# Contrail aging simulation of a supersonic aircraft

Mathieu Muller, Etienne Terrenoire, Younes Bouhafid, Nicolas Bonne

► To cite this version:

Mathieu Muller, Etienne Terrenoire, Younes Bouhafid, Nicolas Bonne. Contrail aging simulation of a supersonic aircraft. EGU 2024, Apr 2024, Vienne, Austria., 2024, 10.5194/egusphere-egu24-9776. [https://hal.science/hal-04614634](https://hal.science/hal-04614634)

HAL Id: hal-04614634

https://hal.science/hal-04614634

Submitted on 17 Jun 2024

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<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Contrail aging simulation of a supersonic aircraft

Mathieu Muller, Etienne Terrenoire, Younes Bouhafid, Nicolas Bonne

► To cite this version:

Mathieu Muller, Etienne Terrenoire, Younes Bouhafid, Nicolas Bonne. Contrail aging simulation of a supersonic aircraft. EGU 2024, Apr 2024, Vienne, Austria., 2024, 10.5194/egusphere-egu24-9776. hal-04614634

HAL Id: hal-04614634

https://hal.science/hal-04614634v1

Submitted on 17 Jun 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>
<figure><img src="image_2.png" /></figure>

# Contrail aging simulation of a supersonic aircraft

Muller Mathieu* (mathieu.muller@onera.fr), Terrenoire Etienne*, Bouhafid Younes*, Bonne Nicolas* (*ONERA, DMPE Université Paris-Saclay, Palaiseau, France)

## Context

SENECA project ("noiSe and EmissioNs of supErsoniC Aircraft") aims at:

* developing supersonic aircrafts;

* investigating the impact of specifical supersonic engine technologies on the aircraft performance and noise;

* quantifying a range of climate impacts of supersonic aviation.

## Objectives

* Model and characterize the contrails due to supersonic aircraft during cruise

* Provide data to climatologists to calculate their global impact

<figure><img src="image_3.png" /></figure>

Classification of aircraft wake evolution into four regimes [1] following a tracer exhaust emitted at t = 0 from the nozzle exit.

## References

[1] Saulgeot, P., Contributions à la compréhension de la formation et de l'atténuation possible des traînées de condensation de l'aviation. Mécanique des fluides [phyiscs.class-ph]. Ecole Polytechnique, 2023. Français. NNT: 2023IPPAX143. tel-04432088

[2] Kärcher, B., Hirschberg, M., Fabian P. Small-scale chemical evolution of aircraft exhaust species at cruising, *J. Geophys. Res.*, vol. 101, 1996

[3] Khou, J-C., Ghedaïfi, W., Vancassel, X., Garnier, F. Spatial Simulation of Contrail Formation in Near-Field of Commercial Aircraft, *J. Aircraft*, vol. 52, pp. 1927-1938, 2015

[4] Muller, M., Terrenoire, E. Near-field mesh adaptation for contrail modeling of a supersonic aircraft, in 57th 3AF International Conference on Applied Aerodynamics, Bordeaux - France, 29 - 31 March 2023

[5] Fahey, D., Keim, E.R., Boering, K.A., Brock, C., Wilson, J., Jonsson, H., Anthony, S., Hanisco, T. F., Wennberg, P. Emission Measurements of the Concorde Supersonic Aircraft in the Lower Stratosphere, *Science*, vol. 270, pp. 70-74, 1995

[6] Pueschel, R. F., Boering, K. A., Verma, S., Howard, S. D., Ferry, G. V., Goodman, J., Allen, D. A., Hamill, P. Soot aerosol in the lower stratosphere: Pole-to-pole variability and contributions by aircraft, *Journal of Geophysical Research*, vol. 102, no. D11, pp. 13,113-13,118, 1997

[7] Bouhafid, Y., Bonne, N., Jacquin, L. Combined Reynolds-averaged Navier-Stokes/Large-Eddy Simulations for an Aircraft Wake until Dissipation Regime. *Aerospace Science and Technology* [under review process]

## Jet regime modeling

### CFD RANS Modeling

* CEDRE/CHARME aerodynamic modeling

* K-ω turbulent model (SST Menter)

<figure><img src="image_4.png" /></figure>

CAD of E19 Aeolus bizjet
(Cranfield University)

* Gas-phase chemistry[2]

* Microphysics model[3]

<figure><img src="image_5.png" /></figure>

Streamlines behind the E19 bizjet colored by origin: orange for the engine exit and blue for wing

### Mesh adaptation procedure (INRIA Tool)

* Variable used to refine the mesh: $V_t = \sqrt{\sum_j (V_j - V_{j,a})^2 + \max(|K - K_a|, K_a)}$

* Mesh adaptation illustration[4]

* 4 criteria to check the mesh quality:

