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Data from all spatial locations of nine turbulent flames in the Cambridge/Sandia swirl database are combined to study how the choice of scalar variables in conditional moment closure (CMC) type approaches affect the conditional spatial fluctuations of reactive scalars. In order to investigate the influence of swirl and stratification, two additional data-sets have been constructed. Principal component analysis (PCA) is applied to help identify the number of scalar variables and the most appropriate choices to describe the composition space. Two PCA scaling methods have been adopted, namely Pareto and Auto-scaling. Regardless of the data-set investigated and the scaling method used, the results suggest that a single principal component correlated with temperature accounted for the largest variance. For the first moment hypothesis, four progress variable, c, definitions identified by PCA are selected as conditioning variables to investigate the conditional fluctuations and normalised RMS of various species and temperature from all three databases at all axial locations. The results indicate that two control variables based on mixture fraction, Z, and progress variable significantly reduce the conditional fluctuations of scalars compared to a single variable. The selection of progress variables had minimal effects on the RMS of conditional fluctuations for all tested conditions, although a slight reduction of conditional fluctuations was found for the temperature-based progress variable, which can potentially help the further extension of CMC-based models in different flame configurations. The present study also shows that using Z and c (regardless of its definition) as two conditioning scalars enables the detachment of the thermo-chemical state from space, swirl and stratification effects. This suggests that adopting a doubly conditioned source term estimation (DCSE) approach might successfully predict the considered set of flames, assuming that ensembles are divided along the axial direction.

This study presents the first demonstration of Marshall and Hinton’s empirical correlation for laminar burning velocity (LBV) applied to iso-octane/ethanol blends. The “Oxford” correlation is first validated for neat iso-octane and ethanol combustion against the outputs of three different chemical kinetics mechanisms and experimental data from the literature. The effects of three different mixing rules, simple energy fraction, modified Le Châtelier, and modified version of the more complex mixing law of Hirasawa, on the predicted LBVs of iso-octane/ethanol blends are evaluated. The modified Le Châtelier mixing law is used with the Oxford correlation to predict blend LBVs at various temperature and pressure conditions. The results are validated against previously unpublished data for iso-octane/ethanol binary fuels at elevated temperature and pressure (up to 10 bar) both from this group, and from the earlier experimental studies of Varea et al. (CORIA) and Broustail et al. (PRISME). The Oxford correlation is shown to perform well across a wide range of temperature and pressure conditions (respectively 298–640 K and 1–10 bar) for the single component fuels. Used in conjunction with a modified Le Châtelier mixing law, the LBVs predicted by the correlation provide an excellent match to the available experimental data across the full range of ethanol concentrations examined (25, 50, and 75% v/v).

Conditional Source-term Estimation (CSE) is a combustion model based on the conditional moment hypothesis where transport equations for reactive species are conditionally averaged on conserved scalars. Major advantages of this strategy are the reduced spatial dependence of the conditional averages and negligible fluctuations around the conditional averages, which considerably simplify the reaction rate closure. Historically, simulations using CSE are limited to low carbon fuels (i.e. methane and hydrogen) where the reduced chemistry manifold can be constructed through techniques including intrinsic low dimensional manifolds and trajectory generated manifolds. However, the use of such strategies to create manifolds for diesel surrogates has proven problematic. In this study, the potential of a combination of an unsteady Flamelet Generated Manifold (FGM) and the Conditional Source-term Estimation approach to predict the ignition and flame propagation on an autoigniting n-dodecane spray flame is assessed. Simulations are performed on a single-hole injection of n-dodecane under a wide range of Engine Combustion Network’s “Spray A” conditions within a Reynolds-averaged Navier-Stokes (RANS) framework. Results from parametric sweeps of ambient temperature and oxygen concentration are qualitatively validated against experimental data from the literature and compared against predictions from an industry standard well-stirred reactor model. The efficacy of the CSE-FGM RANS approach in predicting flame characteristics is evaluated and further compared with high fidelity CSE-FGM simulations using the Large Eddy Simulation (LES) turbulence model. Overall, it was found that the CSE-FGM RANS model was able to capture global flame properties — showing particular strength in predicting auto-ignition events in the low temperature region. The model was also able to satisfactorily capture details of the two-stage ignition process. The results were shown to be consistent with those of the CSE-FGM LES model, demonstrating the adaptability of the CSE-FGM approach to different turbulence modelling paradigms.

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions. The reacting spray results are compared with simulations using a homogeneous reactor combustion model and a flamelet combustion model with the same chemical mechanism. The present study represents the first application of CSE for a diesel spray. The non-reacting liquid/vapour penetration, the mean and RMS mixture fraction, the reactive region, the flame lift-off and the ignition delay show a good agreement with literature data from an optically accessible combustion vessel over a wide range of tested conditions. The CSE-FGM model also shows a better capability in predicting the end-of-injection events in diesel spray combustion. Overall, the CSE-FGM model is shown to capture the experimental trends well, both quantitatively and qualitatively.

Aim: We investigated if the baseline value of mid-regional pro-atrial natriuretic peptide (NP), N-terminal pro-B-type NP and copeptin may be helpful in optimizing β-blocker uptitration in elderly patients with heart failure. Patients & methods: According to the biomarkers’ levels, 457 patients were divided into three subgroups and compared with each other at baseline and 3 months after. Results: All mid-regional pro-atrial NP and N-terminal pro-B-type NP subgroups had significant amelioration of left ventricle ejection fraction and New York Heart Association (NYHA) class after 3 months of β-blocker uptitration (p

Aim: To elucidate the prognostic role of procalcitonin (PCT) in patients with acute decompensated heart failure (ADHF) without clinical signs of infection at admission. Materials & Methods: Serial measurements of PCT and NT-proBNP were performed in 168 patients, aged 68 ± 10 years with ADHF followed by 3-month outcome evaluation. Results: Cox regression analysis demonstrated significant predictive value of baseline PCT for all-cause death/hospitalization (area under the curve: 0.67; p = 0.013) at 90th day. The patients with persistently elevated PCT or with an increase during the first 72 h of hospitalization had the worst prognosis (p = 0.0002). Conclusion: Baseline and serial in-hospital measurements of PCT have significant prognostic properties for 3-month all-cause mortality/hospitalization in patients with ADHF without clinical signs of infection at admission.