Essays about: "Initial curvature"
Showing result 1 - 5 of 14 essays containing the words Initial curvature.
-
1. Interaction for flexural column buckling : Analytical procedures compared with FE-simulations
University essay from KTH/Bro- och stålbyggnadAbstract : This master's thesis presents a study on the stability of steel structures under flexural bucklingconstraints. The study focuses on the interaction and behaviour of flexural buckling formulas in SSEN-1993-1-1 and Swedish BSK and the performance of actual structural members subjected to suchconstraints. READ MORE
-
2. Predicting Road Rut with a Multi-time-series LSTM Model
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : Road ruts are depressions or grooves worn into a road. Increases in rut depth are highly undesirable due to the heightened risk of hydroplaning. Accurately predicting increases in road rut depth is important for maintenance planning within the Swedish Transport Administration. READ MORE
-
3. Steering Method for Nonholonomic Motion Planning based on Quadratic Programming and Differential Flatness
University essay from KTH/Optimeringslära och systemteoriAbstract : In this thesis, an optimization based steering methods based on differential flatness and quadratic programming has been investigated. The method has been implemented into an RRT*-planner and tested in simulation. READ MORE
-
4. Modelling stellar streams around the Milky Way
University essay from Lunds universitet/Astronomi - Genomgår omorganisationAbstract : Stellar streams around the Milky Way (MW) have been observed by wide sky surveys, and studied to understand the mass distribution of the MW. This is because streams are formed by a disruption of a globular cluster or a dwarf galaxy under the influence of the gravitational field of the MW. READ MORE
-
5. Evaluating the Practicality of Using a Kronecker-Factored Approximate Curvature Matrix in Newton's Method for Optimization in Neural Networks
University essay from KTH/Skolan för teknikvetenskap (SCI)Abstract : For a long time, second-order optimization methods have been regarded as computationally inefficient and intractable for solving the optimization problem associated with deep learning. However, proposed in recent research is an adaptation of Newton's method for optimization in which the Hessian is approximated by a Kronecker-factored approximate curvature matrix, known as KFAC. READ MORE