The OpenAP Handbook

A comprehensive guide on aircraft performance, emission, optimization calculations for air transport researchers and developers. Source code on GitHub.
Authors
Affiliation

Delft University of Technology

Delft University of Technology

Preface

Synopsis

Welcome to the OpenAP handbook, a comprehensive guide to unlocking the full potential of the OpenAP aircraft performance library. This book is designed to help you navigate the vast capabilities of OpenAP, an open-source initiative that has been revolutionizing air transport research since its inception in 2019.

The first part of this book takes you through the core components that form the foundation of OpenAP. From the fundamentals of aircraft and engine data (Chapter 1) to the intricacies of drag and maximum thrust calculations (Chapter 2), kinematic models (Chapter 3), and flight phase identification (Chapter 4), we delve into the key components that make OpenAP an indispensable tool for researchers, developers, and aviation professionals. You will also learn how to harness OpenAP’s trajectory generation capabilities (Chapter 5) and analyze fuel and emission data (Chapter 6).

The second part focuses on the Trajectory Optimizer Package (TOP), an extension of OpenAP. Here, you will learn how to generate fuel-optimal and other types of optimal trajectories (Chapter 7). You will discover how to incorporate wind data into your optimizations (Chapter 8). Additionally, you will learn how to use TOP to handle more complex four-dimensional grid costs in your optimization problems, such as contrail formation (Chapter 9).

Each chapter provides detailed insights into the underlying concepts, methodologies, and best practices, empowering you to make the most of OpenAP. Whether you’re a seasoned expert or new to the field, this manual will help you navigate the OpenAP library effectively. The goal is to equip you with the knowledge and skills necessary to leverage OpenAP in your research. Let’s embark on this journey together and explore the possibilities that OpenAP has to offer.

About the Authors

Junzi Sun is an assistant professor in the CNS/ATM group at the TU Delft Faculty of Aerospace Engineering. His research focuses on aircraft surveillance and performance modeling, data science and AI, and aviation sustainability. Passionate about open-source and open science, he aims to make air transportation more sustainable. Born in China, he earned his bachelor’s in telecommunication in Beijing before moving to Europe for his master’s in aerospace engineering at the Polytechnic University of Catalonia. After working in Spain and France, he completed his doctoral research in the Netherlands, where he currently works and lives.

Jacco Hoekstra is a professor in the CNS/ATM group at the TU Delft Faculty of Aerospace Engineering with a focus on enhancing aviation safety, efficiency, and sustainability. As the Chair of CNS/ATM, his research employs simulation, signal processing, and big data to create solutions for avoiding in-flight hazards. He is recognized for contributions to airborne separation assurance, data link technology, and 4D trajectory-based operations. His former roles include the Dean of the Faculty of Aerospace Engineering and the Head of the Air Transport Division at the Netherlands Aerospace Laboratory.


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