Browse Topic: Cost analysis
The emergence of electric Vertical Takeoff and Landing (eVTOL) air vehicles is transforming how people and freight are moved in short distances. This transformation has a profound impact on surrounding infrastructure necessary to provide Aircraft On Ground support for eVTOLs. The hover capabilities of eVTOLs have similar operating characteristics within terminal and uncontrolled airspace. However, the need to conserve battery energy via rapid approaches and departures affects terminal airspace management. To attract eVTOL operators, existing airports, landing zones, and vertiports are modifying their infrastructure to include fixed electric charging stations, additional taxiways, upgraded fire suppression systems, separate hangers, and capable MRO facilities. Augusta Regional Airport (KAGS) is the base airport for the annual Masters Golf Tournament which experiences five times the normal airport traffic and some 40,000 commuting patrons. eVTOLs can offset land traffic issues associated
This study investigates the use of machine learning (ML) models to estimate the gross weight (GW), the longitudinal position of the center of gravity (CGx), and 1/rev cyclic flapping angles (Δ1c and Δ1s) of a compound helicopter with three redundant controls - main rotor RPM, collective propeller thrust, and stabilator angle. Neural Network (NN), Gaussian Process for Regression (GPR), and Support Vector Machine (SVM) algorithms are employed to develop estimation models using supervised training. The airspeed, redundant controls, main rotor controls, aircraft attitudes, and main rotor torque are selected as input variables (predictors) to the models due to their accessibility through the aircraft Health and Usage Monitoring System (HUMS). The dataset is split into low-speed and high-speed regimes to compare the prediction accuracy and training cost of separate regime models against a combined full-regime model. Separate airspeed regime GPR models showed superior performance in GW
For high end composite manufacturing in a rapid development environment, the long lead item is often the hard tooling, in particular the cure mold. A traditional metal mold takes in the neighborhood of four to nine months to design, fabricate and validate. With high temperature capable print materials, and larger and faster printers, Additive Manufacturing (AM) appears to have high potential in this area of advanced composites manufacturing. Sikorsky has used AM very successfully on a scale up to approximately 3'x3' and cure temperatures of 350°F. Though long-term durability is still to be determined; the materials, technologies, and techniques Sikorsky has employed for AM autoclave cure molds on this scale have consistently exceeded expectations. AM tools along the scale of main rotor blades could be leveraged to realize even more significant cost and schedule gains from AM autoclave tooling, and in this area, there are still more questions than answers when it comes to a dependable
This SAE EDGE Research Report looks at the pros and cons of moving this technology forward and brings recommendations to facilitate a smooth transition from fossil fuel-based to hydrogen-based mobility.Unsettled Issues Concerning the Economics of Fuel Cells and Electric Ground Vehicles discusses the unsettled economic aspects of hydrogen and fuel cell applications in the automotive industry. Lately, the idea of using hydrogen in automotive applications is gaining momentum. While the concept of using clean hydrogen fuel generated from water via electrolysis is nothing new, previous efforts to mainstream the technology failed miserably. About a decade ago, the fuel cell technology, which efficiently converts hydrogen and atmospheric oxygen into electricity, was not as advanced and the fuel cell prototypes were bulky and expensive.Yet, many new fuel cell electric vehicles (FCEVs) have emerged, and hydrogen refueling infrastructure is being built globally. Despite the important steps
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