Sea Spray Icing Prediction - Integrating Experiments, Machine Learning, and Computational Fluid Dynamics

Aug 5, 2026

Sea spray icing prediction is addressed through a dissertation that develops and evaluates a machine-learning model (SPICE) for forecasting icing of sea spray. The work integrates experimental evidence with data-driven learning and computational fluid dynamics, using the sea spray icing problem, the need for accurate predictions, and existing standards and regulations as motivation. It surveys historical sea-spray icing models, contrasts forecasting versus comprehensive prediction approaches, and identifies limitations that motivate improved modeling and new datasets.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages181

Reading Time7 h 36 min

AccessFree to download

Abstract

Main contributions

List of Publications

Objective of the PhD project

Introduction

The sea spray icing problem

Necessity of icing predictions

Standards and regulations on sea spray icing

A relevant research topic

History of sea spray icing models

Need for an improved model

Artificial Intelligence and Machine Learning

Computational Fluid Dynamics

Need for more and new data

Paper 1

Faculty of Engineering Science and Technology Sea Spray Icing Prediction: Integrating Experiments, Machine Learning, and Computational Fluid Dynamics. SPICE: A machine learning model for prediction of sea spray icing. Sujay Deshpande A dissertation for the degree of Philosophiae Doctor (PhD) [May 2024] A personal note Thank you, Annie, for being with me through all of this, the encouragement, motivation, inspiration, and for everything else. Thank you Sia for all the beautiful memories so far and wish for many more to come. आई बाबाांचा आशीर्ााद…1 Words fall short to describe this long journey, and so does the list of people to thank. Deeply indebted to all family and friends who were a part of this, all from literal physical help during the experiments to helping me learn and brainstorming with me; for all the support from back in India, and all over the world; and for all the memories we shared and who continue to bless me from up there – we shall continue to be one, अहम् ब्रह्मास्मि2. Finally, to all PhD fellow colleagues at UiT suffering from stress, anxiety, and depression as a direct result of their work and workplace – keep on fighting for what you dreamt of at the start, don’t let others put you down. Most importantly, don’t let the PhD journey dictate your life, you are far better and stronger than the outcome. Carry on, as if nothing really matters3, because it doesn’t. And always remember, अपना time आएगा, तू नांगा ही तो आया है क्या घांटा लेकर जाएगा4. 1 In Marathi: With the blessings of my mother and father 2 In Sanskrit: A spiritual belief from Indian Vedic Literature from the 6th century BCE indicating absolute oneness of the self with the universe. Each aspect of the universe, the ultimate reality, each individual in the non-physical form, the soul, are one and the same entity. 3 Bulsara, Farrokh aka Freddy Mercury; Queen, 1975 4 In Hindi (Mumbai dialect): I will succeed. You have come empty handed and will leave so. Da Silva Fernandes, Vivian Wilson aka Divine; Tewari, Ankur; and Singh, Ranveer; Gully Boy, 2019 Table of contents 1. Abstract ................................................................................................................................................. 8 1.1. Main contributions........................................................................................................................ 9 2. List of Publications ................................................................................................................................ 9 3. Objective of the PhD project ............................................................................................................... 10 4. Introduction ........................................................................................................................................ 10 4.1. The sea spray icing problem........................................................................................................ 10 4.2. Necessity of icing predictions ..................................................................................................... 11 4.3. Standards and regulations on sea spray icing ............................................................................. 12 4.3.1. Consequences of standards and regulations ...................................................................... 12 4.4. A relevant research topic ............................................................................................................ 13 4.5. History of sea spray icing models................................................................................................ 13 4.5.1. Forecasting vs Comprehensive Predictions......................................................................... 14 4.5.2. Overland model................................................................................................................... 14 4.5.3. Roebber & Mitte

FAQs

What is SPICE in this dissertation?

SPICE is a machine learning model developed for prediction of sea spray icing.

Why are icing predictions important in sea spray icing research?

The dissertation explains that reliable icing predictions are necessary due to requirements from standards and regulations and to reduce uncertainty from inadequate modeling.

How does the dissertation integrate experiments, machine learning, and computational fluid dynamics?

The approach combines experimental observations with machine learning for data-driven prediction and computational fluid dynamics to support spray and icing modeling considerations.

Aug 5, 2026

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