EXPERIMENTAL STUDY OF THE INLET FLOW IN A NON-PREMIXED COMBUSTION CHAMBER

The evaluation, validation and development of the models used in computation fluid dynamics requires the availability of experimental data for which the boundary conditions, especially the conditions of the inlet flow, are well defined. Laser diagnostics techniques provide experimental data used in computational fluid dynamics and are a powerful tool for measurements of the mean properties and fluctuations of the turbulent flow because they are non-intrusive methods, with high repetition rate and high spatial and temporal resolution. Therefore, in the present work an experimental study of the inlet flow (inert and combusting flows) in a non-premixed combustion chamber is presented. The velocity measurements were carried out using a laser Doppler velocimeter at the entrance region of the combustion chamber. An asymmetry on the mean flow and an increase on the total velocity fluctuations with the increase of the equivalence ratio was observed. The major effect on the increase of the equivalence ratio was a presence of a coherent movement on large scales associated to the flame brush dynamics

A STEADY PSEUDO-COMPRESSIBILITY APPROACH BASED ON UNSTRUCTURED HYBRID FINITE VOLUME TECHNIQUES APPLIED TO TURBULENT PREMIXED FLAME PROPAGATION

A pseudo-compressibility method for zero Mach number turbulent reactive flows with heat release is combined with an unstructured finite volume hybrid grid scheme. The spatial discretization is based on an overlapped cell vertex approach. An infinite freely planar flame propagating into a turbulent medium of premixed reactants is considered as a test case. The recourse to a flamelet combustion modeling for which the reaction rate is quenched in a continuous way ensures the uniqueness of the turbulent flame propagation velocity. To integrate the final form of discretized governing equations, a three-stage hybrid time-stepping scheme is used and artificial dissipation terms are added to stabilize the convergence path towards the final steady solution. The results obtained with such a numerical procedure prove to be in good agreement with those reported in the literature on the very same flow geometry. Indeed, the flame structure as well as its propagation velocity are accurately predicted thus confirming the validity of the approach followed and demonstrating that such a numerical procedure will be a valuable tool to deal with complex reactive flow geometries

Neurosymbolic Reinforcement Learning and Planning: A Survey

The area of Neurosymbolic Artificial Intelligence (Neurosymbolic AI) is rapidly developing and has become a popular research topic, encompassing sub-fields such as Neurosymbolic Deep Learning (Neurosymbolic DL) and Neurosymbolic Reinforcement Learning (Neurosymbolic RL). Compared to traditional learning methods, Neurosymbolic AI offers significant advantages by simplifying complexity and providing transparency and explainability. Reinforcement Learning(RL), a long-standing Artificial Intelligence(AI) concept that mimics human behavior using rewards and punishment, is a fundamental component of Neurosymbolic RL, a recent integration of the two fields that has yielded promising results. The aim of this paper is to contribute to the emerging field of Neurosymbolic RL by conducting a literature survey. Our evaluation focuses on the three components that constitute Neurosymbolic RL: neural, symbolic, and RL. We categorize works based on the role played by the neural and symbolic parts in RL, into three taxonomies:Learning for Reasoning, Reasoning for Learning and Learning-Reasoning. These categories are further divided into sub-categories based on their applications. Furthermore, we analyze the RL components of each research work, including the state space, action space, policy module, and RL algorithm. Additionally, we identify research opportunities and challenges in various applications within this dynamic field.Comment: 16 pages, 9 figures, IEEE Transactions on Artificial Intelligenc

Variabilidade da Freqüência Cardíaca em Pacientes com Doença de Chagas

A Doença de Chagas (DC) é uma infecçao sistêmica generalizada, normalmente crônica, cujo agente etiológico é o Tripanossoma cruzi, que parasita as células miocárdicas, lesa o sistema de conduçao e perturba o controle autonômico, levando a uma cardiomiopatia dilatada e arritmias cardíacas. A análise da variabilidade da frequência cardíaca com o domínio de tempo e de freqüência é uma forma simples e prática de avaliar a funçao autonômica. O objetivo do estudo foi a avaliaçao de pacientes com DC usando as variáveis de domínio de tempo e de frequência. Foram comparados um grupo de 81 pacientes com DC (47 na fase indeterminada, 8 do sexo masculino, idade média de 55,07 ± 10,75 anos, e 34 na crônica, 8 do sexo masculino, idade média de 57,46 ± 11,59 anos) e um grupo controle de 24 pacientes (7 do sexo masculino, idade média de 48,50 ± 13,93 anos). Obtidas as variáveis de todos os indivíduos através do Holter 24 horas (SDNN, índice de SDNN e de SDANN, rMSSD, pNN50, LF e HF), utilizou-se a análise de variância (α=5%) como teste estatístico. Para o SDNN, o índice de SDANN e o HF nao houve diferença estatística entre os grupos (p=0,01). Uma diferença estatística foi encontrada entre o grupo controle e os grupo de pacientes chagásicos (indeterminado e crônico) com relaçao ao SDANN e o LF (p=0,01). Em relaçao ao grupo controle, os chagásicos apresentaram as variáveis rMSSD e pNN50 com valores estatisticamente maiores. Usando a análise espectral, foi observada uma reduçao na capacidade da resposta simpática, bem como uma diminuiçao global da funçao autonômica observada pela reduçao do SDANN em ambos os grupos de pacientes chagásicos