Simulation of spark dynamic plasma resistance and inductance using PSpice

Hogg, Michael G.; Timoshkin, I. V.; MacGregor, S.J.; Given, M.J.; Wilson, M. P.; Wang, Tao

doi:10.1109/ipmhvc.2014.7287292

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…Figure 4 shows an example of the time dependence of current (I (R2)) and voltage (V (vist)) with a linear change in the MEP value from 1000 microns (XX from 0 to 2.5 ms) to 0 (shortcircuit for 7ms) and vice versa. The data obtained in the simulation are in good agreement with other experimental data [6]. Taking into account the peculiarities of the behavior of current and voltage during EEE, it is possible to evaluate the effectiveness of a particular mode of processing various materials.…”

Section: Resultssupporting

confidence: 80%

Application of Circuit Modeling in the Study of Spark Formation During Electroerosion Treatment

Porvatov¹,

Kozochkin²,

Minin³

et al. 2021

EPJ Web Conf.

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Electrical discharge machining (EDM) of a workpiece is a complex, fast-flowing process characterized by alternating (intermittent) states: short circuit, idle and spark formation. The discontinuity of the EDM process means that the processing is carried out in single pulses, which are formed by a special pulse generator. The parameters of the generator pulses can be divided into time and electrical. The time period and duration of the pulses, as well as the difference between these two parameters (the “silence” interval), are considered temporary. The electric ones include the amplitude value of the voltage, the maximum permissible current, and the polarity of the pulses. in addition, depending on the device of the generator, the pulses can be composite, for example, have an igniting pulse with a higher voltage and a lower current than the main (working) pulse. In this work, we have developed a interelectrode gap model that allows not only to obtain values of electrical parameters, but also to evaluate and to optimize the electrical parameters of materials being processed with known electrical properties. The key advantage of this model is its modularity, which allows to add new functional blocks, which describe external and internal influences, for example, the concentration of erosion products, uneven electrical conductivity of the workpiece, and others, without changing its structure.

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Section: Resultssupporting

confidence: 80%

Application of Circuit Modeling in the Study of Spark Formation During Electroerosion Treatment

Porvatov¹,

Kozochkin²,

Minin³

et al. 2021

EPJ Web Conf.

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“…(4) used for the resistance and Eq. (14) for the averaged conductivity. It can be noticed that the two curves match at early times, and their trends are similar (their correlation factor is 0.9978).…”

Section: Resultsmentioning

confidence: 99%

“…(9) with the averaged conductivity ̅ given by Eq. (14), and using Eq. (2) to perform the integration we get:…”

Section: Electrical Conductivity and Spark Channel Radiusmentioning

confidence: 99%

“…Consequently; the channel temperature does not change appreciably, which implies an approximately steady electrical conductivity of the spark channel [11,12]. Beside its classification as to yield good qualitative agreements with experiments [11,13,14], the Braginskii"s model rarely fit with experimental data due to the assumption made of a steady electrical conductivity [1,11].…”

Section: Introductionmentioning

confidence: 99%

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Considerations on Spark- Gap Channel Radius and Electrical Conductivity

Habib¹

2020

ETJ

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A simple phenomenological model is established to determine the temporal evolution of spark gap channel radius and electrical conductivity during the resistive phase period. The present determination is based on the Braginskii’s equation for the channel radius which includes the electrical conductivity of the discharge channel as a constant quantity. In the present model, however, the electrical conductivity is regarded as a time varyingquantity. Basing on this, a mathematical formulation for the channel radius as a function of time was derived, and this has made possible the derivation of an explicit expression for the conductivity as a function of time as well. Taking the temporal average of the electrical conductivity offers an alternative mathematical formulation for the instantaneous radius based on a steady conductivity value that can be determined according to some experimental parameters. It has been verified that both of the channel radius formulations mentioned above lead to similar results for the temporal evolution. The obtained results of the channel radius were used to determine the instantaneous inductance of the spark channel. The present model was used to examine the role of gas pressure and gap width on the temporal evolutions of the channel radius, conductivity, and inductance in nanosecond spark gaps.

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“…Some researchers have tried to simulate the spark behaviour with a circuit model consisting of spark resistance