Chapter 15
In-flight Icing: Modeling, Prediction, and
Uncertainty
B. Arizmendi, M. Morelli, G. Parma, M. Zocca, G. Quaranta,
and A. Guardone
Abstract In-flight Icing consists of the accumulation of ice over the surfaces of
flying crafts, namely aircraft and helicopters. It occurs when those fly through
visible moisture, i.e., clouds, at temperatures below the freezing point. This
phenomenon is undesirable because it compromises the safety and performance of
the flying crafts. The physics of the phenomenon is complex, and it is still behind its
full comprehension. Moreover, the characterization of the icing environments and
their replication in experimental facilities is subject to large uncertainties. These
might arise from phenomena like the complex physics of clouds, the accuracy of the
measuring devices, or the resolution to reproduce flight and cloud properties, among
others. This entails a reduction on the predictive accuracy of numerical models that
seek to reproduce ice shapes and to assess the performance of ice protection systems.
For these reasons, this research field could greatly benefit from the deployment of
Uncertainty Quantification (UQ) techniques to account from epistemic and aleatory
uncertainties in model predictions. In this chapter, an overview of the study field is
presented to motivate collaborations between practitioners of UQ and researchers of
the field. First, an overview of the physical phenomenon is introduced. Moreover,
research methodologies are described with their identified sources of uncertainty.
Next, the state-of-the-art modeling techniques are described together with their
capabilities of replication of experiments. The characteristic modeling equations
are presented as well. Finally, technologies for ice protection systems are deployed
with the current regulation for flying in icing conditions.
Keywords Aerospace engineering · In-flight icing · Uncertainty quantification ·
Numerical modeling · Ice protection systems
B. Arizmendi () · M. Morelli · G. Parma · M. Zocca · G. Quaranta · A. Guardone
Politecnico di Milano, Milano, Italy
e-mail: barbara.arizmendi@polimi.it; myles.morelli@polimi.it
© Springer Nature Switzerland AG 2021
M. Vasile (ed.), Optimization Under Uncertainty with Applications to Aerospace
Engineering, https://doi.org/10.1007/978-3-030-60166-9_15
455
In-flight Icing: Modeling, Prediction, and
Uncertainty
B. Arizmendi, M. Morelli, G. Parma, M. Zocca, G. Quaranta,
and A. Guardone
Abstract In-flight Icing consists of the accumulation of ice over the surfaces of
flying crafts, namely aircraft and helicopters. It occurs when those fly through
visible moisture, i.e., clouds, at temperatures below the freezing point. This
phenomenon is undesirable because it compromises the safety and performance of
the flying crafts. The physics of the phenomenon is complex, and it is still behind its
full comprehension. Moreover, the characterization of the icing environments and
their replication in experimental facilities is subject to large uncertainties. These
might arise from phenomena like the complex physics of clouds, the accuracy of the
measuring devices, or the resolution to reproduce flight and cloud properties, among
others. This entails a reduction on the predictive accuracy of numerical models that
seek to reproduce ice shapes and to assess the performance of ice protection systems.
For these reasons, this research field could greatly benefit from the deployment of
Uncertainty Quantification (UQ) techniques to account from epistemic and aleatory
uncertainties in model predictions. In this chapter, an overview of the study field is
presented to motivate collaborations between practitioners of UQ and researchers of
the field. First, an overview of the physical phenomenon is introduced. Moreover,
research methodologies are described with their identified sources of uncertainty.
Next, the state-of-the-art modeling techniques are described together with their
capabilities of replication of experiments. The characteristic modeling equations
are presented as well. Finally, technologies for ice protection systems are deployed
with the current regulation for flying in icing conditions.
Keywords Aerospace engineering · In-flight icing · Uncertainty quantification ·
Numerical modeling · Ice protection systems
B. Arizmendi () · M. Morelli · G. Parma · M. Zocca · G. Quaranta · A. Guardone
Politecnico di Milano, Milano, Italy
e-mail: barbara.arizmendi@polimi.it; myles.morelli@polimi.it
© Springer Nature Switzerland AG 2021
M. Vasile (ed.), Optimization Under Uncertainty with Applications to Aerospace
Engineering, https://doi.org/10.1007/978-3-030-60166-9_15
455