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1.
Microfluidic systems are increasingly popular for rapid and cheap determinations of enzyme assays and other biochemical analysis. In this study reduced order models (ROM) were developed for the optimization of enzymatic assays performed in a microchip. The model enzyme assay used was β-galactosidase (β-Gal) that catalyzes the conversion of Resorufin β-d-galactopyranoside (RBG) to a fluorescent product as previously reported by Hadd et al. (Anal Chem 69(17): 3407–3412, 1997). The assay was implemented in a microfluidic device as a continuous flow system controlled electrokinetically and with a fluorescence detection device. The results from ROM agreed well with both computational fluid dynamic (CFD) simulations and experimental values. While the CFD model allowed for assessment of local transport phenomena, the CPU time was significantly reduced by the ROM approach. The operational parameters of the assay were optimized using the validated ROM to significantly reduce the amount of reagents consumed and the total biochip assay time. After optimization the analysis time would be reduced from 20 to 5.25 min which would also resulted in 50% reduction in reagent consumption.  相似文献
2.
Bubbles and droplets both consist of a liquid in contact with a gas. In this paper, we consider the interface between the incompressible liquid and the gas as a zero thickness structure. The position of the interface is determined by the equilibrium between surface tension effects and the fluid pressure difference across the interface. So, the structure interacts with the fluids on either side. The behaviour of a limited number of bubbles and droplets can therefore be simulated as a Fluid-Structure Interaction (FSI) problem.Most existing techniques frequently used for studying bubble and droplet dynamics, such as Level Set or Volume Of Fluid, use monolithic schemes. The flow on both sides of the interface and the position of the interface are calculated in a single code. In this contribution, a partitioned approach is presented. The position of the interface is calculated with a structural solver. Given a displacement of the interface, a separate flow solver calculates the flow on the liquid side of the interface with the Arbitrary Lagrangian-Eulerian (ALE) technique. The structural solver uses a reduced order model of the flow solver to obtain implicit coupling between both solvers. This reduced order model is built up during the coupling iterations of a time step. Grid and time converged solutions of two axisymmetric problems are calculated: an oscillating water droplet in air and the growth and detachment of an air bubble from the outlet of a vertical needle, submerged in quiescent water.  相似文献
3.
A model-based methodology was developed to optimize microfluidic chips for the simultaneous enzymatic quantification of sucrose, d-glucose and d-fructose in a single microfluidic channel with an integrated optical detection system. The assays were based on measuring the change in concentration of the reaction product NADH, which is stoichiometrically related to the concentration of those components via cascade of specific enzymatic reactions. A reduced order mathematical model that combines species transport, enzyme reaction, and electrokinetic bulk flow was developed to describe the operation of the microfluidic device. Using this model, the device was optimized to minimize sensor response time and maximize signal output by manipulating the process conditions such as sample and reagent volume and flow rate. According to this simulation study, all sugars were quantified within 2.5 min in the optimized microchip. A parallel implementation of the assays can further improve the throughput. In addition, the amount of consumed reagents was drastically reduced compared to microplate format assays. The methodology is generic and can easily be adapted to other enzymatic microfluidic chips.  相似文献
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This paper considers the problem of simulating the humidity distributions of a grain storage system. The distributions are described by partial differential equations (PDE). It is quite difficult to obtain the humidity profiles from the PDE model. Hence, a discretization method is applied to obtain an equivalent ordinary differential equation model. However, after applying the discretization technique, the cost of solving the system increases as the size increases to a few thousands. It may be noted that after discretization, the degree of freedom of the system remain the same while the order increases. The large dynamic model is reduced using a proper orthogonal decomposition based technique and an equivalent model but of much reduced size is obtained. A controller based on optimal control theory is designed to obtain an input such that the output humidity reaches a desired profile and also its stability is analyzed. Numerical results are presented to show the validity of the reduced model and possible further extensions are identified.  相似文献
7.
A new structure preserving model order reduction technique for second order systems in limited frequency interval is presented. Frequency limited Gramians (FLGs) and corresponding continuous time algebraic lyapunov equations (CALEs) are developed. For solution of CALEs and Cholesky factorization of FLGs, computationally efficient approximation scheme is proposed. Multiple transformations based on balancing of frequency limited position or velocity Gramians are defined in order to compute Hankel singular values (HSVs). Frequency limited second order balanced truncation based on magnitudes of HSVs is performed for order reduction. Moreover, stability conditions for reduced order models (ROMs) are stated and algorithms for achieving stability in ROMs are proposed. Results are compared with existing technique to certify the usefulness of the proposed technique.  相似文献
8.
A broadly-applicable, control-relevant system identification methodology for nonlinear restricted complexity models (RCMs) is presented. Control design based on RCMs often leads to controllers which are easy to interpret and implement in real-time. A control-relevant identification method is developed to minimize the degradation in closed-loop performance as a result of RCM approximation error. A two-stage identification procedure is presented. First, a nonlinear ARX model is estimated from plant data using an orthogonal least squares algorithm; a Volterra series model is then generated from the nonlinear ARX model. In the second stage, a RCM with the desired structure is estimated from the Volterra series model through a model reduction algorithm that takes into account closed-loop performance requirements. The effectiveness of the proposed method is illustrated using two chemical reactor examples.  相似文献
9.
The objective of this paper is to demonstrate the ability of proper orthogonal decomposition, in combination with domain decomposition, to produce accurate reduced order models (ROMs) for two-dimensional high-speed flows with moving shock waves. To demonstrate this ability, a blunt body flow with quasi-steady shock motion is considered. The blunt body flow contains a strong bow shock that is moved via a change in inlet Mach number and angle of attack. Accuracy is quantified by comparing surface pressures obtained from the ROMs with those from the full order simulation under the same free stream conditions. The order reduction, and computational performance of the ROM is also quantified relative to the full order simulation. The robustness of the ROM to varying flow parameters is explored. A non-Galerkin quasi-implicit steady state implementation is considered.  相似文献
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