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In this work, a novel image-based method is presented to characterize the heat and mass transfer rates in a Hele-Shaw microfluidic reactor. A Fourier transform infrared (FTIR) spectrometer is used in transmission mode in combination with an infrared (IR) camera to simultaneously measure the molar concentration and the thermal fields in the microfluidic chip within few seconds. A classical exothermic NaOH + HCl → NaCl + H2O chemical reaction is used to produce a multiphase flow and a heat source in the reactor. The molar concentration fields of all the species are measured using the IR spectrum in the mid-IR region, and the heat fields are obtained simultaneously from the proper emission. The quantitative aspect of the method is illustrated by comparing the molar concentration profiles to a reactor model, based on the advection-diffusion-reaction equations. The good agreement between the model and experimental data validates the method, and the expected strong diffusion-limited reaction regime in laminar microfluidic reactor is achieved. Thus, the results of this work provide a new and efficient thermospectroscopic imaging method to perform rapid, contactless and in operando heat and mass transfer characterizations in laminar microfluidic reactive flows.

In this paper, the problem of the quantitative characterization of thermal resistance fields in a multilayer sample is addressed by using the classical front face flash method as the thermal excitation and infrared thermography (IRT) as the monitoring sensor. In this challenging problem, the complete inverse processing of a multilayer analytical model is difficult due to the lack of sensitivity of some parameters (layer thickness, depth of thermal resistance, etc.) and the expansive computational iterative processing. For these reasons, the proposed strategy is to use a simple multilayer problem where only one resistive layer is estimated. Moreover, to simplify the inverse processing often based on iterative methods, an asymptotic development method is proposed here. Regarding the thermal signal reconstruction (TSR) methods, the drawback of these methods is the inability to be quantitative. To overcome this problem, the method incorporates a calibration process originating from the complete analytical quadrupole solution to the thermal problem. This analytical knowledge allows self-calibration of the asymptotic method. From this calibration, the quantitative thermal resistance field of a sample can be retrieved with a reasonable accuracy lower than 5%. [ABSTRACT FROM AUTHOR]

Raw signal simulation is an important tool to test the effectiveness of the system parameters and imaging algorithms. A fast raw signal simulation method for multi-circular synthetic aperture imaging is proposed based on the inverse processing of the imaging algorithm and the nonuniform fast Fourier transform. The analytical description and processing procedure are presented. Simulation results of an ideal point target and a human model demonstrate the validity and effectiveness. Compared with the common time-domain method, the proposed method can achieve equivalent performance with higher efficiency. [ABSTRACT FROM AUTHOR]

In this paper, the problem of the quantitative characterization of thermal resistance fields in a multilayer sample is addressed by using the classical front face flash method as the thermal excitation and infrared thermography (IRT) as the monitoring sensor. In this challenging problem, the complete inverse processing of a multilayer analytical model is difficult due to the lack of sensitivity of some parameters (layer thickness, depth of thermal resistance, etc.) and the expansive computational iterative processing. For these reasons, the proposed strategy is to use a simple multilayer problem where only one resistive layer is estimated. Moreover, to simplify the inverse processing often based on iterative methods, an asymptotic development method is proposed here. Regarding the thermal signal reconstruction (TSR) methods, the drawback of these methods is the inability to be quantitative. To overcome this problem, the method incorporates a calibration process originating from the complete analytical quadrupole solution to the thermal problem. This analytical knowledge allows self-calibration of the asymptotic method. From this calibration, the quantitative thermal resistance field of a sample can be retrieved with a reasonable accuracy lower than 5%.

In this letter, a simulation procedure for airborne stripmap synthetic aperture radar with zero squint angle is proposed. The procedure is based on the idea of inverse processing and 1-D summation. It utilizes narrow bandwidth approximation and is more efficient compared to a time-domain simulator. Moreover, it allows for the simulation of raw data for higher aperture angle configurations compared to existing approaches. The effectiveness of the approach is demonstrated by means of examples for point scatterers. [ABSTRACT FROM PUBLISHER]

This article focuses on the implementation of a technique of automobile design using superelements reduced component representations as the component description. Optimisation of models using desired targets is typically performed at the system level and result from the individual component dynamic characteristics. Many different suppliers design and build components used by aerospace and automobile manufacturers. Since performance specifications, not designs, are provided to the component suppliers, system optimisation of the component designs is generally not practical. An alternative is to use a "reverse system modelling" approach to directly solve for perturbations to component characteristics that will achieve target system performance. Using the original or reduced finite element matrices as seeding matrices for the inverse process and for the development of a weighted generalise inverse, the mass matrix can be updated to reflect the target modes.

The article discusses reallocation of system mass and stiffness for achieving target specifications in automobiles. The development of a system model involves the assemblage of many important components from a dynamic standpoint. The performance of the system is dependent on the dynamic characteristics of each of the components. In an attempt to improve the overall system characteristics, targets are typically specified at the system level. Using these targets, an inverse optimisation process can be utilized to determine the adjustment of the mass and stiffness of the system. However, the inverse process will smear the mass and stiffness over all the system degrees of freedom unless all the system equations are utilized in the inverse process or unless some constraints are applied to the set of equations.