Premixed flames exhibit different asymptotic regimes of interaction between heat release and turbulence depending on their respective length scales. At high Karlovitz number, the dilatation caused by ...heat release does not have any relevant effect on turbulent kinetic energy with respect to non-reacting flow, while at low Karlovitz number, the mean shear is a sink of turbulent kinetic energy, and counter-gradient transport is observed. This latter phenomenon is not well captured by closure models commonly used in Large Eddy Simulations that are based on gradient diffusion. The massive amount of data available from Direct Numerical Simulation (DNS) opens the possibility to develop data-driven models able to represent physical mechanisms and non-linear features present in both these regimes. In this work, the databases are formed by DNSs of two planar hydrogen/air flames at different Karlovitz numbers corresponding to the two asymptotic regimes. In this context, the Generative Adversarial Network (GAN) gives the possibility to successfully recognize and reconstruct both gradient and counter-gradient phenomena if trained with databases where both regimes are included. Two GAN models were first trained each for a specific Karlovitz number and tested using the same dataset in order to verify the capability of the models to learn the features of a single asymptotic regime and assess its accuracy. In both cases, the GAN models were able to reconstruct the Reynolds stress subfilter scales accurately. Later, the GAN was trained with a mixture of both datasets to create a model containing physical knowledge of both combustion regimes. This model was able to reconstruct the subfilter scales for both cases capturing the interaction between heat release and turbulence closely to the DNS as shown from the turbulent kinetic budget and barycentric maps.
In this study, we combine the SPARC (Sample-Partitioning Adaptive Reduced Chemistry) and the Cell Agglomeration (CA) techniques, to accelerate the simulation of laminar and turbulent reactive flows ...with detailed kinetics. The reduced mechanisms adopted by SPARC are generated on the basis of representative thermo-chemical states corresponding to laminar, steady-state flamelets parameterized by the mixture fraction and a progress variable, in line with the TRAC (Tabulated Reactions for Adaptive Chemistry) method, recently proposed by Surapaneni and Mira (Comb and Flame, 2023). To further speed-up the calculation, CA (consisting in grouping the cells having similar thermo-chemical states) is carried out before identifying the local reduced mechanism by means of SPARC. To demonstrate the effectiveness of the approach, we considered two benchmark cases: (i) a laminar, pulsating laminar coflow diffusion flame fueled by a mixture of C2H4 and N2 burning in air; (ii) a 2D, turbulent, non-premixed flame burning n-C7H16 in air subject to decaying isotropic turbulence. In both cases, a detailed kinetic mechanism accounting for the formation of PAHs and soot particles and aggregates was considered. The results are promising, showing both accuracy and computational efficiency. While this study uses non-premixed flamelets with mixture fraction and progress variable as an illustrative example, the proposed methodology has the potential to be applied to various combustion modes, including premixed and partially premixed scenarios.
Electrofuels (e-fuels) produced from renewable electricity and carbon sources have gained significant attention in recent years as promising alternatives to fossil fuels for the transportation ...sector. However, the highly volatile e-fuels, such as short-chain oxymethylene ethers (OMEx) are prone to flash vaporization phenomena, which is associated with the formation and growth of vapor bubbles, followed by explosive bursting of the liquid jet. This phenomenon is important in many practical applications, for example, superheated liquid sprays in gasoline direct injection engines as well as cryogenic engines. The simulation of a flash boiling spray of such highly volatile liquid fuels is numerically challenging due to several reasons, including (1) the complexity of the bubble growth process in the presence of multiple vapor bubbles and (2) the need to use an extremely small time step size to accurately capture the underlying physics associated with the flash boiling process. In this paper, we first present a bubble growth model in flash boiling microdroplets considering bubble–bubble interactions along with the finite droplet size effects. A dimensional analysis of the newly derived Rayleigh–Plesset equation (RPE) with bubble–bubble interactions is then performed for Reynolds numbers of different orders of magnitude to estimate the relative importance of different forces acting on the bubble surface. Based on this analysis, a simplified nondimensional semi-analytical solution for bubble growth, which also includes the bubble–bubble interactions, is derived to estimate the bubble growth behavior with reasonable accuracy using the larger time step sizes for a wide range of operating conditions. The derived semi-analytical solution is shown to be a good approximation for describing the bubble growth rate over the whole lifetime of the bubble, thus making it useful for simulations of superheated sprays with large numbers of droplets and even more bubbles. The bubble–bubble interactions are found to have a significant impact on the bubble growth dynamics and result in delaying the onset of droplet bursting due to the slower growth of the vapor bubble compared to the bubble growth without bubble–bubble interactions. Furthermore, in a comparison with DNS results, the proposed bubble growth model is shown to reasonably capture the impact of bubble interactions leading to smaller volumetric droplet expansion.
•A novel reduced-order bubble growth model considering bubble–bubble interactions is proposed for flash boiling microdroplets.•Bubble–bubble interactions is found to slow down the bubble expansion significantly in the later bubble growth stages.•Relative importance of different forces acting on the bubble surface is highlighted.•A simplified non-dimensional semi-analytical solution for bubble growth considering bubble–bubble interactions is derived.•A posteriori analysis revealed a significant computational cost reduction with the proposed semi-analytical solution.
