Electro-Thermal Simulation of Interconnected Systems at Transient Operating Conditions

2017 ◽  
Author(s):  
Torsten Hauck ◽  
Vibhash Jha ◽  
J. H. J. Janssen
Keyword(s):  
Order Reduction ◽  
Element Model ◽  
Operating Conditions ◽  
System Level ◽  
Large Set ◽  
Component Level ◽  
Model Order ◽  
Design And Optimization ◽  
Efficient Simulation ◽  
Current State

The development of complex electronic modules requires very efficient simulation technique for faster design and optimization process. For smaller component level models, current state of the art FEM/CFD tools is sufficient if appropriate boundary conditions are used. But for larger system level models, this approach can be computationally expensive as the finite element model can lead to very large set of equations. Hence, there is a need for much efficient computational methods such as model order reduction (MOR). MOR was developed to study property of dynamical systems to reduce their complexity without changing input/output to the system.

System Level Bench Test for Trailing Arm Strength Estimation

2006 ◽  
Author(s):  
Jaychandar Muthu ◽  
Kanak Soundrapandian ◽  
Jyoti Mukherjee
Keyword(s):  
Failure Mode ◽  
Real Life ◽  
Element Model ◽  
Suspension System ◽  
System Level ◽  
Bench Test ◽  
Component Level ◽  
Arm Strength ◽  
Bench Testing ◽  
Nonlinear Finite Element Model

For suspension components, bench testing for strength is mostly accomplished at component level. However, replicating loading and boundary conditions at the component level in order to simulate the suspension system environment may be difficult. Because of this, the component's bench test failure mode may not be similar to its real life failure mode in vehicle environment. A suspension system level bench test eliminates most of the discrepancies between simulated component level and real life vehicle level environments resulting in higher quality bench tests yielding realistic test results. Here, a suspension level bench test to estimate the strength of its trailing arm link is presented. A suspension system level nonlinear finite element model was built and analyzed using ABAQUS software. The strength loading was applied at the wheel end. The analysis results along with the hardware test correlations are presented. The reasons why a system level test is superior to a component level one are also highlighted.

Modeling of Capacitive Microaccelerometers with Squeeze Film Damping and Electrostatic Effects Using Model Order Reduction

2009 ◽  
Vol 60-61 ◽  
pp. 213-218
Author(s):  
Ya Fei Zhang ◽  
Wei Zheng Yuan ◽  
Hong Long Chang ◽  
Jing Hui Xu
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
System Level ◽  
Squeeze Film ◽  
Electrostatic Effects ◽  
Model Order ◽  
Circuit Simulator ◽  
System Level Simulation ◽  
Squeeze Film Damping ◽  
Hardware Description

Model order reduction is an effective method to generate macromodels for system-level simulation. But it is difficult to deal with the electro-mechanical-damping coupling problems. So we presents a new approach to model the capacitive microaccelerometers with squeeze film damping and electrostatic effects using model order reduction (MOR) method. In this approach, the mechanical, squeeze film damping and electrostatic domains of the devices are modeled separately and then coupled at system-level. The macromodel for squeezed film damping effects could account for slip condition of the flow at low pressure and edge effects. In addition, some important parameters are preserved as symbol. The extracted macromodels are translated into the hardware description language and imported into a circuit simulator. An accelerometer is used to demonstrate the feasibility and efficiency of the proposed approach. Numerical simulation results show that the extracted macromodel can dramatically reduce the computation cost while capturing the device behavior accurately.

Flow Interactions in Low Bypass Ratio Multi-Spool Turbofan Engines

2019 ◽  
Author(s):  
Vishwas Verma ◽  
Gursharanjit Singh ◽  
A. M. Pradeep
Keyword(s):  
Flow Pattern ◽  
System Modeling ◽  
Three Dimensional ◽  
Integrated System ◽  
Operating Conditions ◽  
System Level ◽  
Component Level ◽  
Turbofan Engines ◽  
Flow Interactions ◽  
Marginal Values

Abstract Multi-spool compression systems are characterized by two or more compressor stages running at different rotational speeds. The response of an individual component can be different from an integrated system. Limiting operating conditions such as choke and stall points could have substantially different effects. The present paper explores the interactions and coupling significance between different stages of a multi-spool compression system. Further, an attempt is made by modifying the shape of the inter-compressor duct (ICD) to improve the system performance. The multi-spool system in this study comprises of the NASA stage 67 as the fan followed by in-house core and bypass ducts and a single stage booster. It is observed that the flow pattern in an ICD is entirely different in stand-alone modeling than in the integrated system modeling, owing to fan wakes and booster upstream influences. The booster performance is dependent on the duct exit flow pattern. The shape of the baseline ICD is tailored to reduce extra losses which is generated due to reduction in the length of the ICD and hence making the system more compact. It is shown that the shape tailoring optimization of ICD done independently result in a significant improvement in the duct exit flow pattern and hence an improvement in the booster performance. However, this gain in the performance is reduced to marginal values for an integrated system. This happens due to a strong coupling of the ICD flow pattern with the fan wakes and highly three dimensional nature of the ICD flow pattern. Therefore, it is found that component level optimization may not give rise to an equivalent system-level improvement.

