Offered :

  • Course I Fall 2004:


  • Course II Winter 2005:

This course will build on concepts learned from Course I and will rely heavily on computer simulations to solve problems without closed-form solutions

  • Course III Spring 2005:

This course will be directed to advanced undergraduate students and graduate students looking to apply the concepts of natural selection at work in the natural world with the evolution of human-made machines.


MEM Courses

Applied Engineering Analysis I

Dynamics: MEM 238

Materials: TDEC 211

Freshman Design

MEM Senior Design

UNIV 101


Planned Course I:

Vectors and Tensors for Multiscale Biomechanics

Textbooks: Advanced Engineering Mathematics
Vectors and Tensors in Engineering and Physics

This course will focus on Ordinary Differential Equations, Linear Algebra Methods, LaPlace and Fourier Transform Methods, and Statistics. All concepts used in the text are developed within the text itself and extended to challenging problems relying on a deep understanding of the concepts and offering the student a sense of satisfaction in having attained a thorough grasp of the content. The mathematics presented is applied across several disciplines including Hookean solids, Newtonian dynamics, Navier-Stokes fluid mechanics, and Special and General Relativity. This text also has excellent extensibility to computational mechanics as it relies heavily on linearization, and index notation.


New Course II:

Statistical Numerical Modeling for Interdisciplinary Biomechanical Science and Engineering.

This course will build on concepts learned from Course I and will rely heavily on computer simulations to solve problems without closed-form solutions. Students will be taught the concepts of deterministic vs. stochastic systems (Gallager, 1996). This course will focus primarily on the statistical mechanics involved in describing nano-scale systems (Rieth, 2003). Boltzman statistics, Brownian motion, energy minimization, second law of thermodynamics, diffusion and self-assembly will all be covered. Stochastic based transport theory and self-assembly will also be covered. A course such as this is a critical component to any advanced undergraduate student or doctoral student, in that they will realize that the traditional classical deterministic models typically taught at the undergraduate level break down when one begins to consider nano-scale phenomena. This will be a valuable course for engineering students and medical students wanting to know how to model biophysical phenomena.

New Course III: MechanoEvolution

How early molecular winners affect our lives on a daily basis. This course will be directed to advanced  undergraduate students and graduate students looking to apply the concepts of natural selection at work in the natural world with the evolution of human-made machines. Excerpts will be taken from Jared Diamond’s The Third Chimpanzee (Diamond, 1992), With-hold Rybczynski’s One Good Turn: A Natural History of the Screwdriver and the Screw (Rybczynski, 2000), A.G. Cairns-Smith’s Seven Clues to the Origin of Life (Cairns-Smith, 1990), and Henry Petroski’s The Evolution of Useful Things (Petroski, 1994).

Drexel has a strong reputation for design. Students begin design in their freshman year, and culminate their engineering studies with Senior Design project, frequently in conjunction with a local engineering firm. A focus of this course will be to evaluate a design’s relevance: Does it serve a purpose in today’s economic and social environment? Students taking this class will not only start to assess the natural progression of human-made artifacts, but will look at the rate at which we as a species are changing the natural landscape (Gleick, 1999) and where we may expect to go as a species (Kurzweil, 1999).

Optimization theory will be explored as will game theory. Additionally models for minimization of stress/maximization of strength within mechanical structures will explored with existing software and with codes devised by students within Matlab® and Mathematical®. The course itself will hopefully evolve into one in which students create virtual molecular worlds that have self-assembling structural and motor proteins that fight for survival on the nanoscale based on models such as those by (Hill, 1987), then evolve into larger structures that fight for the survival of their genes. The point will be made of how early molecular winners affects our lives on a daily basis (Dawkins, 1989), and will also teach the points of spending time up front to solve a problem that lies in the future. Other ideas that will be discussed are the limits of the sustainability of complexity. The sustainability of current information technologies will also be addressed to incorporate information theory (Yockey, 1992; Avery, 2003; Yockey, 2004) and the hypothesis that computation machines, like brains are merely nothing more than machines that turn data in to heat and information. One concept that student will also be exposed to that is unconventional for engineering students is that there is no goal of evolution. Survival is the only measure of success, not who is the fastest, smartest, strongest necessarily. A poignant example is that of the Coelacanth fish where a slow, average fish with probably little brain wattage has been able to survive for millennia without competition presumably due to its relatively low metabolism and ability to live in a niche environment. An overall theme of the class which will be explored is the apparent paradox that Life appears to be beating entropy at its own game. This will be addressed from a quantitative standpoint to look at how accrual of more tools or weapons (a machine or technology advantage) by one group can lead to a landslide victory over another. The prospect that there essentially is no way to escape the technological path we have “chosen” for ourselves will be explored as will the ethical question of whether “developing nations” really need to develop and what if any role our own “highly developed” society should take in this endeavor. Students will learn that there is perhaps some optimal level of complexity: if you are too complex you cannot sustain, too simple you are consumed.



Bradley Edward Layton | Research | Publications | Teaching | People | Lab Tour | Resources
Department of Mechanical Engineering and Mechanics
 Room 151G Curtis Hall, 3141 Chestnut Street, Philadelphia, PA 19104-2884
 Continuously updated  2004 Bradley Edward Layton