<figure><img src="image_6.png" /></figure>

Evolution of mesh through adaptation process (slices behind the aircraft)

<figure><img src="image_7.png" /></figure>

Circulation versus normalized distance behind the aircraft

<figure><img src="image_8.png" /></figure>

Vortex radius versus normalized distance behind the aircraft for the latest mesh

<figure><img src="image_9.png" /></figure>

Position of the vortex center versus time for the latest mesh

<figure><img src="image_10.png" /></figure>

$R_3$ criterion versus normalized distance behind the aircraft for the latest mesh

### Parametric study

* Tropical conditions in lower stratosphere: $P_a = 9750$ Pa, $T_a = 196$ K

* Ice SuperSaturated Region (ISSR): $RH_{ice} = 100\%$, $X_{H_2O} = 8$ ppmv

Emission soot parameters

<table><thead><tr><th>Case</th><th>r<sub>s</sub> [nm]</th><th>ρ [kg/m<sup>3</sup>]</th><th>N<sub>s</sub> [#/m<sup>3</sup>]</th></tr></thead><tbody><tr><td>Fahey et al. [5]</td><td>9</td><td>900</td><td>4.76 10<sup>14</sup></td></tr><tr><td>Pueschel et al. [6]</td><td>90</td><td>1600</td><td>2.68 10<sup>11</sup></td></tr></tbody></table>

<figure><img src="image_11.png" /></figure>

Mean values of difference between the partial pressure of water and the saturation pressure over ice versus physical time behind the aircraft

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

Mean values of difference between the partial pressure of water and the saturation pressure over ice versus physical time behind the aircraft

## Vortex and Dissipation regime modeling

### CFD LES Methodology[7]

* CEDRE/CHARME aerodynamic modeling

* Smagorinsky model

* Microphysics model[3]

* 120 s contrail aging simulated

* Characteristic vortex descent time:

$$t_{\text{descent}} = \frac{B_0}{V_{\text{descent}}} = 2.1 \text{ s}$$

* LES initialization in 5 steps:

1. Slice extraction from RANS simulation

2. LES mesh creation

3. Interpolation RANS => LES

4. Adding fluctuations

5. Adding atmospheric stratification

### CFD LES Simulation

<figure><img src="image_16.png" /></figure>

Evolution of the contrail shape and the Q isoline with data from Fahey et al. versus time: 0 s, 3 s, 15 s, 30 s and 60 s

Evolution of the contrail shape and the Q isoline with data from Pueschel et al. versus time: 0 s, 3 s, 15 s, 30 s and 60 s

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

Ice particle number distribution versus ice diameter bins for the cases with data from Fahey et al. (left) and from Pueschel et al. (right)

<figure><img src="image_19.png" /></figure>

Evolution of the mean ice water content inside the contrail for both cases

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

Contrail relative volume distribution versus ice water content bins for the cases with data from Fahey et al. (left) and from Pueschel et al. (right)

<figure><img src="image_22.png" /></figure>

Evolution of the ice mass inside the contrail for both cases
<figure><img src="image_2.png" /></figure>

# Contrail aging simulation of a supersonic aircraft

Muller Mathieu* (mathieu.muller@onera.fr), Terrenoire Etienne*, Bouhafid Younes*, Bonne Nicolas* (*ONERA, DMPE Université Paris-Saclay, Palaiseau, France)

## Context

SENECA project ("noiSe and EmissioNs of supErsoniC Aircraft") aims at:

* developing supersonic aircrafts;

* investigating the impact of specifical supersonic engine technologies on the aircraft performance and noise;

* quantifying a range of climate impacts of supersonic aviation.

## Objectives

* Model and characterize the contrails due to supersonic aircraft during cruise

* Provide data to climatologists to calculate their global impact

<figure><img src="image_3.png" /></figure>

Classification of aircraft wake evolution into four regimes [1] following a tracer exhaust emitted at t = 0 from the nozzle exit.

## References

[1] Saulgeot, P., Contributions à la compréhension de la formation et de l'atténuation possible des traînées de condensation de l'aviation. Mécanique des fluides [phyiscs.class-ph]. Ecole Polytechnique, 2023. Français. NNT: 2023IPPAX143. tel-04432088

[2] Kärcher, B., Hirschberg, M., Fabian P. Small-scale chemical evolution of aircraft exhaust species at cruising, *J. Geophys. Res*, vol. 101, 1996

[3] Khou, J-C., Ghedaïfi, W., Vancassel, X., Garnier, F. Spatial Simulation of Contrail Formation in Near-Field of Commercial Aircraft, *J. Aircraft*, vol. 52, pp. 1927-1938, 2015

[4] Muller, M., Terrenoire, E. Near-field mesh adaptation for contrail modeling of a supersonic aircraft, in 57th 3AF International Conference on Applied Aerodynamics, Bordeaux - France, 29 - 31 March 2023