Fast Multiphysics MEMS Simulation With Arnoldi Model Order Reduction

2008 ◽  
Author(s):  
David Binion ◽  
Xiaolin Chen
Keyword(s):  
Model Order Reduction ◽  
Krylov Subspace ◽  
Order Reduction ◽  
Full Scale ◽  
Solution Time ◽  
System Level ◽  
Computational Time ◽  
Mems Devices ◽  
Model Order ◽  
Reduced Order

Modeling and simulation of Micro Electro Mechanical Systems has become increasingly important as the complexity of MEMS devices increases. In particular, thermal effects on MEMS devices has become a growing topic of interest. Through the FEA, detailed solutions can be obtained to investigate the multiphysics coupling and the transient behavior of a MEMS device at the component level. For system-level integration and simulation, the FEA discretization often results in large full-scale models, which can be computationally demanding or even prohibitive to solve. Model order reduction (MOR) was investigated in this study to reduce problem size for complex dynamic system modeling. The Arnoldi method was implemented for MOR to improve the computational efficiency while preserving the input-output behavior of coupled MEMS simulation. Using this method, a low dimensional Krylov subspace was extracted from the full-scale system model. Reduced order solution of the transient temperature distributions was then determined by projecting the system onto the extracted Krylov subspace and solving the reduced system. An electro thermal MEMS actuator was studied for various inputs. To compare results, the full-scale analyses were performed using the commercial FEA program ANSYS. It was found that the computational time of MOR was only a fraction of the full-scale solution time, with the relative errors ranging from 1.1% to 4.5% at different positions on the actuator. Our results show that the reduced order modeling via Alnoldi can significantly decrease the transient analysis solution time without much loss in accuracy for coupled-field MEMS simulation.

Simulation in System-Level Based on Model Order Reduction for a Square-Wave Micromixer

2015 ◽  
Vol 16 (7-8) ◽  
pp. 307-314 ◽  
Author(s):  
Xueye Chen ◽  
Jienan Shen
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
System Level ◽  
Order Model ◽  
Model Order ◽  
Reduced Order ◽  
Square Wave ◽  
Bonding Method ◽  
Proper Orthogonal ◽  
Sodium Solution

AbstractWith the aim to optimize design, a simulation in system level has been presented for the square-wave micromixer in this article. The square-wave micromixer is divided into straight channels and square-wave units. The reduced-order model based on proper orthogonal decomposition is applied in calculating concentration of the sample in the straight channels, and numerical simulation is applied in calculating concentration of the sample in the square-wave units. The data can mutually be transferred between straight channels and square-wave units by data fitting and interpolation. The maximal relative deviation is 1.52% between simulation in system-level and only simulation. The computational efficiency will be improved significantly with the numbers of straight channels increasing. The Polymethyl methacrylate (PMMA) micromixer is fabricated with mill and hot bonding method. The mixing experiment of fluorescein sodium solution with different concentrations is carried out to verify simulation. The relative deviations between simulation in and experimental results are below 8.26%.

Deterministic and Stochastic Model Order Reduction for Vibration Analyses of Structures With Uncertainties

2017 ◽  
Vol 139 (2) ◽  
Author(s):  
Ji Yang ◽  
Béatrice Faverjon ◽  
Herwig Peters ◽  
Steffen Marburg ◽  
Nicole Kessissoglou
Keyword(s):  
Finite Element ◽  
Stochastic Model ◽  
Dynamic Characteristics ◽  
Model Order Reduction ◽  
Krylov Subspace ◽  
Order Reduction ◽  
Element Model ◽  
Uncertain Parameters ◽  
Model Order ◽  
Frequency Responses

To reduce the computational effort using polynomial chaos expansion to predict the dynamic characteristics of structures with several uncertain parameters, hybrid techniques combining stochastic finite element analysis with either deterministic or stochastic model order reduction (MOR) are developed. For the deterministic MOR, the Arnoldi-based Krylov subspace technique is implemented to reduce the system matrices of the finite element model. For the stochastic MOR, a stochastic reduced basis method is implemented in which the structural modal and frequency responses are approximated by a small number of basis vectors using stochastic Krylov subspace. To demonstrate the computational efficiency of each reduced stochastic finite element model, variability in the natural frequencies and frequency responses of a simply supported flexible plate randomized by uncertain geometrical and material parameters is examined. Results are compared with both Monte Carlo (MC) simulations and nonreduced stochastic models. Using the reduced models, the effects of the individual uncertain parameters as well as the combined uncertainties on the dynamic characteristics of the plate are examined.

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