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Multiple Near-Earth Asteroid Rendezvous and Sample Return Using First Generation Solar Sailcraft
(2005)
Solar Sails for Near- and Medium-Term Scientific Deep Space Missions / W. Sebolt ; B. Dachwald
(2005)
Optimization of Interplanetary Rendezvous Trajectories for Solar Sailcraft Using a Neurocontroller
(2002)
Solar sailcraft of the first generation technology development / Seboldt, Wolfgang ; Dachwald, Bernd
(2003)
In this chapter, the key technologies and the instrumentation required for the subsurface exploration of ocean worlds are discussed. The focus is laid on Jupiter’s moon Europa and Saturn’s moon Enceladus because they have the highest potential for such missions in the near future. The exploration of their oceans requires landing on the surface, penetrating the thick ice shell with an ice-penetrating probe, and probably diving with an underwater vehicle through dozens of kilometers of water to the ocean floor, to have the chance to find life, if it exists. Technologically, such missions are extremely challenging. The required key technologies include power generation, communications, pressure resistance, radiation hardness, corrosion protection, navigation, miniaturization, autonomy, and sterilization and cleaning. Simpler mission concepts involve impactors and penetrators or – in the case of Enceladus – plume-fly-through missions.
Solar Sail Kinetic Energy Impactor Trajectory Optimization for an Asteroid-Deflection Mission
(2007)
Solar Sail Trajectory Optimization for Intercepting, Impacting, and Deflecting Near-Earth Asteroids
(2005)
Low emission zones and truck bans, the rising price of diesel and increases in road tolls: all of these factors are putting serious pressure on the transport industry. Commercial vehicle manufacturers and their suppliers are in the process of identifying new solutions to these challenges as part of their efforts to meet the EEV (enhanced environmentally friendly vehicle) limits, which are currently the most robust European exhaust and emissions standards for trucks and buses.
Möglichkeiten der ottomotorischen Prozeßführung bei Verwendung des elektromechanischen Ventiltriebs
(1998)
Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.