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Technical Paper

Aerodynamics' Influence on Performance in Human-Powered Vehicles for Sustainable Transportation

2024-06-12
2024-37-0028
The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.
Technical Paper

Reduction in Flight Operational Costs by Automating Weather Forecast Updates

2024-06-01
2024-26-0440
A GE Aviation Systems report documents that the National Oceanic and Atmospheric Administration (NOAA) provided weather forecast data has a bias of 15 knots and a standard deviation of 13.3 knots for the 40 flights considered for the research. It also had a 0.47 bias in the temperature with a standard deviation of 0.27. The temperature errors are not as significant as the wind. There is a potential opportunity to reduce the operational cost by improving the weather forecast. The flight management system (FMS) currently uses the weather forecast, available before takeoff, to identify an optimized flight path with minimum operational costs depending on the selected speed mode. Such a flight plan could be optimum for a shorter flight because these flight path planning algorithms are very less susceptible to the accuracy of the weather forecast.
Event

Contact - AeroTech®

2024-05-17
Contact the AeroTech team for any questions around exhibiting, sponsorship, event programming, and more.
Event

Exhibit & Sponsor - 2025 AeroTech

2024-05-17
Secure your space! Reserve your AeroTech exhibit booth and/or sponsorship today — and take advantage of early-bird opportunities at AeroTech® 2024.
Event

Exhibit & Sponsor - 2025 AeroTech

2024-05-17
Secure your space! Reserve your AeroTech exhibit booth and/or sponsorship today — and take advantage of early-bird opportunities at AeroTech® 2024.
Event

Program - 2024 AeroTech

2024-05-17
Explore AeroTech's Key Tracks, Sessions, and Presentations on hot topics in the Aerospace industry.
Event

AeroTech

2024-05-17
AeroTech is your passport to explore the most remarkable advancements in aerospace technology. Form supersonic aircraft to sustainable aviation and propulsion, AeroTech covers it all.
Event

Social Media Toolkit - 2024 AeroTech®

2024-05-17
Check out the topics of discussion at the 2024 AeroTech event, such as aircraft systems, advanced air mobility, manufacturing and materials, and so much more!
Standard

Sheet and Strip Surface Finish Nomenclature

2024-05-16
CURRENT
AS4194B
This SAE Aerospace Standard (AS) defines the nomenclature for surface finishes commonly used for sheet and strip in aerospace material specifications. It is applicable to steel and to iron, nickel, cobalt, and titanium base alloys.
Magazine

Aerospace & Defense Technology: May 2024

2024-05-09
Explaining MOSA from the Team that Led the Army Aviation Mission Computing Environment Task Order What's the Best DC Motor for Your Commercial Aerospace Application? Aerospace Production: Overcoming Challenges in Composite Machining Understanding the Limits of Artificial Intelligence for Predictive Maintenance Pushing the Limits: Engineering Advanced RF Interconnects to Meet the Challenges of Hypersonic Missile Development Expanding Possibilities for Superconducting Qubits With Niobium Researchers Help Robots Navigate Efficiently in Uncertain Environments A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination.
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