Numerical simulation of group combustion of pulverized coal

A mathematical model for the group combustion of pulverized coal particles was developed in a previous work. It includes the Lagrangian description of the dehumidification, devolatilization and char gasification reactions of the coal particles in the homogenized gaseous environment resulting from the three fuels, CO, H2 and volatiles, supplied by the gasification of the particles and their simultaneous group combustion by the gas phase oxidation reactions, which are considered to be very fast. This model is complemented here with an analysis of the particle dynamics, determined principally by the effects of aerodynamic drag and gravity, and its dispersion based on a stochastic model. It is also extended to include two other simpler models for the gasification of the particles: the first one for particles small enough to extinguish the surrounding diffusion flames, and a second one for particles with small ash content when the porous shell of ashes remaining after gasification of the char, non structurally stable, is disrupted. As an example of the applicability of the models, they are used in the numerical simulation of an experiment of a non-swirling pulverized coal jet with a nearly stagnant air at ambient temperature, with an initial region of interaction with a small annular methane flame. Computational algorithms for solving the different stages undergone by a coal particle during its combustion are proposed. For the partial differential equations modeling the gas phase, a second order finite element method combined with a semi-Lagrangian characteristics method are used. The results obtained with the three versions of the model are compared among them and show how the first of the simpler models fits better the experimental results.

“Coarse” stability and bifurcation analysis using time-steppers: A reaction-diffusion example

Evolutionary, pattern forming partial differential equations (PDEs) are often derived as limiting descriptions of microscopic, kinetic theory-based models of molecular processes (e.g., reaction and diffusion). The PDE dynamic behavior can be probed through direct simulation (time integration) or, more systematically, through stability/bifurcation calculations; time-stepper-based approaches, like the Recursive Projection Method [Shroff, G. M. & Keller, H. B. (1993) SIAM J. Numer. Anal. 30, 1099–1120] provide an attractive framework for the latter. We demonstrate an adaptation of this approach that allows for a direct, effective (“coarse”) bifurcation analysis of microscopic, kinetic-based models; this is illustrated through a comparative study of the FitzHugh-Nagumo PDE and of a corresponding Lattice–Boltzmann model.

Emissões de gases de efeito estufa e amônia oriundas da criação de frangos de corte em múltiplos reúsos da cama

Vários países têm buscado investigar as emissões de gases do efeito estufa (GEE) e amônia (NH3) na atividade animal para melhor compreensão da dinâmica e excesso desses gases na atmosfera. As informações disponíveis na literatura sobre as emissões de GEE e NH3 em aviários são variáveis e incertas devido à diversidade e condições particulares das instalações, bem como das inúmeras diferenças no sistema de criação e das complexas interações observadas nos dejetos dos animais. A caracterização das emissões do setor avícola normalmente é realizada por monitoramento aéreo das concentrações dos gases dentro das instalações de produção. No entanto, alguns métodos adotados são insuficientes devido às interferências de outros gases, razão por que as medições podem não refletir, com exatidão, as emissões reais. Diante dessa complexidade, nesta pesquisa buscou-se aplicar técnicas que apresentam menores interferências, bem como desenvolver um sistema de amostragem para medir diretamente as emissões de N2O, CH4 e NH3 dos dejetos de frangos de corte. No desenvolvimento do método, utilizou-se como referência o princípio da câmara estática fechada e a análise por cromatografia gasosa (CG), para estimar as emissões de GEE. Para quantificação direta das emissões de NH3, adaptou-se um método semiaberto estático, baseado na captura, em meio ácido, do NH3 volatilizado dos dejetos das aves. Adicionalmente, buscou-se monitorar as emissões diárias de NH3, CH4 e N2O dos dejetos dos frangos, considerando o típico manejo de reutilização da cama de frango. Foram propostos modelos empíricos para as predições das emissões de N2O, CH4 e NH3, em função do número de reutilizações da cama, da idade das aves e de propriedades físico-químicas da cama de frango. As emissões acumuladas por quatro ciclos de criação permitiram calcular perdas anuais de 0,14, 0,35, e 72,0 g de N2O, CH4 e NH3 ave-alojada-1 ano-1, respectivamente. Considerando o número de frangos de corte alojados em 2015, a atividade avícola emitiu cerca de 545,1 Gg CO2eq pelo manejo dos dejetos nos aviários, correspondente a 0,04 kg CO2eq por kg de carne. Reduções de 21, 40 e 78% foram observadas nas emissões anuais de N2O, CH4 e NH3, respectivamente, ao utilizar (seis ciclos) a cama somente em um ciclo de criação. Contudo, um balanço de N foi conduzido para contabilizar as entradas e saídas de N na produção de frangos de corte durante os quatro ciclos de criação avaliados. A principal entrada de N no sistema foi pela ração, como entrada secundária, o N via cama de frango, o qual aumentou consideravelmente a cada ciclo de reutilização. Considerando que esta pesquisa apresenta uma metodologia aplicável e inovadora para determinar os fluxos de GEE em galpões abertos no país, os dados serão úteis para o inventário anual brasileiro das emissões de GEE oriundas dos dejetos da avicultura de corte. Os resultados são úteis também para incentivar novas pesquisas que possam avançar no conhecimento de impactos e alternativas de mitigação de GEE na produção de frangos de corte e, adicionalmente, conferir sustentabilidade à produção de carne no Brasil

