Evolution of spray and aerosol from respiratory releases: theoretical estimates for insight on viral transmission

By modelling the evaporation and settling of droplets emitted during respiratory releases and using previous measurements of droplet size distributions and SARS-CoV-2 viral load, estimates of the evolution of the liquid mass and the number of viral copies suspended were performed as a function of time from the release. The settling times of a droplet cloud and its suspended viral dose are significantly affected by the droplet composition. The aerosol (defined as droplets smaller than 5 μm) resulting from 30 s of continued speech has O(1 h) settling time and a viable viral dose an order-of-magnitude higher than in a short cough. The time-of-flight to reach 2 m is only a few seconds resulting in a viral dose above the minimum required for infection, implying that physical distancing in the absence of ventilation is not sufficient to provide safety for long exposure times. The suspended aerosol emitted by continuous speaking for 1 h in a poorly ventilated room gives 0.1–11% infection risk for initial viral loads of 108–1010 copies ml−ll, respectively, decreasing to 0.03–3% for 10 air changes per hour by ventilation. The present results provide quantitative estimates useful for the development of physical distancing and ventilation controls

Predicting Soot Emissions with Advanced Turbulent Reacting Flow Modelling

Soot is carbonaceous particulate matter formed due to the incomplete combustion of hydrocarbon fuels. The prediction of soot emissions is crucial if next-generation combustion devices are to mitigate the deleterious effects of particulate matter on human health and the environment. Theories for the distribution of size and shape of soot particles in turbulent reacting flows are required, not only for accurate predictions related to flame characteristics but also to meet increasingly stringent regulations. Over the last decades, advances in the understanding of key processes controlling soot formation and oxidation have led to the development of models that can replicate soot emissions and size in laminar flames, sometimes even at a quantitative level. However, predictions in turbulent flames still lack behind due to uncertainties in the intricate coupling between kinetics, aerosol dynamics and turbulence, and the wide range of scales that have to be simulated. There is a clear need to explore the fundamentals of soot evolution in turbulent conditions and develop effective methodologies to predict the soot particle size distribution (PSD) accurately and rapidly. This thesis presents a step in this direction for flames in geometrical configurations of high relevance to aviation combustors. In the first part of the thesis, a comprehensive modelling strategy is proposed using a detailed physicochemical sectional soot model coupled with the Conditional Moment Closure (CMC) turbulent combustion model and Large Eddy Simulation (LES). This modelling approach allows for an elaborate description of the unsteady reacting field and explicitly accounts for transport, history and finite-rate chemistry effects on soot precursors and the PSD. The soot PSD evolution is investigated first in simplified configurations followed by detailed simulations of a canonical turbulent jet flame. The results are analysed to reveal the hierarchy of reaction pathways during soot formation and oxidation and demonstrate the effects of residence time, micromixing and differential diffusion of soot particles. These analyses are necessary to understand the sooting flame structure and act as preparatory investigations for the rest of the thesis. In the second part, a lab-scale swirl flame with addition of dilution air is simulated to explore soot PSD evolution in a Rich-Quench-Lean (RQL) burner configuration widely used in practice for emissions control. Results show a reasonably good agreement with experiments for the mean reaction zone and soot locations and their variations with different airflow provided in the burner primary and dilution regions. The predicted PSDs at the burner exit are fairly well captured for a high-dilution condition but show too few and too small particles for a dilution-free condition, which may be due to an over-prediction of the oxidation rates or the underlying assumptions for particle transport. The results are then used to indicate how dilution air modifies the soot PSD within the primary zone. The method is shown to reproduce the known sensitivity of soot and its precursors on history and scalar dissipation rate effects, a prerequisite for reliable predictions. As a result, it offers a framework for accurately capturing soot PSD in realistic combustion devices. In the third part of the thesis, a new approach based on Incompletely Stirred Reactor Network (ISRN) modelling is presented. The aim is to develop an emissions screening tool that can be utilised during the design phase of combustors. ISRN modelling simplifies calculations so that parametric studies with very complex chemistry and soot models can be performed, or a large number of geometries can be explored, all at a modest computational cost. The approach shares similarities with reactor network and compartmental modelling methods from chemical engineering but offers elaborate molecular mixing and transport treatment. It relies on a network of incompletely stirred reactors, which are inhomogeneous in terms of the flow and mixing fields but characterised by homogeneous conditional averages, with the conditioning performed on the mixture fraction. The ISRN approach is demonstrated on an ethylene model RQL combustor and a single sector lean-burn model combustor operating on Jet-A1 fuel in pilot-only mode, showing very good accuracy in reproducing the mean reaction zone as revealed by LES-CMC or experiments. It is then found that reasonable accuracy can be produced for soot emissions at a significantly reduced computational cost, further enabling the use of multiple chemical mechanisms and soot models and provide estimates of the soot PSD. Finally, a new framework for analysing turbulent non-premixed flames and history effects on soot evolution is presented. The framework is formulated based on the concept of conditional particle age, denoting the total time the mixture or particles have spent at a particular mixture fraction, and conditional thermal age, which allows for a quantification of time-temperature history. Without the need for strong modelling assumptions, governing equations for the two age types are derived that can be used both in the CMC or ISRN context. The approach is then demonstrated on a simple 1D configuration and an ISRN computation of a model RQL combustor. The findings suggest that the concept of conditional age has excellent potential for estimating particle surface reactivity and develop age-dependent closure for soot surface growth and oxidation

