Efficient Component-Based Vibration and Power Flow Analysis of a Vehicle Structure

2001 ◽  
Author(s):  
Yung-Chang Tan ◽  
Soo-Yeol Lee ◽  
Matthew P. Castanier ◽  
Christophe Pierre
Keyword(s):  
Power Flow ◽  
Flow Analysis ◽  
Element Model ◽  
Reduced Order Model ◽  
Order Model ◽  
Component Structure ◽  
Modeling And Analysis ◽  
Reduced Order ◽  
Vehicle Structure ◽  
Entire Vehicle

Abstract A case study on the efficient prediction of vibration and power flow in a vehicle structure is presented. The modeling and analysis technique is based on component mode synthesis (CMS). First, the finite element model (FEM) of the entire vehicle structure is partitioned into component models. Then, the Craig-Bampton method is used to assemble a CMS model of the vehicle. The CMS matrices are further reduced by finding characteristic constraint (CC) modes. A relatively small number of CC modes are selected to capture the primary motion of the interface between components, yielding a highly reduced order model of the vehicle vibration in the low- to mid-frequency range. Using this reduced order model (ROM), the power flow and vibration response of the vehicle is analyzed for several design configurations. A design change in one component structure requires a re-analysis of the FEM for that component only, in order to generate a new ROM of the entire vehicle. It is found that this component-based approach allows efficient evaluation of the effectiveness of the vehicle design changes.

Intentional Mistuning With Predominant Aerodynamic Effects

2018 ◽  
Author(s):  
Carlos Martel ◽  
José J. Sánchez
Keyword(s):  
Finite Element ◽  
Traveling Waves ◽  
Element Model ◽  
Simple Expression ◽  
Reduced Order Model ◽  
Action Mechanism ◽  
Aerodynamic Forces ◽  
Order Model ◽  
Reduced Order ◽  
Random Mistuning

Intentional mistuning is a well known procedure to decrease the uncontrolled vibration amplification effects of the inherent random mistuning and to reduce the sensitivity to it. The idea is to introduce an intentional mistuning pattern that is small but much larger that the existing random mistuning. The frequency of adjacent blades is moved apart by the intentional mistuning, reducing the effect of the blade-to-blade coupling and thus the effect of the random mistuning. The situation considered in this work is more complicated because the main source for the blade damping is the effect of the aerodynamic forces (as it happens in a blisk for a family of blade dominated modes with very similar frequencies). In this case the damping is clearly defined for the tuned traveling waves but not for each blade. The problem is analyzed using the Asymptotic Mistuning Model methodology. A reduced order model is derived that allows us to understand the action mechanism of the intentional mistuning, and gives a simple expression for the estimation of its beneficial effect. The results from the reduced model are compared with those from a finite element model of a more realistic rotor under different forcing conditions.

Prediction of Geometrically Induced Localization Effects Using a Subset of Nominal System Modes

2019 ◽  
Author(s):  
Thomas Maywald ◽  
Christoph R. Heinrich ◽  
Arnold Kühhorn ◽  
Sven Schrape ◽  
Thomas Backhaus
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Reduced Order Model ◽  
Vibration Measurement ◽  
Mode Shapes ◽  
Compressor Stage ◽  
Order Model ◽  
Reduced Order ◽  
Numerical Predictions

Abstract It is widely known that the vibration characteristics of blade integrated discs can dramatically change in the presence of manufacturing tolerances and wear. In this context, an increasing number of publications discuss the influence of the geometrical variability of blades on phenomena like frequency splitting and mode localization. This contribution is investigating the validity of a stiffness modified reduced order model for predicting the modal parameters of a geometrically mistuned compressor stage. In detail, the natural frequencies and mode shapes, as well as the corresponding mistuning patterns, are experimentally determined for an exemplary rotor. Furthermore, a blue light fringe projector is used to identify the geometrical differences between the actual rotor and the nominal blisk design. With the help of these digitization results, a realistic finite element model of the whole compressor stage is generated. Beyond that, a reduced order model is implemented based on the nominal design intention. Finally, the numerical predictions of the geometrically updated finite element model and the stiffness modified reduced order model are compared to the vibration measurement results. The investigation is completed by pointing out the benefits and limitations of the SNM-approach in the context of geometrically induced mistuning effects.

