A Reduced-Order Model of a Microfluidic Transistor

2013 ◽  
Author(s):  
Joseph Bakarji ◽  
Khoudor Keniar ◽  
Mohammad Cheikh ◽  
Issam Lakkis
Keyword(s):  
Reduced Order Model ◽  
Elastic Model ◽  
Small Signal ◽  
Micro Channel ◽  
Order Model ◽  
Reduced Order ◽  
Proposed Model ◽  
Structure Problem ◽  
Flow Inertia ◽  
The Impact

A reduced-order model of a Microfluidic Transistor is presented. The transistor is essentially a long micro channel between substrate and a membrane that is pressure actuated. The proposed model captures steady (DC) and small signal (AC) behavior of the device in a manner analogous to standard semiconductor transistor models. The model is based on steady and perturbed unsteady solutions of the conservation of mass and momentum, coupled with an elastic model for the membrane. To improve the accuracy and to enhance the range of validity, the model is enhanced by numerical simulations of the coupled fluid-structure problem. The model predicts dependence of the transconductance on the pressure differentials across the membrane and along the channel. The proposed model also investigates the impact of flow inertia, among other effects, on the dynamic behavior of the transistor.

scholarly journals An improved reduced-order model for pressure drop across arterial stenoses

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258047
Author(s):  
Konstantinos G. Lyras ◽  
Jack Lee
Keyword(s):  
Pressure Drop ◽  
Reduced Order Model ◽  
Accurate Estimation ◽  
Classification Error ◽  
Fractional Flow ◽  
Order Model ◽  
Reduced Order ◽  
Flow Reserve ◽  
Proposed Model ◽  
New Formulation

Quantification of pressure drop across stenotic arteries is a major element in the functional assessment of occlusive arterial disease. Accurate estimation of the pressure drop with a numerical model allows the calculation of Fractional Flow Reserve (FFR), which is a haemodynamic index employed for guiding coronary revascularisation. Its non-invasive evaluation would contribute to safer and cost-effective diseases management. In this work, we propose a new formulation of a reduced-order model of trans-stenotic pressure drop, based on a consistent theoretical analysis of the Navier-Stokes equation. The new formulation features a novel term that characterises the contribution of turbulence effect to pressure loss. Results from three-dimensional computational fluid dynamics (CFD) showed that the proposed model produces predictions that are significantly more accurate than the existing reduced-order models, for large and small symmetric and eccentric stenoses, covering mild to severe area reductions. FFR calculations based on the proposed model produced zero classification error for three classes comprising positive (≤ 0.75), negative (≥ 0.8) and intermediate (0.75 − 0.8) classes.

Reduced-Order Model of a Mistuned Multi-Stage Bladed Rotor

2007 ◽  
Author(s):  
Alok Sinha
Keyword(s):  
Degrees Of Freedom ◽  
Maximum Amplitude ◽  
Reduced Order Model ◽  
Order Model ◽  
Mass Model ◽  
Reduced Order ◽  
Multi Stage ◽  
Bladed Rotor ◽  
The Impact ◽  
Three Degrees Of Freedom

This paper deals with a reduced-order model of a multi-stage rotor in which each stage has a different number of blades. In particular, it is shown that a reduced-order model can be developed on the basis of tuned modes of certain bladed disks. The validity of this algorithm is shown for a spring-mass model with three degrees of freedom per sector. In addition, the statistical distributions of the peak maximum amplitude are generated via Monte Carlo simulations, and the impact of mistuning is examined for a two-stage rotor.

Reduced Order Model for a Two Stage Gas Turbine Including Mistuned Bladed Disks and Shaft Interaction

2009 ◽  
Author(s):  
Luis A. Boulton ◽  
Euro Casanova
Keyword(s):  
Finite Element ◽  
Gas Turbine ◽  
Reduced Order Model ◽  
Mode Shapes ◽  
Order Model ◽  
Two Stage ◽  
Bladed Disks ◽  
Reduced Order ◽  
Bladed Disk ◽  
The Impact

