Falk Riess

An advanced model of bicycle dynamics

A theoretical model of a moving bicycle is presented for arbitrary bicycle geometries at finite angles. The nonlinear equations of motion are derived and solved with the help of a computer. The solutions are tested for energy conservation, and examined with respect to inherent stability. For common bicycles, velocity and lean angle ranges of self-stable motion are predicted.

Stochastic analysis of different rough surfaces

Abstract.This paper shows in detail the application of a new stochastic approach for the characterization of surface height profiles, which is based on the theory of Markov processes. With this analysis we achieve a characterization of the scale dependent complexity of surface roughness by means of a Fokker-Planck or Langevin equation, providing the complete stochastic information of multiscale joint probabilities. The method is applied to several surfaces with different properties, for the purpose of showing the utility of this method in more detail. In particular we show evidence of the Markov properties, and we estimate the parameters of the Fokker-Planck equation by pure, parameter-free data analysis. The resulting Fokker-Planck equations are verified by numerical reconstruction of the conditional probability density functions. The results are compared with those from the analysis of multi-affine and extended multi-affine scaling properties which is often used for surface topographies. The different surface structures analysed here show in detail the advantages and disadvantages of these methods.

Stochastic analysis of surface roughness

For the characterization of surface height profiles we present a new stochastic approach which is based on the theory of Markov processes. With this analysis we achieve a characterization of the complexity of the surface roughness by means of a Fokker-Planck or Langevin equation, providing the complete stochastic information of multiscale joint probabilities. The method was applied to different road surface profiles which were measured with high resolution. Evidence of Markov properties is shown. Estimations for the parameters of the Fokker-Planck equation are based on pure, parameter-free data analysis.

A Multibody Model for the Simulation of Bicycle Suspension Systems

The paper describes a two-dimensional mathematical model for the motion of a bicycle-rider system with wheel suspensions. It focusses on the prediction of vibrational stress on the rider due to uneven track. The model was evaluated by comparing its predictions with measuring data concerning weighted accelerations on the human body, depending on various bicycle designs and road surfaces. For the intended purpose the predictions for vibrational stress and vibrational behaviour are sufficiently precise, and the model turns out to be adequate for designing and developing bicycle suspensions.

From an idea to a vision: There’s plenty of room at the bottom

Many workers in nanotechnology cite Richard Feynman’s after-dinner speech, “There’s plenty of room at the bottom,” which was given by him on December 29, 1959, to be the birthday of theoretical nanotechnology. This attribution is misleading because there is no direct link from Feynman’s talk to today’s micromachines. We discuss the historical background of Feynman’s talk, the state of the art in 1959, and Feynman’s motivation. We conclude that Feynman was not interested in building miniaturized versions of existing macroscopic machines, but wished to construct microbiological machines and tools that would enable scientists to mimic microbiological materials.

Fat Tail Statistics and Beyond

Based on data from three different systems, namely, turbulence, financial market and surface roughness we discuss methods to analyze their complexities. Scaling analysis and fat tail statistics in the context of Levy distributions are compared with a stochastic method, for which a Fokker-Planck equation can be estimated from data. We show that the last method provides a more detailed characterization of complexity.