A Method for Reducing the Order of Nonlinear Dynamic Systems

1984 ◽  
Vol 51 (2) ◽  
pp. 391-398 ◽  
Author(s):  
S. F. Masri ◽  
R. K. Miller ◽  
H. Sassi ◽  
T. K. Caughey
Keyword(s):  
Dynamic Systems ◽  
Three Dimensional ◽  
Element Model ◽  
Random Excitation ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Dimensional Finite Element ◽  
Restoring Forces ◽  
Three Dimensional Finite Element

An approximate method that uses conventional condensation techniques for linear systems together with the nonparametric identification of the reduced-order model generalized nonlinear restoring forces is presented for reducing the order of discrete multidegree-of-freedom dynamic systems that possess arbitrary nonlinear characteristics. The utility of the proposed method is demonstrated by considering a redundant three-dimensional finite-element model half of whose elements incorporate hysteretic properties. A nonlinear reduced-order model, of one-third the order of the original model, is developed on the basis of wideband stationary random excitation and the validity of the reduced-order model is subsequently demonstrated by its ability to predict with adequate accuracy the transient response of the original nonlinear model under a different nonstationary random excitation.

Inverse Determination of Moving Heat Flux Distributions Using Reduced Order Models

2014 ◽  
Author(s):  
Brian H. Dennis ◽  
Ashkan Akbariyeh ◽  
John Michopoulos ◽  
Foteini Komninelli ◽  
Athanasios Iliopoulos
Keyword(s):  
Heat Flux ◽  
Finite Element ◽  
Finite Element Model ◽  
Target Surface ◽  
Element Model ◽  
Basis Functions ◽  
Reduced Order Model ◽  
Analysis Model ◽  
Order Model ◽  
Reduced Order

Optimization-based solutions to inverse problems involve the coupling of an analysis model, such as a finite element model, with a numerical optimization method. The goal is to determine a set of parameters that minimize an objective function that is determined by solving the analysis model. In this paper, we present an approach that dramatically reduces the computational cost for solving this inverse problems in this way by replacing the original full order finite element model (FOM) with a reduced order model (ROM) that is both accurate and quick to compute. The reduced order model is constructed with basis functions generated using proper orthogonal decomposition of set of solutions from the FOM. A discrete Galerkin method is used to project the differential equation on the basis functions. This approach allows us to transform the linear full order finite element model into an equivalent discrete ROM with far fewer unknowns. The method is applied to a parameter estimation problem in heat transfer. Specifically, we determine the parameters governing the magnitude and distribution of an unknown surface heat flux moving at a constant velocity across the surface of a solid bar of material. A finite element model was implemented in the commercial package COMSOL and a corresponding ROM was constructed. The ROM was coupled with an optimization algorithm to determine the parameter values that minimized the distance between the computed surface temperatures and the target surface temperature. The target surface temperature was generated using simulated measurements produced from the full order finite element model. Several optimization methods were used. The results show the approach can recover the parameters with high accuracy with twenty seven FOM runs.

Estimation of Forcing Function for a Geometrically Mistuned Bladed Rotor via Modified Modal Domain Analysis

2015 ◽  
Author(s):  
Vinod Vishwakarma ◽  
Alok Sinha
Keyword(s):  
Estimation Algorithm ◽  
Element Model ◽  
Domain Analysis ◽  
Reduced Order Model ◽  
Dynamic Responses ◽  
Order Model ◽  
Mass Model ◽  
Reduced Order ◽  
Forcing Function ◽  
Bladed Rotor

Modified Modal Domain Analysis (MMDA) is a method to generate an accurate reduced order model (ROM) of a bladed disk with geometric mistuning. An algorithm based on MMDA ROM and a state observer is developed to estimate forcing functions for synchronous (including integer multiples) conditions from the dynamic responses obtained at few nodal locations of blades. The method is tested on a simple spring-mass model, finite element model (FEM) of a geometrically mistuned academic rotor and FEM of a bladed rotor of an industrial scale transonic research compressor. The accuracy of the forcing function estimation algorithm is examined by varying the order of reduced-order model and the number of vibration output signals.

