- Engineering Building III (EB3) 4172
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Research Area: Dynamics, modern physics, system modeling and algorithm development
I am a dynamicist. I study motion at its most basic level and sometimes it is almost against common sense; at times it appears strange and surprising. As it pertains to computational modelling, one of the large challenges lies in integrating the disciplines and the phases of matter, so I study that, too. On that subject, I teach the course entitled Discrete Element Method (MAE 789). The method is a modern computational approach to two-scale modeling which compliments the more traditional Finite Element Method which is a single-scale method. The majority of my published work deals with advancements at the applied level. Along these lines, there is a growing need for algorithm development, like in autonomous operation of robotic systems. Much of my work in this area addresses issues with unmanned systems, mostly with aerial systems. I also teach the course entitled Mechatronics (MAE 320). In this introductory course, students learn how to integrate electronics and computer algorithms into hardware, then they form small teams and build their own electromechanical systems.
Speaker on basic physics and recent developments
November 29, 2021, video (by Noah Gassner), “The concept of impetus: a new twist on an old idea”
September 14, 2021, Congratulations to Jin Peng for winning the 2021 GTI Summer Program’s Class Poster Competition (video trailer), “Geocentric versus heliocentric”
April 20, 2021, video (by Ricky Puyana), “Particles and waves are not the fundamentals of our universe: modern theory of impetus”
Jan 4, 2021, magazine article, “Fragments of energy – not waves or particles – may be the fundamental building blocks of the universe.”
Basic research that advances the space-time framework that governs physical behavior. This research builds on recent developments in four-dimensional geometry and in four-dimensional vector fields.
This is joint research with Dr. Jeffrey Eischen and others with the assistance of students.
Namibia Wildlife Aerial Observatory (WAO):
A unique study-abroad program in which field units of undergraduate students spend a semester flying unmanned aerial vehicles over large, endangered animals in an animal reserve for the purposes of studying them and to better understand how to protect them
Each field unit collects aerial data to answer a research question, doing so under the guidance of a graduate research assistant.
Joe Manning, PhD candidate, deployment of aerial technologies in private and public organizations
Andrew Zulu, PhD candidate, unmanned aerial systems for anti-poaching
Pawel Obyrcki, MS candidate, unmanned aerial systems for animal counting in Africa
STUDENTS INTERESTED IN NAMIBIA WAO STUDY-ABROAD (FOR FALL 2022)
Discrete Element Method:
Research that concerns the development of the DEM method
Stephen Coppola, PhD candidate, advancement of the DEM method
Research that concerns the development of algorithms for motion control
Michael Picinich, MS candidate, development of a heliocopter (quad copter with a central propeller)
An extracurricular activity that began more then twenty years ago with the development of a suite of simulation tools that accurately predict the trajectory of a basketball, its collisions with the backboard and rim, and statistically analyze the probability of a shot.
The tools are applied to best practices in the free throw and the bank shot. This is a joint project with Dr. Chau Tran and with the assistance of many students.
Larry M. Silverberg (2008), “Unified Field Theory for the Engineer and the Applied Scientist,” J. Wiley, Inc. ISBN-13: 978-3527407880
Larry M. Silverberg and J. P. Thrower (2001) “Mark’s Mechanics: Problem-Solving Companion,” McGraw Hill Book Co. ISBN 0-07-136278-9
Virginia Polytechnic Institute
Virginia Polytechnic Institute
Virginia Polytechnic Institute
My basic research focuses on advancing the space-time framework that governs physical behavior. My applied research contributes to dynamic system modeling and develops algorithms for dynamic systems.
- Isotropic packing algorithm for particle simulations
- Coppola, S., & Silverberg, L. M. (2021), INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING. https://doi.org/10.1002/nme.6742
- Artificial Lumbered Flight for Autonomous Soaring
- Powers, T. C., Silverberg, L. M., & Gopalarathnam, A. (2020), JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 43(3), 553–566. https://doi.org/10.2514/1.G004397
- On a new field theory formulation and a space-time adjustment that predict the same precession of Mercury and the same bending of light as general relativity
- Silverberg, L. M., & Eischen, J. W. (2020), PHYSICS ESSAYS, 33(4), 489–512. https://doi.org/10.4006/0836-1398-33.4.489
- A New System Development Framework Driven by a Model-Based Testing Approach Bridged by Information Flow
- Zhu, D., Pritchard, E. G. D., & Silverberg, L. M. (2018), IEEE SYSTEMS JOURNAL, 12(3), 2917–2924. https://doi.org/10.1109/JSYST.2016.2631142
- Gender comparison in consistency in the basketball free throw by an event-driven approach
- Silverberg, L. M., Tran, C. M., & Laue, C. (2018), SPORTS ENGINEERING, 21(4), 333–340. https://doi.org/10.1007/s12283-018-0276-z
- Cellular growth algorithms for shape design of truss structures
- Tschida, C. E., & Silverberg, L. M. (2013), Computers and Structures, 116, 1–6. https://doi.org/10.1016/j.compstruc.2012.10.006
- Optimal Targets for the Bank Shot in Mens Basketball
- Silverberg, L. M., Tran, C. M., & Adams, T. M. (2011), Journal of Quantitative Analysis in Sports, 7(1). https://doi.org/10.2202/1559-0410.1299
- Autonomous soaring: The montague cross-country challenge
- Edwards, D. J., & Silverberg, L. M. (2010), Journal of Aircraft, 47(5), 1763–1769. https://doi.org/10.2514/1.c000287
- Control of underwater vehicles in full unsteady flow
- Levedahl, B. A., & Silverberg, L. (2009), IEEE Journal of Oceanic Engineering, 34(4), 656–668. https://doi.org/10.1109/JOE.2009.2027798
- Fourier series of half-range functions by smooth extension
- Morton, J., & Silverberg, L. (2009), Applied Mathematical Modelling, 33(2), 812–821. https://doi.org/10.1016/j.apm.2007.12.009