In the past decades, Deep Learning (DL) frameworks have demonstrated excellent performance in modeling nonlinear interactions and are a promising technique to move beyond physics-based models. In ...this context, super-resolution techniques may present an accurate approach as subfilter-scale (SFS) closure model for Large Eddy Simulations (LES) in premixed combustion. However, DL models need to perform accurately in a variety of physical regimes and generalize well beyond their training conditions. In this work, a super-resolution Generative Adversarial Network (GAN) is proposed as closure model for the unresolved subfilter-stress and scalar-flux tensors of the filtered reactive Navier–Stokes equations solved in LES. The model trained on a premixed methane/air jet flame is evaluated a-priori on similar configurations at different Reynolds and Karlovitz numbers. The GAN generalizes well at both lower and higher Reynolds numbers and outperforms existing algebraic models when the ratio between the filter size and the Kolmogorov scale is preserved. Moreover, extrapolation at a higher Karlovitz number is investigated indicating that the ratio between the filter size and the thermal flame thickness may not need to be conserved in order to achieve high correlation in terms of SFS field. Generalization studies obtained on substantially different flame conditions indicate that successful predictive abilities are demonstrated if the generalization criterion is matched. Finally, the reconstruction of a scalar quantity, different from that used during the training, is evaluated, revealing that the model is able to reconstruct scalar fields with large gradients that have not been explicitly used in the training. The a-priori investigations carried out assess whether out-of-sample predictions are even feasible in the first place, providing insights into the quantities that need to be conserved for the model to perform well between different regimes, and represent a crucial step toward future embedding into LES numerical solvers.
In global efforts to reduce harmful greenhouse gas emissions from the transportation sector, novel bio-hybrid liquid fuels from renewable energy and carbon sources can be a major form of energy for ...future propulsion systems due to their high energy density. A fundamental understanding of the spray and mixing performance of the new fuel candidates in combustion systems is necessary to design and develop the fuels for advanced combustion concepts. In the fuel design process, a large number of candidates is required to be screened to arrive at potential fuels for further detailed investigations. For such a screening process, three-dimensional (3D) simulation models are computationally too expensive and hence unfeasible. Therefore, in this paper, we present a fast, reduced-order model for inert sprays. The model is based on the cross-sectionally averaged spray (CAS) model derived by Wan (1997) from 3D multiphase equations. The original model was first tested against a wide range of conditions and different fuels. The discrepancies between the CAS model and experimental data are addressed by integrating state-of-the-art breakup and evaporation models. In addition, a transport equation for vapor mass fraction is proposed, which is important for evaporation modeling. Furthermore, the model is extended to consider polydisperse droplets by modeling the droplet size distribution by commonly used presumed probability density functions, such as Rosin–Rammler, lognormal, and gamma distributions. The improved CAS model is capable of predicting trends in the macroscopic spray characteristics for a wide range of conditions and fuels. The computational cost of the CAS model is lower than the 3D simulation methods by up to 6 orders of magnitude depending on the method. This enables the model to be used not only for the rapid screening of novel fuel candidates, but also for other applications, where reduced-order modeling is useful.
•A fast, reduced-order CAS model is presented for transient inert sprays.•Latest droplet breakup, evaporation models and vapor transport improve predictions.•Trends of spray penetration are captured for a wide range of conditions and fuels.•Information on the droplet size distribution can be obtained along the spray axis.•Computational costs are lower by orders of magnitude for CAS model vs. 3D methods.
Coralline hydroxyapatite (CHAP) is a porous, biocompatible bone-graft substitute manufactured by the Replamineform process. The use of this material in the experimental and clinical settings for ...maxillofacial onlay grafting has been recently described. This study was designed to quantitate the rate of vascularization of coralline hydroxyapatite when used in an onlay application to membranous bone in an animal model. Sixteen onlay grafts of coralline hydroxyapatite (0.5 X 0.5 X 1.0 cm Interpore 200) were placed in a subperiosteal location on the nasal dorsum of 2- to 3-kg male New Zealand white rabbits. The grafts and nasal bones were harvested en bloc at 1, 2, 3 and 4 weeks after onlay. Prior to harvest, injectable silicone visualizing agent (Microfil*) was injected by means of carotid artery cutdown. The decalcified specimens were examined on a digitizing pad to count the number of vessels appearing in the blocks of hydroxyapatite. Counting was summed and integrated by an Apple IIe microcomputer. A significant difference (p less than 0.05) was noted in both the number of vessels and the fraction of implants infiltrated by vessels between 1 and 4 weeks. The usefulness of these previously undescribed data may be in their extrapolation to onlay grafts of coralline hydroxyapatite in maxillofacial reconstruction in humans.
Fibroma of the tendon sheath is a benign lesion usually found in contact with tendon sheath or on the epitenon layer. This case report describes the intratendinous location not previously described. ...Impairment of flexor tendon excursion is relieved by longitudinal tenotomy and tumor excision.
A patient sought bilateral prophylactic mastectomies because of a strongly positive family history of breast cancer. Fortunately, prior to operation, this family history was discovered to be a ...fabrication by the patient. Few ablative plastic surgical procedures are done without objective criteria. Plastic surgeons relying on a positive family history as sufficient indication for bilateral prophylactic mastectomy need to be aware that such a history may be the contrivance of a patient with Munchausen's syndrome. A high index of suspicion may enable the plastic surgeon to recognize Munchausen's syndrome and thus avoid both contributing to the patient's illness and performing an unwarranted operation.
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