An electrolytic tank for the measurement of steady-state response, transient response, and allied properties of networks

1949 ◽  
Vol 96 (99) ◽  
pp. 163-177 ◽  
Author(s):  
A.R. Boothroyd ◽  
E.C. Cherry ◽  
R. Makar
2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Ruiyang Wang ◽  
Bingen Yang

Abstract In Part I of this two-part paper, a new benchmark transient model of Inductrack systems is developed. In this Part II, the proposed model, which is governed by a set of non-linear integro-differential governing equations, is used to predict the dynamic response of Inductrack systems. In the development, a state-space representation of the non-linear governing equations is established and a numerical procedure with a specific moving circuit window for transient solutions is designed. The dynamic analysis of Inductrack systems with the proposed model has two major tasks. First, the proposed model is validated through comparison with the noted steady-state results in the literature. Second, the transient response of an Inductrack system is simulated and analyzed in several typical dynamic scenarios. The steady-state response results predicted by the new model agree with those obtained in the previous studies. On the other hand, the transient response simulation results reveal that an ideal steady-state response can hardly exist in those investigated dynamic scenarios. It is believed that the newly developed transient model provides a useful tool for dynamic analysis of Inductrack systems and for in-depth understanding of the complicated electro-magneto-mechanical interactions in this type of dynamic systems.


1993 ◽  
Vol 04 (01) ◽  
pp. 1-13 ◽  
Author(s):  
ÖRJAN EKEBERG

This work is concerned with the question of how a population of neurons responds to tonic and transient synaptic input from other similar populations. Because of the methodological problems involved in measuring and manipulating the firing properties of a large set of real neurons simultaneously, another strategy is used here: the experiments are made as a series of simulations using a population of realistic model neurons. The steady state response of this particular model neuron is found to be similar to that used in abstract nonspiking models. The transient response, however, reveals that even though each individual neuron simply changes its frequency moderately, the population can respond quickly and with damped oscillations. These oscillations are due to spike synchronization caused by systematic phase shifts induced by synchronous changes in the input.


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