Performance evaluation of a portable laser-induced fluorescence spectroscopy system for the assessment of the humification degree of the soil organic matter.

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Mast Cells and Gastrointestinal Dysmotility in the Cystic Fibrosis Mouse

BACKGROUND: Cystic fibrosis (CF) has many effects on the gastrointestinal tract and a common problem in this disease is poor nutrition. In the CF mouse there is an innate immune response with a large influx of mast cells into the muscularis externa of the small intestine and gastrointestinal dysmotility. The aim of this study was to evaluate the potential role of mast cells in gastrointestinal dysmotility using the CF mouse (Cftr(tm1UNC), Cftr knockout). METHODOLOGY: Wild type (WT) and CF mice were treated for 3 weeks with mast cell stabilizing drugs (ketotifen, cromolyn, doxantrazole) or were treated acutely with a mast cell activator (compound 48/80). Gastrointestinal transit was measured using gavage of a fluorescent tracer. RESULTS: In CF mice gastric emptying at 20 min post-gavage did not differ from WT, but was significantly less than in WT at 90 min post-gavage. Gastric emptying was significantly increased in WT mice by doxantrazole, but none of the mast cell stabilizers had any significant effect on gastric emptying in CF mice. Mast cell activation significantly enhanced gastric emptying in WT mice but not in CF mice. Small intestinal transit was significantly less in CF mice as compared to WT. Of the mast cell stabilizers, only doxantrazole significantly affected small intestinal transit in WT mice and none had any effect in CF mice. Mast cell activation resulted in a small but significant increase in small intestinal transit in CF mice but not WT mice. CONCLUSIONS: The results indicate that mast cells are not involved in gastrointestinal dysmotility but their activation can stimulate small intestinal transit in cystic fibrosis

Epistemic uncertainties in RANS model free coefficients

International audienceThe epistemic uncertainty in the free coefficients of two popular Reynolds-averaged Navier–Stokes (RANS) eddy-viscosity turbulence models is quantified. In particular, the Launder–Sharma low-Reynolds K-εK-ε and the Menter K-ωK-ω SST models are considered. The free coefficients present in turbulence models are retrieved from some properties of benchmark turbulent flows, viz. the energy power law exponent for decaying homogeneous isotropic turbulence, the value of the Von Karman constant, the turbulence production over dissipation rate estimated in the asymptotic regime of a homogeneous shear flow and the dimensionless turbulent kinetic energy in the logarithmic layer. The values presented in literature for these quantities, obtained from experiments or direct numerical simulations (DNS), show a significant dispersion, indicating the presence of an epistemic uncertainty. Starting from the data collected in literature, realistic continuous probability density functions of the basic flow properties, and hence of the RANS model coefficients, are obtained through generalized Polynomial Chaos (gPC). The impact of this uncertainty on the results of RANS simulations of the turbulent channel flow is then investigated for different Reynolds numbers through comparison with DNS data. The solution over the continuous multi-dimensional uncertainty space of the considered random variables is reconstructed through the application of a surrogate model (response surface) obtained by means of gPC. In general, the predictions of the K-ωK-ω SST model are less sensitive to the uncertainty in the model parameters than those of the low-Reynolds K-εK-ε model. For both models and for any combination of the coefficients, the predictions of the turbulent kinetic energy profile are not satisfactory, while low errors can be obtained for friction and mean velocity. Evaluation of optimal values of free parameters is a Data Assimilation (DA) problem. An example of the use of the gPC response surface for an efficient calibration of the model coefficients in order to minimize the error in the prediction of these two last variables is provided. The result accuracy estimated through the gPC surrogate model well agrees with that obtained in deterministic simulations carried out with the calibrated values of the model constants

Quantification of epistemic uncertainties in RANS turbulence models and coefficient calibration via data assimilation

International audienceno abstrac

Bulletin of the American Physical Society

International audienceno abstrac

Reliability of Large-Eddy Simulations: Benchmarking and Uncertainty Quantification

Nowadays, large-eddy simulation (LES) is increasingly applied to complex flow configurations of interest in technological or environmental applications