A Nonlinear Finite Element Model for Leaf Springs

2003 ◽  
Author(s):  
Mohamed A. Omar ◽  
Hiroyuki Sugiyama ◽  
Ahmed A. Shabana ◽  
Wei-Yi Loh ◽  
Rena Basch
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Nonlinear Finite Element ◽  
Reduced Order Model ◽  
Body Motion ◽  
Leaf Spring ◽  
Order Model ◽  
Reduced Order ◽  
Nonlinear Finite Element Model

This paper presents a nonlinear finite element model for the leaf spring that can be used in multibody applications and vehicle dynamic simulations. The floating frame of reference formulation is used in this investigation to model leaf spring nonlinear dynamics. This formulation accounts for the coupling between different modes of deformation as well as the nonlinear coupling between the rigid body motion and the elastic deformation. By employing component mode synthesis techniques, a reduced order model is obtained for the leaf spring while maintaining a good degree of accuracy. The inertia shape integrals can be calculated once in advance using a preprocessor and then stored to be used to automatically generate the nonlinear equations of motion of the leaf spring. The use of a preprocessor to evaluate the inertia shape integrals before the dynamic simulation leads to considerable saving in CPU time and allows the utilization of existing finite element computer codes to obtain the data required for the flexible body simulation. This reduced order model is implemented in a general multibody algorithm in order to examine the effectiveness and robustness of the proposed techniques. As an application, the wind-up deformation of the front suspension system of a typical sport utility vehicle under severe braking condition is investigated.

Study on Reduced Order Model in Large-Span Roof Vibration under Wind Actions

2014 ◽  
Vol 580-583 ◽  
pp. 3066-3070
Author(s):  
Fang Jin Sun ◽  
Da Ming Zhang
Keyword(s):  
Finite Element ◽  
Strain Energy ◽  
Strain Energy Function ◽  
Element Model ◽  
Reduced Order Model ◽  
High Fidelity ◽  
Order Model ◽  
Reduced Order ◽  
Large Span ◽  
Wind Actions

Reduced order model was for the first time employed for the large-span structure by system identification approach. The structure’s modal amplitudes are utilized to construct strain energy function of the system. A high fidelity finite element model is adopted to calculate modes and strain energy information to determine the unknown coefficients in the strain energy function. Wind-induced responses of a large-span structure were computed by the proposed method. The results were compared well with those obtained from the high fidelity finite element model and experiments. It proves that reduced order model is an effective way to compute large-span structure responses under wind actions when taking aero-elastic effects into account.

Application of Conditional Space-Time Proper Orthogonal Decomposition to Engine In-Cylinder Flow Analysis

2021 ◽  
Author(s):  
Rui Gao ◽  
Kwee-Yan Teh ◽  
Fengnian Zhao ◽  
Mengqi Liu ◽  
David L. S. Hung
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Internal Combustion Engines ◽  
Flow Analysis ◽  
Space Time ◽  
Orthogonal Decomposition ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Cylinder Flow ◽  
Proper Orthogonal

Abstract The cycle-to-cycle variation of engine in-cylinder flow is critical for the improvement of performance for spark-ignition internal combustion engines. Proper orthogonal decomposition (POD), with its ability to extract the most energetic fluctuation structure, is widely used to analyze the in-cylinder flow and understand the variation of its evolution in different cycles. However, both of the two existing approaches to use POD for engine flow analysis encounter difficulties when applied for this purpose. Phase-dependent POD decomposes a data set in which all samples are taken at a certain engine phase (crank angle) from different cycles, but the POD results at neighboring engine phases do not necessarily evolve coherently. Phase-invariant POD, when applied to analyze tumble flow, stretches/compresses and interpolates the flow fields obtained at different engine phases onto the same grid, and this deformation means that phase-invariant POD results are no longer significant in energy sense. To overcome these difficulties, we propose an adaptation of conditional space-time POD to work with engine flow, with which the flow within a range of engine phases in each cycle is considered as one sample. It is shown that the low-order modes obtained with conditional space-time POD capture fluctuation structures that evolve coherently, and these results are compared and contrasted with those of the two existing POD approaches. A reduced-order model of the engine in-cylinder flow is constructed based on the partial sum of the modes and coefficients obtained from the conditional space-time POD, and it is shown that this new reduced-order model identifies structure that is both coherent spatially and temporally.

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