Sökning: "Weight Topology Optimization"
Visar resultat 11 - 15 av 36 uppsatser innehållade orden Weight Topology Optimization.
11. Evaluating Topology Optimization as an alternative methodology for developing Vibration Test Fixtures
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för teknikvetenskap och matematikSammanfattning : This thesis evaluates an alternative method for creating vibration test fixtures. The new method is based on producing fixtures by utilizing the external forces, that a fixture is subjected to during vibration tests, instead of creating it with estimations and guess-work, as it is done today. LÄS MER
12. Design for Additive Manufacturing : An Optimization driven design approach
Master-uppsats, KTH/Maskinkonstruktion (Inst.)Sammanfattning : Increasing application of Additive Manufacturing (AM) in industrial production demands product reimagination (assemblies, subsystems) from an AM standpoint. Simulation driven design tools play an important part in achieving this with design optimization subject to the capabilities of AM technologies. LÄS MER
13. Methodology Development for Topology Optimization of Power Transfer Unit Housing Structures
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : Simulation driven design is a method and process that has been developed over many years, and with today’s advanced software, the possibility to embed simulation into the design process has become a reality. The advantages of using simulation driven design in the product development process is well known and compared to a more traditional design process, the simulation driven design process can give the user the possibility to explore, optimize and design products with reduced lead time. LÄS MER
14. Childhood Habituation in Evolution of Augmenting Topologies (CHEAT)
Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationSammanfattning : Neuroevolution is a field within machine learning that applies genetic algorithms to train artificial neural networks. Neuroevolution of Augmenting Topologies (NEAT) is a method that evolves both the topology of the network and trains the weights of the network at the same time, and has been found to successfully solve reinforcement learning problems efficiently and the XOR problem with a minimal topology. LÄS MER
15. Konceptutveckling av solbilskaross
Kandidat-uppsats, Jönköping University/Tekniska HögskolanSammanfattning : “Development of a solar car body” is a bachelor thesis done at Jönköping University by two students studying mechanical engineering with a focus on product development and design. The project has been done for JU Solar Team, an organization where student develop and build a solar powered electric car with which they then use in the competition Bridgestone World Solar Challenge. LÄS MER