimization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enhances energy conversion efficiency without increasing load weight, allows for better fluid flow distribution among turbines, and adapts to environmental conditions, thereby improving overall energy production and reducing distances between energy conversion units.
Implementation Method 1
when the fluid flow exerts an external force on the blade
Implementation Method 2
an actuator configured to change the three-dimensional shape of the blade
Implementation Method 3
a controller configured to generate control signals using the primary value derived from responding to the above primary measured value
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
Disclosed is an energy converting apparatus for converting mechanical energy obtained by a fluid flow into electric energy. The energy converting apparatus comprises: a blade; a measuring device for measuring reaction of the blade when the fluid flow exerts an external force on the blade, and generating a measurement value corresponding to a measurement result; a memory for storing control values; a controller for reading a first control value among the control values from the memory in response to the measurement value output from the measuring device, and generating a control signal by using the first control value; and an actuator for changing a three-dimensional shape of the blade in response to the control signal output from the controller.