Flexible Rotor Eigenmode Simulation for Variable Operating Conditions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional approaches to simulating the transverse motion response of rotors are computationally expensive and lack accuracy due to their inability to account for parameter-dependent properties, leading to inaccurate results when rotational speed and temperature change.
Innovation Solution
The method involves computing and matching eigenmodes across varying parameter values, using correlation metrics to store modal properties in lookup tables, which are then used to simulate the transverse motion response efficiently and accurately, reducing computational expense while maintaining high accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional simulation methods are used to simulate transverse motion response of rotors, then the simulation can be performed, but the computational expense is high and accuracy is reduced due to inability to account for parameter-dependent properties
Solution Approach 1:
The patent pre-computes and stores mode shapes at discrete parameter values (speed, temperature) before actual simulation. These pre-computed mode shapes are stored in a database and retrieved during simulation using interpolation, eliminating the need to re-compute them during each simulation run. This preliminary action significantly reduces computational time while maintaining accuracy.
Solution Approach 2:
The patent accounts for parameter-dependent properties by computing mode shapes at multiple discrete values of critical parameters (rotational speed, temperature). The simulation then interpolates between these pre-computed parameter values to accurately capture the effect of parameter changes on rotor behavior, thereby improving simulation accuracy without proportional increase in computational cost.
2Measurement precision
If parameter-dependent properties are accounted for in rotor simulation, then simulation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the continuous parameter space into discrete parameter values (e.g., specific speed values, temperature points). Mode shapes are computed at these discrete segments and stored. During simulation, the system selects and interpolates between these segments rather than continuously recomputing, thereby managing computational complexity while capturing parameter-dependent behavior.
Solution Approach 2:
The patent creates a database copy of mode shapes at various parameter values. Instead of computing mode shapes during each simulation, the system copies pre-computed mode shapes from the database and uses them with interpolation. This copying approach reduces computational complexity while maintaining the ability to account for parameter-dependent properties.
3Measurement precision
If mode shapes are recomputed during simulation to account for parameter changes, then accuracy is improved, but computational expense increases significantly
Solution Approach 1:
The patent performs the computationally intensive mode shape computation as a preliminary action before the actual simulation. The results are stored in a database for quick retrieval. During simulation, the system only performs lightweight interpolation operations rather than full recomputation, thereby maintaining parameter-dependent accuracy while achieving significant speedup (5-10 times faster according to the patent).
Data Source
AI summary
Exemplary embodiments simulate the eigenmodes of a flexible rotor in a model of a rotor and thus reduce the number of variables and computation expense required during simulation of the transverse motion response of the rotor. The exemplary embodiments may use data structures, such as lookup tables, to store precomputed information that may be used for the determining eigenmode properties as the values of one or more parameters affecting the eigenmode properties (e.g., speed, shaft temperature, bearing viscosity, normal force acting along the rotor shaft axis, turbine power level, turbine fluid flow rate, etc.) change during a simulation. The use of the data structures helps to reduce the computational expense during the simulation. The computational expense is reduced because the eigenmode properties need not be calculated dynamically during each simulation run and because there are far fewer variables to represent the transverse motion along the flexible rotor and to indicate vibration and loads during simulation.