Incompletely Stirred Reactor Network Modeling of a Model Gas Turbine Combustor

In this paper, we address the problem of answering continuous route planning queries over a road network, in the presence of updates to the delay (cost) estimates of links. A simple approach to this problem would be to recompute the best path for all queries on arrival of every delay update. However, such a naive approach scales poorly when there are many users who have requested routes in the system. Instead, we propose two new classes of approximate techniques – K-paths and proximity measures to substantially speed up processing of the set of designated routes specified by continuous route planning queries in the face of incoming traffic delay updates. Our techniques work through a combination of precomputation of likely good paths and by avoiding complete recalculations on every delay update, instead only sending the user new routes when delays change significantly. Based on an experimental evaluation with 7,000 drives from real taxi cabs, we found that the routes delivered by our techniques are within 5% of the best shortest path and have run times an order of magnitude or less compared to a naive approach

Stochastic low-order modelling of hydrogen autoignition in a turbulent non-premixed flow

Autoignition risk in initially non-premixed flowing systems, such as premixing ducts, must be assessed to help the development of low-NOx systems and hydrogen combustors. Such situations may involve randomly fluctuating inlet conditions that are challenging to model in conventional mixture-fraction-based approaches. A modelling strategy is presented here featuring a joint CFD and surrogate modelling for fast and accurate prediction of the stochastic autoignition behaviour in an experiment with continuous hydrogen flow in a hot air turbulent co-flow. The variability of three input parameters, i.e., inlet fuel and air temperatures and average wall temperature, is first sampled via a space-filling design. For each sampled set of conditions, the CFD modelling of the flame is performed via the Incompletely Stirred Reactor Network (ISRN) approach, which solves the reacting flow governing equations in post-processing on top of an LES of the inert hydrogen plume. An accurate surrogate model, namely a Gaussian Process, is then trained on the ISRN simulations of the burner, and the final quantification of the variability of autoignition locations is achieved by querying the surrogate model via Monte Carlo sampling of the random input quantities. The results are in agreement with the observed statistics of the autoignition locations. The methodology adopted in this work can be used effectively to quantify the impact of fluctuations and assist the design of practical combustion systems.EU, Grant Agreement No 952181, project "COEC

Numerical investigation of flame structure and soot formation in a lab-scale rich-quench-lean burner

