Closure to “Discussion of ‘Stochastic Characterization of Macro- and Microerrors of Journal Bearing Roundness’” (1977, ASME J. Eng. Ind., 99, pp. 334–335)

1977 ◽  
Vol 99 (2) ◽  
pp. 335-335
Author(s):  
B. Velsher ◽  
M. O. M. Osman ◽  
T. S. Sankar
Keyword(s):  
Journal Bearing ◽  
Stochastic Characterization

Stochastic Characterization of Macro- and Microerrors of Journal Bearing Roundness

1977 ◽  
Vol 99 (2) ◽  
pp. 327-334 ◽  
Author(s):  
B. Velsher ◽  
M. O. M. Osman ◽  
T. S. Sankar
Keyword(s):  
Journal Bearing ◽  
Form Error ◽  
Measuring Device ◽  
New Approach ◽  
Measuring Devices ◽  
Stochastic Characterization ◽  
Round Surface ◽  
Hybrid Computer ◽  
The Mathematical Model

A new approach for the characterization of form error and surface roughness of round bearings is presented. The method employs the theory of random function excursions to describe the macro- and microerrors of the round surface in both radial and circumferential directions. The mathematical principle of the measuring technique is given, and it is shown that an accurate description of the roundness can be obtained from the knowledge of the intercept probabilities of the crest and valley excursions of the surface trace about a given reference circle. Based on the mathematical model, new indices for the characterization of journal bearing roundness are proposed. These indices are computed directly from data obtained from commercially available roundness measuring devices. A number of experiments were performed to justify the validity of the proposed roundness indices. Roundness measurements were carried out on a number of differently machined cylinders using a specially equipped measuring device (Talyrond 51) with a link to a hybrid computer EAI-690. The theoretically computed indices compared favorably with the measurements made on the actual round surfaces.

A stochastic characterization of Loewner optimality design criterion in linear models

Metrika ◽  
2001 ◽  
Vol 53 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Erkki P. Liski ◽  
Alexander Zaigraev
Keyword(s):  
Linear Models ◽  
Design Criterion ◽  
Stochastic Characterization

On Stochastic Characterization of Temporal Storm Patterns

1984 ◽  
Vol 16 (8-9) ◽  
pp. 147-153 ◽  
Author(s):  
Van-Thanh-Van Nguyen
Keyword(s):  
Markov Chain ◽  
Probability Distributions ◽  
First Order ◽  
Stochastic Characterization ◽  
Order Markov Chain ◽  
Hourly Rainfall ◽  
General Stochastic Model ◽  
Storm Rainfall ◽  
Rainfall Occurrences

The present study, a continuation of a previous work by the author, suggests a new theoretical approach to the characterization of the temporal pattern of storms. A storm is defined as a continuous run of non-zero one-hour rainfall depths. A general stochastic model is developed to determine the probability distributions of cumulative storm rainfall amounts at successive time intervals after the storm began. The previous model for characterizing storm temporal patterns was based on the assumption that hourly rainfall depths were independent and identically exponentially distributed random variables, while sequences of wet hours were modeled by a first-order stationary Markov chain. Hence, the model did only introduce dependence of wet hour occurences into the rainfall process through the first-order Markov chain. The present paper proposes a more general model that can take into account both the persistence in hourly rainfall occurrences and the dependence between successive hourly rainfall depths. Results of an illustrative example show that by accounting for the correlation structure of consecutive rainfall depths the present model gives a better fit to the observations than the previous one.

Stochastic characterization of space-time precipitation: Implications for remote sensing

1994 ◽  
Vol 17 (1-2) ◽  
pp. 47-59 ◽  
Author(s):  
Juan B. Valdés ◽  
Eunho Ha ◽  
Chulsang Yoo ◽  
Gerald R. North
Keyword(s):  
Remote Sensing ◽  
Space Time ◽  
Stochastic Characterization

Stochastic Characterization of Epoxies to Predict Performance Uncertainty of Photonic Packages

2004 ◽  
Author(s):  
S. Radhakrishnan ◽  
G. Subbarayan ◽  
L. Nguyen ◽  
W. Mazotti
Keyword(s):  
Analytical Model ◽  
Stochastic Analysis ◽  
Coupling Efficiency ◽  
Viscoelastic Behavior ◽  
Material Behavior ◽  
Considerable Uncertainty ◽  
Stochastic Characterization ◽  
Degree Of Confidence ◽  
Extensive Experimental Data

There is considerable uncertainty in the prediction of performance of a system mainly due to idealizations in geometry, material behavior, and loading history. Uncertainties in geometry can be predicted and controlled using tighter tolerances. However, the models currently used to describe material behavior are mostly deterministic. To predict the coupling efficiency of a photonic system to greater degree of confidence, stochastic analysis procedures are necessary. As part of this analysis, the behavior of materials must be stochastically characterized. In this paper, we present extensive experimental data on thermally and UV-cured epoxies typically used in photonic packages to enable stochastic analysis. The test data includes the viscoelastic behavior. We present analytical model to obtain the variation in the displacement of the epoxies resulting from its stochastic viscoelastic behavior. We utilize the analytical model to predict the uncertainty in the coupling efficiency of a generic photonic package.

scholarly journals A Stochastic Characterization of the Capture Zone in Pursuit-Evasion Games

Games ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 54
Author(s):  
Simone Battistini
Keyword(s):  
Optimal Strategies ◽  
Capture Zone ◽  
Pursuit Evasion ◽  
Guidance Strategies ◽  
Stochastic Characterization ◽  
Evasion Game ◽  
Multi Agent ◽  
Planning Problems ◽  
Insight Into

Pursuit-evasion games are used to define guidance strategies for multi-agent planning problems. Although optimal strategies exist for deterministic scenarios, in the case when information about the opponent players is imperfect, it is important to evaluate the effect of uncertainties on the estimated variables. This paper proposes a method to characterize the game space of a pursuit-evasion game under a stochastic perspective. The Mahalanobis distance is used as a metric to determine the levels of confidence in the estimation of the Zero Effort Miss across the capture zone. This information can be used to gain an insight into the guidance strategy. A simulation is carried out to provide numerical results.

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