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David J. Lovell Associate Professor |
1173 Glenn L. Martin Hall, College Park, MD, 20742 Phone: (301) 405-7995 Fax: (301) 405-2585 email: lovell@umd.edu
Department
of Civil and Environmental Engineering Institute for Systems Research Applied
Mathematics & Statistics, and Scientific Computation Program Engineers Without Borders
TEACHING
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Spring 2010 ENCE 402 - Simulation and Design of Experiments. Review of statistics and hypothesis testing, sample
design and design of experiments, generation of discrete and continuous distributions
and their applications. Introduction of simulation languages and simulation
of discrete and continuous engineering systems. Output analysis, model
validation and sensitivity and reliability analysis. ENCE 289i - Engineering in the Developing World. Survey of engineering methods to provide basic human
needs - food, water, shelter, clothing, energy, and transportation - in the
developing world. Lessons learned from the developed world. Close interaction
with the student chapter of Engineers Without Borders. |
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Summer 2010 ENES 100 (Young Scholars Program)
- Introduction to Engineering Design.
Students work in teams to design and build predator and prey robot platforms. |
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Fall 2010 ENES 100 - Introduction to
Engineering Design.
Students work in teams to design and build hovercraft. ENCE 289j – Planes, Trains and
Automobiles: Transportation Innovation.
A historical perspective on innovations largely
associated with transportation technologies. From manufacturing improvements
ushered in by the boom of automobile sales to control, communications, and
propulsion innovations in rail systems to advances in noise control and
engine emissions coupled with the aviation industry. Also offers insight into
how the public need for mobility has driven various fields of science to
innovative solutions to difficult problems. |
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Spring 2011 ENCE 302 - Probability and Statistics for Civil
and Environmental Engineers. Statistics is the science of
data. Civil Engineers must often make decisions based on incomplete, variable
or uncertain information. In addition, modern methods of design and analysis
need to account for variability in natural, engineered and human systems.
After successful completion of this class, a student should have facility and
familiarity with established basic techniques for managing data, modeling
variability and uncertainty, communicating about data and decisions, and
supporting or defending a decision or judgment based on uncertain or
incomplete data. |