274 research outputs found
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
Produção de oito genótipos de girassol cultivados em diferentes perÃodos e municÃpios da Bahia.
Variabilidade da Freqüência CardÃaca 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 cardÃacas. A análise da variabilidade da frequência cardÃaca com o domÃnio 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 domÃnio 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 indivÃduos através do Holter 24 horas (SDNN, Ãndice de SDNN e de SDANN, rMSSD, pNN50, LF e HF), utilizou-se a análise de variância (α=5%) como teste estatÃstico. Para o SDNN, o Ãndice de SDANN e o HF nao houve diferença estatÃstica entre os grupos (p=0,01). Uma diferença estatÃstica 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
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