Probabilistic representation of harmonic currents in AC traction systems

1984 ◽  
Vol 131 (5) ◽  
pp. 181 ◽  
Author(s):  
R.E. Morrison ◽  
A.D. Clark
Keyword(s):  
Probabilistic Representation ◽  
Harmonic Currents

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Probabilistic Representation of Complexity

2001 ◽  
Author(s):  
Nabil I. Al-Najjar ◽  
Ramon Casadesus-Masanell ◽  
Emre Ozdenoren
Keyword(s):  
Probabilistic Representation

scholarly journals BSDEs with polynomial growth generators

2000 ◽  
Vol 13 (3) ◽  
pp. 207-238 ◽  
Author(s):  
Philippe Briand ◽  
René Carmona
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Existence And Uniqueness ◽  
Polynomial Growth ◽  
Probabilistic Representation ◽  
Existence And Uniqueness Results ◽  
State Variable ◽  
Cahn Equation ◽  
Uniqueness Results ◽  
Terminal Time

In this paper, we give existence and uniqueness results for backward stochastic differential equations when the generator has a polynomial growth in the state variable. We deal with the case of a fixed terminal time, as well as the case of random terminal time. The need for this type of extension of the classical existence and uniqueness results comes from the desire to provide a probabilistic representation of the solutions of semilinear partial differential equations in the spirit of a nonlinear Feynman-Kac formula. Indeed, in many applications of interest, the nonlinearity is polynomial, e.g, the Allen-Cahn equation or the standard nonlinear heat and Schrödinger equations.

scholarly journals A Novel Method for Harmonic Current Injection with Sensor Supported Adaptation on Permanent Magnet Synchronous Machines

Machines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 139
Author(s):  
Matthias Vollat ◽  
Dominik Krahe ◽  
Frank Gauterin
Keyword(s):  
Permanent Magnet ◽  
Current Injection ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machine ◽  
Permanent Magnet Synchronous Machines ◽  
Harmonic Current ◽  
Harmonic Currents ◽  
Sensor Signals ◽  
Novel Method ◽  
Higher Harmonic

To reduce torque oscillations in electric motors, harmonic current injection (HCI) has been used in industry for some time. For this purpose, higher harmonic currents calculated in advance are injected into the machine. Since the general conditions for the machine can change during its life cycle, this article presents a method that makes it possible to change the parameters of HCI during operation. For this purpose, sensor signals are used to detect the reaction of the electric motor to small variations of the HCI parameters. The knowledge gained in this way is used to make further suitable variations. FEM simulations were used to verify the effectiveness of the approach. The results show that the algorithm can independently optimize the HCI parameters during runtime and reduces the amplitude of the 6th harmonic in the torque by 87% for a permanent magnet synchronous machine.

Using Tolerance-Maps to Generate Frequency Distributions of Clearance and Allocate Tolerances for Pin-Hole Assemblies

2007 ◽  
Vol 7 (4) ◽  
pp. 347-359 ◽  
Author(s):  
Gaurav Ameta ◽  
Joseph K. Davidson ◽  
Jami J. Shah
Keyword(s):  
Mathematical Model ◽  
Statistical Method ◽  
Frequency Distribution ◽  
Probabilistic Representation ◽  
Worst Case ◽  
Frequency Distributions ◽  
One Dimensional ◽  
Material Condition ◽  
Geometric Tolerances ◽  
Case Basis

A new mathematical model for representing the geometric variations of lines is extended to include probabilistic representations of one-dimensional (1D) clearance, which arise from positional variations of the axis of a hole, the size of the hole, and a pin-hole assembly. The model is compatible with the ASME/ ANSI/ISO Standards for geometric tolerances. Central to the new model is a Tolerance-Map (T-Map) (Patent No. 69638242), a hypothetical volume of points that models the 3D variations in location and orientation for a segment of a line (the axis), which can arise from tolerances on size, position, orientation, and form. Here, it is extended to model the increases in yield that occur when maximum material condition (MMC) is specified and when tolerances are assigned statistically rather than on a worst-case basis; the statistical method includes the specification of both size and position tolerances on a feature. The frequency distribution of 1D clearance is decomposed into manufacturing bias, i.e., toward certain regions of a Tolerance-Map, and into a geometric bias that can be computed from the geometry of multidimensional T-Maps. Although the probabilistic representation in this paper is built from geometric bias, and it is presumed that manufacturing bias is uniform, the method is robust enough to include manufacturing bias in the future. Geometric bias alone shows a greater likelihood of small clearances than large clearances between an assembled pin and hole. A comparison is made between the effects of choosing the optional material condition MMC and not choosing it with the tolerances that determine the allowable variations in position.

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