Statistical Approach on Visualizing Multi-Variable Interactions in a Hybrid Breakup Model under ECN Spray Conditions

Nsikane, Daniel; Mustafa, Kenan; Ward, Andrew; Morgan, Rod; Mason, David; Heikal, Morgan

doi:10.4271/2017-24-0104

Cited by 6 publications

(15 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The usual mesh and time-step independence studies were conducted to ensure model convergence. Independence is found for a mesh size of 0.45 mm × 0.45 mm (∼1,335,096 cells) and a time step of 5e–7 s. 51 These settings can be carried over throughout the investigation. The selected sub-models are listed in Table 3.…”

Section: Numerical Setupmentioning

confidence: 96%

“…The DoE parameters, their range and phenomenological significance are collected in Table 4. Nsikane et al 51 showed how in these cases, an adjustment of C 2 was selected to achieve good results. In our more recent studies, both C 1 and C 2 are considered as DoE variables.…”

Section: Design Of Experimentsmentioning

confidence: 99%

“…Initial work towards answering the second question has been performed by Nsikane et al 51,52 The conclusions of Nsikane et al 51 suggested that a single setup to match a range of operating conditions could not be found. While this does not prove that such a setup does not exist, the employed so-called design-of-experiment (DoE) approach to statistically analyse hundreds of simulations certainly increased the confidence that targeted tuning will always be necessary.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Novel approach for adaptive coefficient tuning for the simulation of evaporating high-speed sprays injected into a high-temperature and high-pressure environment

Nsikane

Vogiatzaki

Morgan

et al. 2019

International Journal of Engine Research

View full text Add to dashboard Cite

Producing reliable in-cylinder simulations for quick-turnaround engine development for industrial purposes is a challenging task for modern computational fluid dynamics, mostly because of the tuning effort required for the sub-models used in the various frameworks (the Reynolds-averaged Navier–Stokes and large eddy simulation). Tuning is required because of the need for modern engines to operate under a wider range of conditions and fuels. In this article, we suggest a novel methodology based on automated simulation parameter optimisation that is capable of delivering a priori a coefficient matrix for each operating condition. This approach produces excellent results for multiple comparison metrics like liquid and vapour penetration lengths, radial and axial mass fraction and temperature distributions. In this article, we also show for the first time that input model coefficients can potentially be linked to ambient boundary conditions in a physically consistent manner. Changes in injection pressure, charge pressure and charge density are considered. This paves the way for the tabulation of the constants in order to eliminate lengthy tuning iterations between operating conditions and move towards adaptive simulations as the piston moves changing the in-cylinder conditions. An additional discussion is performed for the validity range of existent models given that in recent years there has been a shift towards more extreme thermodynamic conditions in the injection stage (reaching the limits of transcritical flows). Although in this work the framework was implemented in the Reynolds-averaged Navier–Stokes context because this is the tool of preference of digital engineering currently by automotive industries, the approach can be easily extended in large eddy simulation.

show abstract

Section: Numerical Setupmentioning

confidence: 96%

Section: Design Of Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Novel approach for adaptive coefficient tuning for the simulation of evaporating high-speed sprays injected into a high-temperature and high-pressure environment

Nsikane

Vogiatzaki

Morgan

et al. 2019

International Journal of Engine Research

View full text Add to dashboard Cite

show abstract

“…Simulation results within this framework rely on multiple user-defined variables which need validation to extended operating conditions to be considered predictive. Different studies have tried to enhance RANS simulations predictive capabilities by investigating input-variables sensitivity [10,11]. Run times and required resources are still unacceptable for virtual hardware screening and calibration at a powertrain system level.…”

Section: Available Solutions To Improve the Virtualmentioning

confidence: 99%

“…CFD RoHR predictions at multiple operating points for each of the engine design screened during the concept stage of development remain unpractical. This is due to the limited time available to define the first engine concept [3], limited experimental data available to tune CFD models and the lack of consensus on how modelling coefficients should be set [10,41]. CFD analysis can be used later in the development process, once the concept design is defined [8,38,39,41].…”

Section: Future Workmentioning

confidence: 99%

A process for an efficient heat release prediction at the concepts screening stage of gasoline engine development

