Baseball Ballistics by James Pate Williams, Jr., BS, BS, MSwE, PhD

There are analytic equations that are applicable to the trajectory of a batted or thrown baseball:

Click to access 04-LAJPE-782_Chudinov.pdf

I created a C# application to test the preceding equations against numerical methods of calculating the trajectory of a baseball. The baseball has an initial velocity of 90 miles per hour and an angle of inclination of 20 degrees. The classical model certainly overestimates the trajectory.

Siacci’s Method by James Pate Williams, Jr. BA, BS, MSwE, PhD

Siacci’s Method Chapter 5 and Appendix A of “Exterior Ballistics, 1935” by Lieutenant Commander Ernest Edward Herrmann of the United States Naval Academy. This is an approximate technique for solving exterior ballistics trajectories with between 12 to 15 degrees of elevation. The artillery is the 16 inch / 50 caliber rifled guns of the Iowa class of fast battleships (BB-61 USS Iowa, BB-62 USS New Jersey, BB-63 USS Missouri, and BB-64 USS Wisconsin).

Range Table 0Range Table 2Range Table 1ExteriorBallisticsRK5 Main Form

 

My Near-Term Agenda by James Pate Williams, Jr. BA, BS, MSwE, PhD

Merry Christmas to all you devout Christians. I am not one of you. I am about to embark on a mission to carefully annotate with open source C# computer code my copy of “Exterior Ballistics, 1935” by Professor Ernest Edward Herrmann of then the United States Naval Academy at Annapolis, Maryland. This book set the standard for naval gunnery in World War II. Of course, our navy and especially our battle-wagons had the largest rifled artillery of any United States service. The 105 mm = 105 mm / 25.4 mm / inch = 4.13 inches, 120 mm / 25.4 mm / inch = 4.72 inches, and 155 mm / 25.4 mm / inch = 6.10 inch of our excellent United States Army and United States Marine Corps (semper fidelis) are puny in comparison to the mighty 8, 10, 12, 14, and finally 16 inch mostly rifled artillery of our incredible navy’s cruisers, dreadnoughts, and battleships of the World War I and World War II era ships. Even a destroyer of the USN Fletcher class had 5-inch (127 mm) / 38 caliber rifled artillery which had a 5 inch * 38 = 190-inch barrel length. Our mightiest naval artillery was, of course, my favorite the mighty 16 inch (406.4 mm) / 50 caliber rifles that had a barrel length of 16 * 50 inches = 800 inches = 66.6 feet!

Thanks,

James Pate Williams, Jr.

Bachelor of Arts Chemistry LaGrange College 1979

Bachelor of Science Computer Science LaGrange College 1994

Master of Software Engineering Auburn University 2000

Doctor of Philosophy Computer Science Auburn University 2005

Gratis Open Source Computer Software Developer Since Summer 1978

1980 – 1983 Graduate Work in Chemistry and Mathematics at Georgia Tech

A Current Website I developed for my friends Wesley “Wes” and Missy Cochran:

http://thecochrancollection.com/Home

Powers of Two – Excel by James Pate Williams, Jr. BA, BS, MSwE, PhD

First Function in Excel (Assumes that You Have Access to an Office 365 Subscription)

Please attempt the following procedure:

  1. Type Excel in the Windows 10 Search Box
  2. Select the Excel App
  3. Select Blank workbook
  4. Maximize the Excel Window
  5. Type x in Cell A1
  6. Tab to Cell B1
  7. Type y in Cell B1
  8. Type 0 in Cell A2
  9. Type 1 in Cell B2
  10. Type 1 in Cell A3
  11. Type 2 in Cell B3
  12. Type 2 in Cell A4
  13. Type 4 in Cell B4
  14. Type 3 in Cell A5
  15. Type 8 in Cell B5
  16. Type 4 in Cell A6
  17. Type 16 in Cell B6
  18. Type 5 in Cell A7
  19. Type 32 in Cell A8
  20. Highlight Cells A1 and B1
  21. From the Toolbar Select Alignment and Right Alignment
  22. Select File Save As
  23. Select “Documents” and “Powers of Two” as the filename
  24. Highlight Cells A1 to B7
  25. Select Insert from Toolbar
  26. Select Charts Scatter
  27. Select the Chart
  28. Select the Big + Sign on the Right
  29. Label the y-axis “y = 2 ^ n”
  30. Label the x-axis “n”
  31. Relabel the Title of the Chart as “Powers of Two”

Note that x is in the finite set { 0, 1, 2, 3, 4, 5 }

Note that y is the function y = 2 ^ x where ^ is the exponentiation operator

Powers of Two TablePowers of Two Chart

Global Primary Greenhouse Gas Concentrations by James Pate Williams Jr BA, BS, MSwE, PhD

I designed and implemented a C# computer language application to model the global greenhouse gas concentrations data found on the NOAA website:

https://www.esrl.noaa.gov/gmd/aggi/aggi.html

I used the latest recommended data for time period 1979 to 2017. The concentrations of three greenhouse gases were modeled: carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).

The empirical modeling paradigm I used was simple linear regression. My model goes out to the year 2300. The key formulas used by the model are:

                                Simple Linear Regression Parameters

See the website:

https://en.wikipedia.org/wiki/Simple_linear_regression

Some plots of the concentrations in parts per million (PPM) and parts per billion (PPB) are given below.

                                                Carbon Dioxide Concentration in Parts Per Million
                                                        Methane Concentration in Parts Per Billion
                                                 Nitrous Oxide Concentration in Parts Per Billion
                                             Carbon Dioxide Concentration in Parts Per Million
                                                      Methane Concentration in Parts Per Billion
                                                   Nitrous Oxide Concentration in Parts Per Billion
              Simple Linear Regression Parameters
              Simple Linear Regression Parameters
             Simple Linear Regression Parameters
                                                         Greenhouse Gas Concentrations Table

NOAA Contiguous United States of America Precipitation by James Pate Williams Jr BA, BS, MSwE, PhD

I designed and implemented a C# computer language application to model the precipitation data found on the NOAA website:

https://www.ncdc.noaa.gov

I used the latest recommended data for time period 1895 to 2017. The empirical modeling paradigm I used was simple linear regression. My model goes out to the year 2300. The key formulas used by the model are:

Simple  Linear Regression Equations

See the website:

https://en.wikipedia.org/wiki/Simple_linear_regression

Some plots of the contiguous U.S. precipitation are shown below. The climate is getting wetter thus some parts of the U.S.maybe more prone to floods.

Precipitation Plot
Precipitation Plot
Precipitation Plot
Precipitation Plot
Precipitation Plot
Precipitation Plot
Precipitation Plot
Simple Linear Regression Parameters
Precipitation Table Experimental and Theoretical Values

NOAA Contiguous United States of America Temperature Anomaly by James Pate Williams Jr BA, BS, MSwE, PhD

I designed and implemented a C# computer language application to model the temperature anomaly data found on the NOAA website:

https://www.ncdc.noaa.gov

I used the latest recommended data for time period 1895 to 2017. The empirical modeling paradigm I used was simple linear regression. My model goes out to the year 2300. The key formulas used by the model are:

Simple Linear Regression Equations

See the website:

https://en.wikipedia.org/wiki/Simple_linear_regression

Below are some plots of the temperature anomaly.

Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
Temperature Anomaly Actual Anomaly in Red Theoretical in Blue
C# Application Main Form
Simple Linear Regression Parameters
Table Function Form with Experimental and Theoretical Anomalies