Statistics

1706 Submissions

[8] viXra:1706.0551 [pdf] submitted on 2017-06-30 03:09:09

The Recursive Future And Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure Considered To Exhaustion {File Closing Version+2} ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 7 Pages.

In this research investigation, the author has presented a Recursive Past Equation and a Recursive Future Equation based on the Ananda-Damayanthi Normalized Similarity Measure considered to Exhaustion [1] (please see the addendum of [1] as well).
Category: Statistics

[7] viXra:1706.0425 [pdf] replaced on 2017-10-17 16:05:40

The Moment-Generating Function of Normal Variate Functionals Using the Star Probability Measure

Authors: Yuri Heymann
Comments: 14 Pages.

The motivation of this study is to investigate new methods for the calculation of the moment-generating function of the lognormal distribution. Taylor expansion method on the moments of the lognormal suffers from divergence issues, saddle-point approximation is not exact, and integration methods can be complicated. In the present paper we introduce a new probability measure that we refer to as the star probability measure as an alternative approach to compute the moment-generating function of normal variate functionals such as the lognormal distribution.
Category: Statistics

[6] viXra:1706.0379 [pdf] submitted on 2017-06-19 00:46:33

The Recursive Future And Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure Considered To Exhaustion {File Closing Version}

Authors: Ramesh Chandra Bagadi
Comments: 7 Pages.

In this research investigation, the author has presented a Recursive Past Equation and a Recursive Future Equation based on the Ananda-Damayanthi Normalized Similarity Measure considered to Exhaustion [1] (please see the addendum of [1] as well).
Category: Statistics

[5] viXra:1706.0295 [pdf] submitted on 2017-06-16 05:25:45

One Step Forecasting Model (Advanced Model - Version 5)

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research investigation, the author has presented an Advanced Forecasting Model.
Category: Statistics

[4] viXra:1706.0279 [pdf] replaced on 2017-08-28 09:11:45

Statistical Characterization of the Time to Reach Peak Heat Release Rate for Nuclear Power Plant Electrical Enclosure Fires

Authors: Raymond H.V. Gallucci
Comments: 10 Pages.

Since publication of NUREG/CR-6850 (EPRI 1011989), EPRI/NRC-RES Fire PRA Methodology for Nuclear Power Facilities in 2005, phenomenological modeling of fire growth to peak heat release rate (HRR) for electrical enclosure fires in nuclear power plant probabilistic risk assessment (PRA) has typically assumed an average 12-minute rise time. [1] One previous analysis using the data from NUREG/CR-6850 from which this estimate derived (Gallucci, “Statistical Characterization of Cable Electrical Failure Temperatures Due to Fire, with Simulation of Failure Probabilities”) indicated that the time to peak HRR could be represented by a gamma distribution with alpha (shape) and beta (scale) parameters of 8.66 and 1.31, respectively. [2] Completion of the test program by the US Nuclear Regulatory Commission (USNRC) for electrical enclosure heat release rates, documented in NUREG/CR-7197, Heat Release Rates of Electrical Enclosure Fires (HELEN-FIRE) in 2016, has provided substantially more data from which to characterize this growth time to peak HRR. [3] From these, the author develops probabilistic distributions that enhance the original NUREG/CR-6850 results for both qualified (Q) and unqualified cables (UQ). The mean times to peak HRR are 13.3 and 10.1 min for Q and UQ cables, respectively, with a mean of 12.4 min when all data are combined, confirming that the original NUREG/CR-6850 estimate of 12 min was quite reasonable. Via statistical-probabilistic analysis, the author shows that the time to peak HRR for Q and UQ cables can again be well represented by gamma distributions with alpha and beta parameters of 1.88 and 7.07, and 3.86 and 2.62, respectively. Working with the gamma distribution for All cables given the two cable types, the author performs simulations demonstrating that manual non-suppression probabilities, on average, are 30% and 10% higher than the use of a 12-min point estimate when the fire is assumed to be detected at its start and halfway between its start and the time it reaches its peak, respectively. This suggests that adopting a probabilistic approach enables more realistic modeling of this particular fire phenomenon (growth time).
Category: Statistics

[3] viXra:1706.0191 [pdf] submitted on 2017-06-15 02:21:37

The Recursive Future And Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure Considered To Exhaustion {Latest Super Ultimate Version}

Authors: Ramesh Chandra Bagadi
Comments: 10 Pages.

In this research investigation, the author has presented a Recursive Past Equation and a Recursive Future Equation based on the Ananda-Damayanthi Normalized Similarity Measure considered to Exhaustion [1] (please see the addendum of [1] as well).
Category: Statistics

[2] viXra:1706.0190 [pdf] submitted on 2017-06-15 03:22:48

The Recursive Future And Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure Considered To Exhaustion {Latest Correct Version}

Authors: Ramesh Chandra Bagadi
Comments: 8 Pages.

In this research investigation, the author has presented a Recursive Past Equation and a Recursive Future Equation based on the Ananda-Damayanthi Normalized Similarity Measure considered to Exhaustion [1] (please see the addendum of [1] as well).
Category: Statistics

[1] viXra:1706.0017 [pdf] submitted on 2017-06-03 04:27:45

The Recursive Future And Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure Considered To Exhaustion (New Version 4)

Authors: Ramesh Chandra Bagadi
Comments: 10 Pages.

In this research investigation, the author has presented a Recursive Past Equation and a Recursive Future Equation based on the Ananda-Damayanthi Normalized Similarity Measure considered to Exhaustion [1].
Category: Statistics