Rota

Morgan

Mustafa

et al. 2020

International Journal of Engine Research

View full text Add to dashboard Cite

In recent years, the exploration of new combustion technologies has accelerated in response to increasingly stringent emissions regulations and fuel economy demands. Virtual engineering tools, that enable the screening of novel hardware and engine calibrations at the early stage of engine development, have become imperative to meet new emission regulations. One-dimensional engine simulations are used at the start of the design of a new engine to define the overall combustion system geometries. Later, more complex three-dimensional computational fluid dynamics calculations are coupled to one-dimensional engine system codes to optimise initial concept geometries and define a system design ready for prototyping. To provide meaningful results, one-dimensional engine system codes often use empirical-based combustion models to calculate the engine burn rate. Moreover, realistic engine burn rates responses, for the entire engine map and for different calibrations, are required to provide three-dimensional computational fluid dynamics codes with correct boundary conditions during the design optimisation phase. Thus, the burn characteristic of new non-traditional combustion solution, for which little experimental data are available, needs to be initially assumed. To improve virtual development and reduce this uncertainty, the industry’s attention shifted towards quasi-dimensional combustion models capable of providing engine burn rate predictions. Within the quasi-dimensional modelling framework, turbulence models, adding extra user-input variables, are required to capture the effect of different combustion chamber geometries on the engine combustion rate. Rigorous validation of zero-dimensional turbulence models for different engine concepts and calibrations is therefore needed to enable quasi-dimensional combustion models to predict the engine burn rate. An alternative methodology, with limited dependency on previous test data, is required to enhance the exploration of novel combustion strategies and geometric architectures. An available process, based on a quasi-dimensional combustion stochastic reactor model, a one-dimensional engine system model and non-combusting three-dimensional computational fluid dynamics calculations, was used for this work. The approach uses limited non-combusting computational fluid dynamics calculations and a previously developed scaling factor response for the stochastic reactor model turbulence input ( τSRM) to quickly predict the engine rate of heat release. In this work, the scaling factor response was assessed against two different engine variants over a variety of engine operating conditions. Moreover, the same response was used to predict the effect of different bore-to-stroke ratios on the engine combustion rate and knock tolerance. Non-combusting computational fluid dynamics and one-dimensional engine system simulations have been carried out to investigate changes in turbulence characteristics due to different engine variants and bore-to-stroke ratios. It was shown that limited number of non-combusting computational fluid dynamics runs is required to characterise the in-cylinder turbulence for each explored engine variant. The scaling factor response was used to manipulate the turbulence input ( τSRM) resulting in good engine burn rates predictions for the explored engine variants and bore-to-stroke ratios. The presented methodology showed augmented predictive capabilities and has potential to move the engine development towards a less hardware dependent virtual approach, offering a practical solution for the exploration of new engine concepts.

show abstract

Spray Breakup Modelling for Internal Combustion Engines

Sonawane

Ágarwal

2021

Energy, Environment, and Sustainability

View full text Add to dashboard Cite

Rising concerns about emissions have led to a significant tightening of pollution norms for internal combustion (IC) engines. High-pressure direct injection (HPDI) technologies have been adopted for most on-road and off-road engines to meet the global demand for clean and efficient powertrains. Higher fuel efficiency, superior combustion, and lower pollutant formation are the characteristic features of the HPDI. The introduction of alternative fuels, modified combustion geometry, and novel combustion concepts demand continuous improvement in fuel injection equipment (FIE). The complicated physics of HPDI and its modelling is an active area of research among researchers and engine developers. Fuel-injected in the combustion chamber breaks up into a spray of fine droplets, evaporating, mixing with ambient air, and forming a fuel-air mixture, greatly affecting the engine combustion and emission characteristics. Therefore, it is necessary to study the fuel breakup phenomenon under different engine conditions comprehensively. Detailed understanding of the spray breakup phenomenon is unavailable due to difficulties in optical access, highly dense sprays, complex processes, etc. However, recent advances in measurement technologies and computational tools have made it feasible for researchers. This chapter attempts to capture widely used spray breakup models and research studies involving IC engines. Fundamental spray breakup and atomization have been discussed at the beginning of the chapter. Subsequently, the basis and fundamentals of popular spray models have been discussed. Finally, the authors have comprehensively discussed the key contributions in sprays to provide an overall idea about the spray models and their application for IC engine studies. Various spray breakup models such as Blob Model, Linear Instability Sheet Atomization (LISA) Model, Kelvin-Helmholtz (KH) Model, Kelvin-Helmholtz-Aerodynamics Cavitation Turbulence (KH-ACT) Model, RT (Rayleigh-Taylor) Model, Hybrid/Modified Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) Model, Taylor Analogy Breakup (TAB) Model, Enhanced TAB breakup model (ETAB) are discussed briefly in this chapter. Towards the end, a summary of the contents of the chapter is provided, which covers highlights and significant observations.

show abstract

Statistical Approach on Visualizing Multi-Variable Interactions in a Hybrid Breakup Model under ECN Spray Conditions

Cited by 6 publications

References 19 publications

Novel approach for adaptive coefficient tuning for the simulation of evaporating high-speed sprays injected into a high-temperature and high-pressure environment

Novel approach for adaptive coefficient tuning for the simulation of evaporating high-speed sprays injected into a high-temperature and high-pressure environment

A process for an efficient heat release prediction at the concepts screening stage of gasoline engine development

Spray Breakup Modelling for Internal Combustion Engines

Contact Info

Product

Resources

About