Numerical solution of the Dirichlet initial boundary value problem for the heat equation in exterior 3-dimensional domains using integral equations

A numerical method for the Dirichlet initial boundary value problem for the heat equation in the exterior and unbounded region of a smooth closed simply connected 3-dimensional domain is proposed and investigated. This method is based on a combination of a Laguerre transformation with respect to the time variable and an integral equation approach in the spatial variables. Using the Laguerre transformation in time reduces the parabolic problem to a sequence of stationary elliptic problems which are solved by a boundary layer approach giving a sequence of boundary integral equations of the first kind to solve. Under the assumption that the boundary surface of the solution domain has a one-to-one mapping onto the unit sphere, these integral equations are transformed and rewritten over this sphere. The numerical discretisation and solution are obtained by a discrete projection method involving spherical harmonic functions. Numerical results are included.

Finite-strain laminates: Bending-enhanced hexahedron and delamination

With a new finite strain anisotropic framework, we introduce a unified approach for constitutive model- ing and delamination of composites. We describe a finite-strain semi-implicit integration algorithm and the application to assumed-strain hexahedra. In a laminate composite, the laminae are modeled by an anisotropic Kirchhoff/Saint-Venant material and the interfaces are modeled by the exponential cohesive law with intrinsic characteristic length and the criterion by Benzeggagh and Kenane for the equivalent fracture toughness. For the element formulation, a weighted least-squares algorithm is used to calculate the mixed strain. Löwdin frames are used to model orthotropic materials without the added task of per- forming a polar decomposition or empirical frames. To assess the validity of our proposals and inspect step and mesh size dependence, a least-squares based hexahedral element is implemented and tested in depth in both deformation and delamination examples.

Least-squares finite strain hexahedral element/constitutive coupling based on parametrized configurations and the Löwdin frame

Two novelties are introduced: (i) a finite-strain semi-implicit integration algorithm compatible with current element technologies and (ii) the application to assumed-strain hexahedra. The Löwdin algo- rithm is adopted to obtain evolving frames applicable to finite strain anisotropy and a weighted least- squares algorithm is used to determine the mixed strain. Löwdin frames are very convenient to model anisotropic materials. Weighted least-squares circumvent the use of internal degrees-of-freedom. Het- erogeneity of element technologies introduce apparently incompatible constitutive requirements. Assumed-strain and enhanced strain elements can be either formulated in terms of the deformation gradient or the Green–Lagrange strain, many of the high-performance shell formulations are corotational and constitutive constraints (such as incompressibility, plane stress and zero normal stress in shells) also depend on specific element formulations. We propose a unified integration algorithm compatible with possibly all element technologies. To assess its validity, a least-squares based hexahedral element is implemented and tested in depth. Basic linear problems as well as 5 finite-strain examples are inspected for correctness and competitive accuracy.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

A four-stage index 2 Diagonally Implicit Runge-Kutta method

High index Differential Algebraic Equations (DAEs) force standard numerical methods to lower order. Implicit Runge-Kutta methods such as RADAU5 handle high index problems but their fully implicit structure creates significant overhead costs for large problems. Singly Diagonally Implicit Runge-Kutta (SDIRK) methods offer lower costs for integration. This paper derives a four-stage, index 2 Explicit Singly Diagonally Implicit Runge-Kutta (ESDIRK) method. By introducing an explicit first stage, the method achieves second order stage calculations. After deriving and solving appropriate order conditions., numerical examples are used to test the proposed method using fixed and variable step size implementations. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.