A number of previous works have suggested that in some cases the interaction between shaft and bladed disk modes could significantly modify the dynamics of the whole assembly i.e. the bladed disks mounted on a flexible shaft. This paper presents the application of a previously published reduced-order modeling technique to the dynamical modeling of a real two stage gas turbine, including the bladed disks and the shaft. In the resulting reduce order model, mistuning is included in the bladed disk models and the shaft is modeled using beam finite elements according to the classical rotordynamic approach. Generation of finite element parent model for the real turbine is presented and discussed as well as simplifications used in order to generate the reduced order model. Comparisons are made between the reduced model and the full finite element solution for free response frequencies and mode shapes in order to assess the methodology and to evaluate the impact of simplifying hypothesis considered in model generation. Finally, this work also shows interaction between shaft modes and bladed disk modes, therefore confirming that stage independent analysis might not be adequate for predicting the global dynamic response of some turbomachinery rotors.

Statistical Evaluation of the Performance Impact of Manufacturing Variations for Steam Turbines

2016 ◽  
Author(s):  
Juntao Xiong ◽  
Jing Yang ◽  
Ivan McBean ◽  
Said Havakechian ◽  
Feng Liu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Aerodynamic Performance ◽  
Reduced Order Model ◽  
Fast Method ◽  
Steam Turbines ◽  
Order Model ◽  
Machining Processes ◽  
Reduced Order ◽  
The Impact

A fast method is presented for evaluating the impact of blade manufacturing variations on the aerodynamic performance of turbomachines. The method consists of two parts. Firstly, an adjoint method is developed to evaluate the aerodynamic sensitivities for multistage turbomachines. This sensitivity information may then be used to perform fast direct Monte Carlo simulations to obtain the statistical distribution of the variations of aerodynamic performances resulting from any given set of manufacturing variations. Secondly, a method is developed to construct reduced-order models for the three-dimensional blades manufacturing variations using the Principal Component Analysis (PCA) method. Monte-Carlo simulations with the adjoint sensitivities can then be applied to the full and individual modes of the blade manufacturing deviations. The proposed method is applied to the last two stages of a low-pressure steam turbine. A total of 29 sets of measured manufacturing deviations of the last-stage rotor blades are used to construct a reduced-order model of the manufacturing variations. The manufacturing variation reduced-order model helps identify origins of the manufacturing deviations connected to the machining processes of the blades. Relations of the statistics of the aerodynamic performance variations such as mean, standard deviation, etc. to the different modes of manufacturing deviations are studied and analyzed.

scholarly journals An efficient multigrid-DEIM semi-reduced-order model for simulation of single-phase compressible flow in porous media

2020 ◽  
Author(s):  
Jing-Fa Li ◽  
Bo Yu ◽  
Dao-Bing Wang ◽  
Shu-Yu Sun ◽  
Dong-Liang Sun
Keyword(s):  
Porous Media ◽  
Equation Of State ◽  
Single Phase ◽  
Reduced Order Model ◽  
Flow In Porous Media ◽  
Order Model ◽  
Reduced Order ◽  
Proposed Model ◽  
Speed Up ◽  
Robinson Equation

Abstract In this paper, an efficient multigrid-DEIM semi-reduced-order model is developed to accelerate the simulation of unsteady single-phase compressible flow in porous media. The cornerstone of the proposed model is that the full approximate storage multigrid method is used to accelerate the solution of flow equation in original full-order space, and the discrete empirical interpolation method (DEIM) is applied to speed up the solution of Peng–Robinson equation of state in reduced-order subspace. The multigrid-DEIM semi-reduced-order model combines the computation both in full-order space and in reduced-order subspace, which not only preserves good prediction accuracy of full-order model, but also gains dramatic computational acceleration by multigrid and DEIM. Numerical performances including accuracy and acceleration of the proposed model are carefully evaluated by comparing with that of the standard semi-implicit method. In addition, the selection of interpolation points for constructing the low-dimensional subspace for solving the Peng–Robinson equation of state is demonstrated and carried out in detail. Comparison results indicate that the multigrid-DEIM semi-reduced-order model can speed up the simulation substantially at the same time preserve good computational accuracy with negligible errors. The general acceleration is up to 50–60 times faster than that of standard semi-implicit method in two-dimensional simulations, but the average relative errors of numerical results between these two methods only have the order of magnitude 10−4–10−6%.

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