A computational study of heat transfer, soot production and transport in an acetylene-air laminar diffusion flame in the field of a line vortex

The present work involves a computational study of soot formation and transport in case of a laminar acetylene diffusion flame perturbed by a co nvecting line vortex. The topology of the soot contours (as in an earlier experimental work [4]) have been investigated. More soot was produced when vortex was introduced from the air si de in comparison to a fuel side vortex. Also the soot topography was more diffused in case of the air side vortex. The computational model was found to be in good agreement with the ex perimental work [4]. The computational simulation enabled a study of the various parameters affecting soot transport. Temperatures were found to be higher in case of air side vortex as compared to a fuel side vortex. In case of the fuel side vortex, abundance of fuel in the vort ex core resulted in stoichiometrically rich combustion in the vortex core, and more discrete so ot topography. Overall soot production too was low. In case of the air side vortex abundan ce of air in the core resulted in higher temperatures and more soot yield. Statistical techniques like probability density fun ction, correlation coefficient and conditional probability function were introduced to explain the transient dependence of soot yield and transport on various parameters like temperature, a cetylene concentration.

A computational study of flame dynamics on soot production and transport for an acetylene-air laminar diffusion flame in the field of a convecting line vortex

The present work involves a computational study of soot formation and transport in case of a laminar acetylene diffusion flame perturbed by a convecting line vortex. The topology of the soot contours (as in an earlier experimental work [4]) have been investigated. More soot was produced when vortex was introduced from the air side in comparison to a fuel side vortex. Also the soot topography was more diffused in case of the air side vortex. The computational model was found to be in good agreement with the experimental work [4]. The computational simulation enabled a study of the various parameters affecting soot transport. Temperatures were found to be higher in case of air side vortex as compared to a fuel side vortex. In case of the fuel side vortex, abundance of fuel in the vort ex core resulted in stoichiometrically rich combustion in the vortex core, and more discrete soot topography. Overall soot production too was low. In case of the air side vortex abundance of air in the core resulted in higher temperatures and more soot yield. Statistical techniques like probability density function, correlation coefficient and conditional probability function were introduced to explain the transient dependence of soot yield and transport on various parameters like temperature, a cetylene concentration.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Ancilla-assisted quantum state tomography in multiqubit registers

The standard method of quantum state tomography (QST) relies on the measurement of a set of noncommuting observables, realized in a series of independent experiments. Ancilla-assisted QST (AAQST) proposed by Nieuwenhuizen and co-workers Phys. Rev. Lett. 92, 120402 (2004)] greatly reduces the number of independent measurements by exploiting an ancilla register in a known initial state. In suitable conditions AAQST allows mapping out density matrix of an input register in a single experiment. Here we describe methods for explicit construction of AAQST experiments in multiqubit registers. We also report nuclear magnetic resonance studies on AAQST of (i) a two-qubit input register using a one-qubit ancilla in an isotropic liquid-state system and (ii) a three-qubit input register using a two-qubit ancilla register in a partially oriented system. The experimental results confirm the effectiveness of AAQST in such multiqubit registers.

Universal flame propagation behavior in packed bed of biomass

This article aims at seeking the universal behavior of propagation rate variation with air superficial velocity (V-s) in a packed bed of a range of biomass particles in reverse downdraft mode while also resolving the differing and conflicting explanations in the literature. Toward this, measurements are made of exit gas composition, gas phase and condensed phase surface temperature (T-g and T-s), and reaction zone thickness for a number of biomass with a range of properties. Based on these data, two regimes are identified: gasificationvolatile oxidation accompanied by char reduction reactions up to 16 +/- 1cm/s of V-s and above this, and char oxidationsimultaneous char oxidation and gas phase combustion. In the gasification regime, the measured T-s is less than T-g; a surface heat balance incorporating a diffusion controlled model for flaming combustion gives and matches with the experimental results to within 5%. In the char oxidation regime, T-g and T-s are nearly equal and match with the equilibrium temperature at that equivalence ratio. Drawing from a recent study of the authors, the ash layer over the oxidizing char particle is shown to play a critical role in regulating the radiation heat transfer to fresh biomass in this regime and is shown to be crucial in explaining the observed propagation behavior. A simple model based on radiation-convection balance that tracks the temperature-time evolution of a fresh biomass particle is shown to support the universal behavior of the experimental data on reaction front propagation rate from earlier literature and the present work for biomass with ash content up to 10% and moisture fraction up to 10%. Upstream radiant heat transfer from the ash-laden hot char modulated by the air flow is shown to be the dominant feature of this model.