[5] Fahey, D., Keim, E.R., Boering, K.A., Brock, C., Wilson, J., Jonsson, H., Anthony, S., Hanisco, T. F., Wennberg, P. Emission Measurements of the Concorde Supersonic Aircraft in the Lower Stratosphere, *Science*, vol. 270, pp. 70-74, 1995

[6] Pueschel, R. F., Boering, K. A., Verma, S., Howard, S. D., Ferry, G. V., Goodman, J., Allen, D. A., Hamill, P. Soot aerosol in the lower stratosphere: Pole-to-pole variability and contributions by aircraft, *Journal of Geophysical Research*, vol. 102, no. D11, pp. 13,113-13,118, 1997

[7] Bouhafid, Y., Bonne, N., Jacquin, L. Combined Reynolds-averaged Navier-Stokes/Large-Eddy Simulations for an Aircraft Wake until Dissipation Regime. *Aerospace Science and Technology* [under review process]

## Jet regime modeling

### CFD RANS Modeling

* CEDRE/CHARME aerodynamic modeling

* K-ω turbulent model (SST Menter)

<figure><img src="image_4.png" /></figure>

CAD of E19 Aeolus bizjet
(Cranfield University)

* Gas-phase chemistry[2]

* Microphysics model[3]

<figure><img src="image_5.png" /></figure>

Streamlines behind the E19 bizjet colored by origin: orange for the engine exit and blue for wing

### Mesh adaptation procedure (INRIA Tool)

* Variable used to refine the mesh: $V_t = \sqrt{\sum_j(V_j - V_{j,a})^2 + \max(|K - K_a|, K_a)}$

* Mesh adaptation illustration[4]

<figure><img src="image_6.png" /></figure>

Evolution of mesh through adaptation process (slices behind the aircraft)

* 4 criteria to check the mesh quality:

<figure><img src="image_7.png" /></figure>

Circulation versus normalized distance behind the aircraft

<figure><img src="image_8.png" /></figure>

Position of the vortex center versus time for the latest mesh

<figure><img src="image_9.png" /></figure>

Vortex radius versus normalized distance behind the aircraft for the latest mesh

<figure><img src="image_10.png" /></figure>

$R_3$ criterion versus normalized distance behind the aircraft for the latest mesh

### Parametric study

* Tropical conditions in lower stratosphere: $P_a = 9750$ Pa, $T_a = 196$ K

* Ice SuperSaturated Region (ISSR): $RH_{ice} = 100\%$, $X_{H_2O} = 8$ ppmv

Emission soot parameters

<table><thead><tr><th>Case</th><th>r<sub>s</sub> [nm]</th><th>ρ [kg/m<sup>3</sup>]</th><th>N<sub>s</sub> [#/m<sup>3</sup>]</th></tr></thead><tbody><tr><td>Fahey et al. [5]</td><td>9</td><td>900</td><td>4.76 10<sup>14</sup></td></tr><tr><td>Pueschel et al. [6]</td><td>90</td><td>1600</td><td>2.68 10<sup>11</sup></td></tr></tbody></table>

<figure><img src="image_11.png" /></figure>

Mean values of difference between the partial pressure of water and the saturation pressure over ice versus physical time behind the aircraft

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

Mean values of difference between the partial pressure of water and the saturation pressure over ice versus physical time behind the aircraft

## Vortex and Dissipation regime modeling

### CFD LES Methodology[7]

* CEDRE/CHARME aerodynamic modeling

* Smagorinsky model

* Microphysics model[3]

* 120 s contrail aging simulated

* Characteristic vortex descent time:

$$t_{\text{descent}} = \frac{B_0}{V_{\text{descent}}} = 2.1 \text{ s}$$

* LES initialization in 5 steps:

1. Slice extraction from RANS simulation

2. LES mesh creation

3. Interpolation RANS => LES

4. Adding fluctuations

5. Adding atmospheric stratification

### CFD LES Simulation

<figure><img src="image_16.png" /></figure>

Evolution of the contrail shape and the Q isoline with data from Fahey et al. versus time: 0 s, 3 s, 15 s, 30 s and 60 s

Evolution of the contrail shape and the Q isoline with data from Pueschel et al. versus time: 0 s, 3 s, 15 s, 30 s and 60 s

<figure><img src="image_17.png" /></figure>

Ice particle number distribution versus ice diameter bins for the cases with data from Fahey et al. (left) and from Pueschel et al. (right)

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

Evolution of the mean ice water content inside the contrail for both cases

<figure><img src="image_20.png" /></figure>

Contrail relative volume distribution versus ice water content bins for the cases with data from Fahey et al. (left) and from Pueschel et al. (right)

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

Evolution of the ice mass inside the contrail for both cases