Characteristic study, its identification and self-tuned approach to control hydro-power plants

The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

The Advantage of Arriving First: Characteristic Times in Finite Size Populations of Error-Prone Replicators

We study the evolution of a finite size population formed by mutationally isolated lineages of error-prone replicators in a two-peak fitness landscape. Computer simulations are performed to gain a stochastic description of the system dynamics. More specifically, for different population sizes, we compute the probability of each lineage being selected in terms of their mutation rates and the amplification factors of the fittest phenotypes. We interpret the results as the compromise between the characteristic time a lineage takes to reach its fittest phenotype by crossing the neutral valley and the selective value of the sequences that form the lineages. A main conclusion is drawn: for finite population sizes, the survival probability of the lineage that arrives first to the fittest phenotype rises significantly

Strain rate effect on semi‐crystalline plla mechanical properties measured by instrumented indentation tests

Poly(L‐lactide) is a widely studied biomaterial, currently approved for use in a range of medical devices. Its mechanical properties can be tailored giving the material different crystallinity degrees. PLLA presents a complex non‐linear behaviour that depends not only on structural parameters such as crystallinity degree but also on external parameters such as strain rate and temperature. Failure of polymeric implants is attributed to their intrinsic time‐dependent performance under static loading conditions.