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Aerospace R&D

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Aerospace R&D has been a driving force for innovation pushing major technological advancements that have redefined transportation, led to incredible discoveries, and sheparded in a fourth industrial revolution—digital transformation—which will create exciting opportunities for revolutionary transitions. AIAA can provide thought leadership and be a trusted voice, guiding the larger community through this shift. Interdisciplinary work fostered by advanced collaboration promises to yield breakthroughs in aeronautics and aerospace systems. Digital transformation is driving model-based technological advances such as digital engineering, digital twin, and digital thread, which are expected to accelerate the pace of R&D to deployment of advanced systems significantly. Such innovation can lower overall total lifecycle cost and ultimately improve customer experiences.

Across aeronautics and aerospace, we are information rich, but knowledge poor. We need smarter collaboration between people and their machines and tools to harvest the data. Digital transformation will allow us to capture knowledge, use it in models, and then apply it to new materials. Rapid prototyping and integration will accelerate first-design feasibility. We also need to enable artificial intelligence and machine learning to make our machines smarter. Shifting routine tasks to machines will allow our workforce to focus on tackling the next generation of technology challenges.

Within the Aerospace R&D Domain, we must address significant issues including potential cyberattacks on aerospace systems and building autonomous systems from a moral, ethical, and legal perspective. We also must find ways to accelerate the deployment of technology, with appropriate testing to help ensure success.

AIAA Aerospace R&D Lead
Tobey Jackson

Senior Vice President, Events |  Contact Us

Key Topics

  • advanced-materials-cover Advanced Manufacturing and Advanced Materials

    How do we incorporate multifunctional materials, create lighter systems through the application of new materials and new manufacturing techniques, and accelerate the certification of new materials and new manufacturing processes?

  • ai-machine-learning-domains-thumbnail Autonomy

    We must safely insert advanced information technologies into aerospace systems and provide smart contingency management capabilities across all aerospace plattorms. How can we leverage lessons from the automotive industry to help us address emerging issues, such as increasing congestion in both air and space traffic? We should consider how we adopt a human-centered autonomy approach.

  • ai-machinelearning-graphic-istock-thumbnail Artificial Intelligence/Machine Learning

    Recent developments in artificial intelligence and machine learning are making headlines, and are already having a strong impact on how aerospace professionals work. How will Al and ML impact aerospace science and engineering practices? How can Al and ML applications provide new pathways for safer, faster, and more cost-effective aerospace system development?

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  • assured-sysems-cover Resilient and Assured Systems

    With increasing levels of autonomous control, how do we ensure that the resulting behaviors satisfy legal, moral, and ethical perspectives? As we create increasingly more complex and adaptive systems, how do we ensure that these systems are as safe, or safer, than previous generations? How do we accelerate lessons learned and incorporate into already deployed systems? As systems become more self-aware, can they adapt their control systems to reflect sensor or mechanical disruptions?

  • transformative-sys-engineering-thumbnail Transformative Systems Engineering

    How do we embrace digital twin concepts being inspired by engineered resilient systems and accelerate adoption of model-based systems engineering (MBSE)? How do we create frameworks to incorporate new technologies into system engineering methodologies, such as human-AI teaming and advanced materials more effectively? And we must leverage new digital techniques to reverse the trend of increasing timelines from first flight to initial operational capability.

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