Explicit/implicit partitioning and a new explicit form of the generalized alpha method

Most finite element packages use the Newmark algorithm for time integration of structural dynamics. Various algorithms have been proposed to better optimize the high frequency dissipation of this algorithm. Hulbert and Chung proposed both implicit and explicit forms of the generalized alpha method. The algorithms optimize high frequency dissipation effectively, and despite recent work on algorithms that possess momentum conserving/energy dissipative properties in a non-linear context, the generalized alpha method remains an efficient way to solve many problems, especially with adaptive timestep control. However, the implicit and explicit algorithms use incompatible parameter sets and cannot be used together in a spatial partition, whereas this can be done for the Newmark algorithm, as Hughes and Liu demonstrated, and for the HHT-alpha algorithm developed from it. The present paper shows that the explicit generalized alpha method can be rewritten so that it becomes compatible with the implicit form. All four algorithmic parameters can be matched between the explicit and implicit forms. An element interface between implicit and explicit partitions can then be used, analogous to that devised by Hughes and Liu to extend the Newmark method. The stability of the explicit/implicit algorithm is examined in a linear context and found to exceed that of the explicit partition. The element partition is significantly less dissipative of intermediate frequencies than one using the HHT-alpha method. The explicit algorithm can also be rewritten so that the discrete equation of motion evaluates forces from displacements and velocities found at the predicted mid-point of a cycle. Copyright (C) 2003 John Wiley Sons, Ltd.

Numerical simulations of Lamb waves in plates using a semi-analytical finite element method

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2011

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

The prognostic value of semi-quantitative i-123 mibg scintigraphy at diagnosis in high risk neuroblastoma: validation of the siopen score method

Purpose: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.Method: Patterns of skeletal 123I mIBG uptake were assigned numerical scores (Mscore) ranging from 0 (no metastasis) to 72 (diffuse metastases) within 12 body areas as described previously. 271 anonymised, paired image data sets acquired at diagnosis and on completion of Rapid COJEC induction chemotherapy were reviewed, constituting a representative sample of 1602 children treated prospectively within the HR-NBL1/SIOPEN trial. Pre-and post-treatment Mscores were compared with bone marrow cytology (BM) and 3 year event free survival (EFS).Results: Results 224/271 patients showed skeletal MIBG-uptake at diagnosis and were evaluable forMIBG-response. Complete response (CR) on MIBG to Rapid COJEC induction was achieved by 66%, 34% and 15% of patients who had pre-treatment Mscores of <18 (n¼65, 29%), 18-44 (n¼95,42%) and Y ´ 45 (n¼64, 28.5%) respectively (chi squared test p<.0001). Mscore at diagnosis and on completion of Rapid COJEC correlated strongly with BM involvement (p<0.0001). The correlation of pre score with post scores and response was highly significant (p<0.001). Most importantly, the 3 year EFS in 47 children with Mscore 0 at diagnosis was 0.68 (A ` 0.07), by comparison with 0.42 (A` 0.06), 0.35 (A` 0.05) and 0.25 (A` 0.06) for patients in pre-treatment score groups <18, 18-44 and Y ´ 45, respectively (p<0.001). AnMscore threshold ofY ´ 45 at diagnosis was associated with significantly worse outcome by comparison with all other Mscore groups (p¼0.029). The 3 year EFS of 0.53 (A` 0.07) of patients in metastatic CR (mIBG and BM) after Rapid Cojec (33%) is clearly superior to patients not achieving metastatic CR (0.24 (A ` 0.04), p¼0.005).Conclusion: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.