Ice Crystal Shed Prediction in Turbomachinery Using Accretion Laser Scans and Subsurface Thermal Data

Accurate prediction of shedding in ice crystal icing (ICI) in turbomachinery remains a challenge, particularly due to limitations of current 3D numerical accretion models in capturing realistic shapes and sub-surface conditions. This study presents an experimentally grounded approach to assess shed potential using laser-scanned ice accretion geometries and time-resolved wall thermal data. Experiments were conducted using a vaned test article exposed to ice crystal conditions at the NRC's ICE-MACR facility, for inlet temperatures in the range T_0,in = [-6.0, -2.0] degC. End-of-test freeze-out accretions were recorded using a handheld laser scanner. Despite occlusions from vanes and accumulated ice along the line of sight, usable ice accretion profiles were extracted without the need for scan repair. Cases with warmer inlet temperatures exhibit larger ice accretions, with circumferentially averaged blockage up to 3.16 times the dry vaned baseline. A vaneless reference case exhibits only light frosting under the same conditions. The scanned accretions are used in conjunction with experimental wall thermal histories to identify regions of shedding by advancing thermal boundary conditions and resolving the likely impact on subsurface water films. This hybrid experimental–numerical approach offers a robust framework for informing future shed models with realistic thermal boundary conditions and accretion geometries.

Authors

Institutions

Publication Details

Published
2025-07-16
DOI
https://doi.org/10.2514/6.2025-3856
Primary Topic
Icing and De-icing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ice Crystal Shed Prediction in Turbomachinery Using Accretion Laser Scans and Subsurface Thermal Data

Natan Zawadzki, Matthew McGilvray, David R. H. Gillespie, Thomas J. Cross
Icing and De-icing Technologies
article

Ice Crystal Shed Prediction in Turbomachinery Using Accretion Laser Scans and Subsurface Thermal Data

Natan Zawadzki, Matthew McGilvray, David R. H. Gillespie, Thomas J. Cross
article en

Abstract

Accurate prediction of shedding in ice crystal icing (ICI) in turbomachinery remains a challenge, particularly due to limitations of current 3D numerical accretion models in capturing realistic shapes and sub-surface conditions. This study presents an experimentally grounded approach to assess shed potential using laser-scanned ice accretion geometries and time-resolved wall thermal data. Experiments were conducted using a vaned test article exposed to ice crystal conditions at the NRC's ICE-MACR facility, for inlet temperatures in the range T_0,in = [-6.0, -2.0] degC. End-of-test freeze-out accretions were recorded using a handheld laser scanner. Despite occlusions from vanes and accumulated ice along the line of sight, usable ice accretion profiles were extracted without the need for scan repair. Cases with warmer inlet temperatures exhibit larger ice accretions, with circumferentially averaged blockage up to 3.16 times the dry vaned baseline. A vaneless reference case exhibits only light frosting under the same conditions. The scanned accretions are used in conjunction with experimental wall thermal histories to identify regions of shedding by advancing thermal boundary conditions and resolving the likely impact on subsurface water films. This hybrid experimental–numerical approach offers a robust framework for informing future shed models with realistic thermal boundary conditions and accretion geometries.

University of Oxford (GB)
Openalex Percentile: Top 76%
Icing and De-icing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.