What are the latest aerospace engineering research tools and methods you use?

2 Digital Twins

Digital twins are virtual replicas of physical systems or assets that can be used to monitor, control, and optimize their performance and behavior. Digital twins can help you create a digital thread that connects the design, manufacturing, operation, and maintenance of your aerospace products, as well as enable data-driven decision making and predictive analytics. Digital twins can also enhance the reliability, safety, and efficiency of your systems, as well as reduce the risks of failures or malfunctions. Some of the latest digital twin tools and methods include cloud computing, artificial intelligence, and internet of things.

3 Additive Manufacturing

Additive manufacturing (AM) is a process of creating objects by depositing layers of material on top of each other, using a computer-controlled device, such as a 3D printer. AM can help you create complex and customized shapes and structures that are not possible or feasible with traditional manufacturing methods, such as machining or casting. AM can also reduce the waste, cost, and time of production, as well as improve the quality and performance of your aerospace components. Some of the latest AM tools and methods include metal powder bed fusion, direct energy deposition, and topology optimization.

4 Model-Based Systems Engineering

Model-based systems engineering (MBSE) is a method of applying systems engineering principles and practices using models as the primary means of communication and documentation. MBSE can help you manage the complexity and interdependency of your aerospace systems, as well as facilitate collaboration and integration among different disciplines and stakeholders. MBSE can also improve the traceability, consistency, and verification of your requirements, specifications, and designs, as well as enable faster and cheaper changes and modifications. Some of the latest MBSE tools and methods include SysML, Modelica, and Simulink.

5 Machine Learning

Machine learning (ML) is a branch of artificial intelligence that involves teaching computers to learn from data and perform tasks without explicit programming. ML can help you discover patterns, trends, and insights from large and complex datasets, such as images, videos, or sensors, that are relevant to your aerospace engineering problems. ML can also enhance the accuracy, speed, and scalability of your analysis, prediction, and optimization processes, as well as enable new capabilities and applications. Some of the latest ML tools and methods include deep learning, reinforcement learning, and neural networks.

6 Virtual Reality

Virtual reality (VR) is a technology that creates an immersive and interactive simulation of a realistic or imaginary environment, using devices such as headsets, gloves, or controllers. VR can help you visualize, explore, and manipulate your aerospace engineering models and designs, as well as test and evaluate their functionality and usability. VR can also improve the training, education, and collaboration of your aerospace engineering team, as well as provide a more engaging and enjoyable experience. Some of the latest VR tools and methods include haptic feedback, eye tracking, and mixed reality.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?