Nonquadratic penalization improves near-infrared diffuse optical tomography

A new approach that can easily incorporate any generic penalty function into the diffuse optical tomographic image reconstruction is introduced to show the utility of nonquadratic penalty functions. The penalty functions that were used include quadratic (l(2)), absolute (l(1)), Cauchy, and Geman-McClure. The regularization parameter in each of these cases was obtained automatically by using the generalized cross-validation method. The reconstruction results were systematically compared with each other via utilization of quantitative metrics, such as relative error and Pearson correlation. The reconstruction results indicate that, while the quadratic penalty may be able to provide better separation between two closely spaced targets, its contrast recovery capability is limited, and the sparseness promoting penalties, such as l(1), Cauchy, and Geman-McClure have better utility in reconstructing high-contrast and complex-shaped targets, with the Geman-McClure penalty being the most optimal one. (C) 2013 Optical Society of America

Efficient gradient-free simplex method for estimation of optical properties in image-guided diffuse optical tomography

Typical image-guided diffuse optical tomographic image reconstruction procedures involve reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem less ill-posed compared to traditional underdetermined cases. Still, the methods that are deployed in this case are same as those used for traditional diffuse optical image reconstruction, which involves a regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method is proposed here to perform the image reconstruction procedure and is shown to provide solutions that closely match ones obtained using established methods, even in highly noisy data. The proposed method also has the distinct advantage of being more efficient owing to being regularization free, involving only repeated forward calculations. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

An approximately H-1-optimal Petrov-Galerkin meshfree method: application to computation of scattered light for optical tomography

Nearly pollution-free solutions of the Helmholtz equation for k-values corresponding to visible light are demonstrated and verified through experimentally measured forward scattered intensity from an optical fiber. Numerically accurate solutions are, in particular, obtained through a novel reformulation of the H-1 optimal Petrov-Galerkin weak form of the Helmholtz equation. Specifically, within a globally smooth polynomial reproducing framework, the compact and smooth test functions are so designed that their normal derivatives are zero everywhere on the local boundaries of their compact supports. This circumvents the need for a priori knowledge of the true solution on the support boundary and relieves the weak form of any jump boundary terms. For numerical demonstration of the above formulation, we used a multimode optical fiber in an index matching liquid as the object. The scattered intensity and its normal derivative are computed from the scattered field obtained by solving the Helmholtz equation, using the new formulation and the conventional finite element method. By comparing the results with the experimentally measured scattered intensity, the stability of the solution through the new formulation is demonstrated and its closeness to the experimental measurements verified.

Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography

A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

Scalar transport in diffusion flame wrapped up by an air and fuel side vortex

The present work involves a computational study of soot (chosen as a scalar which is a primary pollutant source) formation and transport in a laminar acetylene diffusion flame perturbed by a convecting line vortex. The topology of soot contours resulting from flame vortex interactions has been investigated. More soot was produced when vortex was introduced from the air side in comparison to the fuel side. Also, the soot topography was spatially more diffuse in the case of air side vortex. The computational model was found to be in good agreement with the experimental work previously reported in the literature. The computational simulation enabled a study of various parameters like temperature, equivalence ratio and temperature gradient affecting the soot production and transport. Temperatures were found to be higher in the case of air side vortex in contrast to the fuel side one. In case of fuel side vortex, abundance of fuel in the vortex core resulted in fuel-rich combustion zone in the core and a more discrete soot topography. Besides, the overall soot production was observed to be low in the fuel side vortex. However, for the air side vortex, air abundance in the core resulted in higher temperatures and greater soot production. Probability density functions (PDFs) have been introduced to investigate the spatiotemporal variation of soot yield and transport and their dependence on temperature and acetylene concentration from statistical view point. In addition, the effect of flame curvature on soot production is also studied. The regions convex to fuel stream side witnessed thicker soot layer. All numerical simulations have been carried out on Fluent 6.3.26. (C) 2013 Elsevier Ltd. All rights reserved.

Scaling of turbulent flame speed for expanding flames with Markstein diffusion considerations

In this paper we clarify the role of Markstein diffusivity, which is the product of the planar laminar flame speed and the Markstein length, on the turbulent flame speed and its scaling, based on experimental measurements on constant-pressure expanding turbulent flames. Turbulent flame propagation data are presented for premixed flames of mixtures of hydrogen, methane, ethylene, n-butane, and dimethyl ether with air, in near-isotropic turbulence in a dual-chamber, fan-stirred vessel. For each individual fuel-air mixture presented in this work and the recently published iso-octane data from Leeds, normalized turbulent flame speed data of individual fuel-air mixtures approximately follow a Re-T,f(0.5) scaling, for which the average radius is the length scale and thermal diffusivity is the transport property of the turbulence Reynolds number. At a given Re-T,Re-f, it is experimentally observed that the normalized turbulent flame speed decreases with increasing Markstein number, which could be explained by considering Markstein diffusivity as the leading dissipation mechanism for the large wave number flame surface fluctuations. Consequently, by replacing thermal diffusivity with the Markstein diffusivity in the turbulence Reynolds number definition above, it is found that normalized turbulent flame speeds could be scaled by Re-T,M(0.5) irrespective of the fuel, equivalence ratio, pressure, and turbulence intensity for positive Markstein number flames.