The understanding of the processes involved in soot formation and oxidation is a critical factor for a reliable prediction of emissions in aero-engines, particularly as legislation becomes increasingly stringent. This work studies the flame structure and soot formation in a lab-scale burner, which reproduces the main features of a Rich-Quench-Lean (RQL) combustor, using high-fidelity numerical simulations. The investigated burner, developed at the University of Cambridge, is based on a bluff-body swirl-stabilised ethylene flame, with air provided in the primary region through two concentric swirling flows and quenching enabled by means of four dilution jets at variable distance downstream. Measurements for different air split between the two inlet swirling flows and dilution ports, and different height of the dilution jets, indicate noticeable differences in the soot tendency. Numerical simulations have been performed using Large-Eddy Simulation with the Conditional Moment Closure combustion model and a two-equation model for soot, allowing a detailed resolution of the mixing field and to directly take into account the effect of turbulent transport on the flame structure, which has been shown to have an important effect on the soot formation and evolution. The main objective of this work is to study the flow field and mixing characteristics in the burner's primary region, in order to improve the understanding of the mechanisms leading to the soot behaviour observed in the experiment at different operating conditions. Results show the key role of mixing in determining the level of soot in the burner, with the soot production mainly related to the extension of the flame zone characterized by a rich mixture, with pyrolysis products and soot precursors. The presence of additional dilution air seems to improve the oxidation and leads to a leaner mixture in the primary combustion region whereas the air added through the outer swirl stream seems to have less impact on the mixture formation in the primary region. Analysis of the solution in mixture fraction space shows the importance of residence time for the soot formation and highlights the existence of a range of values of mixture fraction, between 0.1 and 0.2, where the soot production terms are maximum. High residence times and local air-to-fuel ratio in the range of high soot production should be avoided to decrease the level of soot mass fraction in the burner

Hydrogen Combustion in Gas Turbines

The development of gas turbines using 100% hydrogen as fuel is an important step towards the development of new energy and propulsion technologies using zero carbon fuels. This chapter reviews some elements of combustion science and engineering that can help with these developments. Stable and low-NOx hydrogen combustors face significant challenges. Stabilisation of the flame at the right location without autoignition or flashback, with low NOx production, and without any thermoacoustic oscillations is important to achieve. Some new combustor architectures addressing these requirements are reviewed. The importance of mixing history is emphasised and some novel tools that can be used for assessing the effects of mixing on NOx are discussed

Personalized displacement ventilation as an energy-efficient solution for airborne disease transmission control in offices

Peer reviewed: TrueThere is evidence to suggest that airborne droplets play an important role in the transmission of respiratory diseases. The highest risk of exposure to these pathogens is in indoor environments, where airflow control has been recognized as one of the most effective engineering means to combat its spread. However, this can contribute to a significant increase in energy costs, as conventional ventilation is often not designed to remove contaminants efficiently. In this study, Computational Fluid Dynamics simulations were used to analyze how a novel ventilation approach, called Personalized Displacement Ventilation (PerDiVent), can simultaneously reduce both pathogenic airborne transmission and reduce energy costs in an open office. In addition, thermal comfort and noise were investigated to assess the practicality of the concept. PerDiVent was found to reduce the risk of cross infection by a factor of 1.08–2.0 compared to mixing ventilation in the worst and best case scenarios analyzed, and lead to savings in mechanical power of at least 30%. Furthermore, there is great potential to further improve the system and to increase the stated numbers substantially with relatively simple alterations to the design. Tools that can be used to great advantage for such optimization are also proposed in this work. These include a simple integral model and analytical metrics to estimate the reduction in cross-infection risk and energy savings as a function of PerDiVent’s effectiveness in removing contaminants. Finally, the system has a modular and highly flexible arrangement, which makes it suitable for retrofitting purposes in various indoor environments and integration with current ventilation systems. The concept shows great promise for the future, where ventilation is required to create healthier and more sustainable environments.</jats:p

A Numerical Study of Soot Evolution In A Lab-Scale Rich-Quench-Lean Burner

Soot evolution in an ethylene lab-scale burner using the Rich-Quench-Lean (RQL) concept is investigated using Large-Eddy Simulation (LES) with the Conditional Moment Closure (CMC) method and a two-equation soot model. Three operating conditions are being analysed by varying the airflow provided in the burner's primary region and the dilution region while keeping the global equivalence ratio constant. The main objective is to study the effects of flame structure and residence time on soot evolution in a burner which reproduces the main features of the RQL concept. Results show the key differences in mixing field and soot tendency between the various operating conditions. A Lagrangian particle tracking analysis and evaluation of the solution in mixture fraction space highlight the significance of history effects and scalar dissipation rate on soot evolution, which should be taken into consideration for the design of next-generation low-emission aero-engines utilising the RQL concept