Deconvolution-based deblurring of reconstructed images in photoacoustic/thermoacoustic tomography

Photoacoustic/thermoacoustic tomography is an emerging hybrid imaging modality combining optical/microwave imaging with ultrasound imaging. Here, a k-wave MATLAB toolbox was used to simulate various configurations of excitation pulse shape, width, transducer types, and target object sizes to see their effect on the photoacoustic/thermoacoustic signals. A numerical blood vessel phantom was also used to demonstrate the effect of various excitation pulse waveforms and pulse widths on the reconstructed images. Reconstructed images were blurred due to the broadening of the pressure waves by the excitation pulse width as well as by the limited transducer bandwidth. The blurring increases with increase in pulse width. A deconvolution approach is presented here with Tikhonov regularization to correct the photoacoustic/thermoacoustic signals, which resulted in improved reconstructed images by reducing the blurring effect. It is observed that the reconstructed images remain unaffected by change in pulse widths or pulse shapes, as well as by the limited bandwidth of the ultrasound detectors after the use of the deconvolution technique. (C) 2013 Optical Society of America

Studies on thin film based flexible gold electrode arrays for resistivity imaging in electrical impedance tomography

Practical phantoms are essential to assess the electrical impedance tomography (EIT) systems for their validation, calibration and comparison purposes. Metal surface electrodes are generally used in practical phantoms which reduce the SNR of the boundary data due to their design and development errors. Novel flexible and biocompatible gold electrode arrays of high geometric precision are proposed to improve the boundary data quality in EIT. The flexible gold electrode arrays are developed on flexible FR4 sheets using thin film technology and practical gold electrode phantoms are developed with different configurations. Injecting a constant current to the phantom boundary the surface potentials are measured by a LabVIEW based data acquisition system and the resistivity images are reconstructed in EIDORS. Boundary data profile and the resistivity images obtained from the gold electrode phantoms are compared with identical phantoms developed with stainless steel electrodes. Surface profilometry, microscopy and the impedance spectroscopy show that the gold electrode arrays are smooth, geometrically precised and less resistive. Results show that the boundary data accuracy and image quality are improved with gold electrode arrays. Results show that the diametric resistivity plot (DRP), contrast to noise ratio (CNR), percentage of contrast recovery (PCR) and coefficient of contrast (COC) of reconstructed images are improved in gold electrode phantoms. (C) 2013 Elsevier Ltd. All rights reserved.

Carbon nanotube based multifunctional flame sensor

Carbon nanotubes (CNT) due to its multifunctional characteristics has been presented as a flame sensor by combining both radiation and chemical sensitivity. Chemical functionalization enhances the sensitivity of CNT sensor toward any chemical modifications that are induced by the flame. Response of the sensor is revealed to be dependent on the measurement direction (longitudinal and transverse) as well as the radiation intensity. A nonlinear relation between the sensitivity and its distance from the source is used to calibrate the intensity of the flame. The present method allows a simpler approach for the flame detection by utilizing a calibration scheme to operate at any particular bias current and tune its sensitivity with respect to any working distance at a particular bias current. (C) 2013 Elsevier B.V. All rights reserved.

Projection Error Propagation-based Regularization (PEPR) method for resistivity reconstruction in Electrical Impedance Tomography (EIT)

A novel Projection Error Propagation-based Regularization (PEPR) method is proposed to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method defines the regularization parameter as a function of the projection error developed by difference between experimental measurements and calculated data. The regularization parameter in the reconstruction algorithm gets modified automatically according to the noise level in measured data and ill-posedness of the Hessian matrix. Resistivity imaging of practical phantoms in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm as well as with Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS) with PEPR. The effect of PEPR method is also studied with phantoms with different configurations and with different current injection methods. All the resistivity images reconstructed with PEPR method are compared with the single step regularization (STR) and Modified Levenberg Regularization (LMR) techniques. The results show that, the PEPR technique reduces the projection error and solution error in each iterations both for simulated and experimental data in both the algorithms and improves the reconstructed images with better contrast to noise ratio (CNR), percentage of contrast recovery (PCR), coefficient of contrast (COC) and diametric resistivity profile (DRP). (C) 2013 Elsevier Ltd. All rights reserved.