CBEMS 163 Computer Techniques in Experimental Materials Research (2012-2013)

CBEMS 163 Computer Techniques in Experimental Materials Research

(Not required for any major. Selected Elective for ChE and MSE.)
Catalog Data:

CBEMS 163 Computer Techniques in Experimental Materials Research (Credit Units: 3) Principles and practical guidelines of automated materials testing. Computer fundamentals, programming languages, data acquisition and control hardware, interfacint techniques, programming strategies, data analysis, data storage, safeguard procedures. Concurrent with ENGRMSE 263. (Design units: 1)

Required Textbook:
Recommended Textbook:
  • J. D. Beasley, Practical Computing for Experimental Scientists, Oxford Science Publications, 1988.
  • B. E. Cline, Automated Data Acquisition, Petrocelli Books, 1983.
  • L. M. Mezei, Practical Spreadsheet Statistics & Curve Fitting for Scientists and Engineers, Prentice Hall, 1990.
  • C. E. Pearson, Numerical Methods in Engineering and Science, Van Nostrand Reinhold Company, 1986.
James C. Earthman
Relationship to Student Outcomes
No student outcomes specified.
Course Learning Outcomes. Students will:

1. Design software, interface connections, and procedures to incorporate the use of computers in experimental research activities. Perform data analysis that includes sampling techniques, noise reduction, regression analysis, numerical methods, graphics. Evaluate what laboratory automation schemes are worth pursuing and what the potential benefits are.

2. Function on multi-disciplinary teams Formulate and solve materials and engineering problems both individually and in groups using computer techniques.

3. Communicate effectively (writing and presenting projects).

4. Recognize the need for life-long learning.

5. Understand contemporary issues relevant to the application of computer techniques to materials research.

Prerequisites by Topic
Lecture Topics:
  • Computer Fundamentals: Binary Representation of Numbers, Character Code, Computer Organization and Operation, Programming Languages.
  • Programming Techniques: Virtual Instrumentation Using Labview, Structured Programming and Subroutines, Testing and Debugging, Experimental Control, Data Storage, Failsafe Measure.
  • Data Acquisition and Control Hardware: A/D Converters, D/A Converters, Digital Voltmeters, Multiplexers, Counters.
  • Communication Fundamentals: Interfaces, Interrupts, Buffered I/O, Direct Memory Access, Digital I/O, Analog I/O. Data Analysis: Sampling Techniques, Noise Reduction, Regression Analysis, Numerical Methods, Graphics. Quantitative Image Analysis: Digitizing Images, Producing a Binary Image, Measurement Techniques, Data Analysis and Representation
Class Schedule:

Meets for 3 hours of lecture each week for 10 weeks.

Computer Usage:

Students perform all homework and project assignments using computers.

Laboratory Projects:

Students conduct a final project that involves developing software for computer-based data acquisition and analysis.

Professional Component

This course contributes towards the Materials Science Engineering major through the Engineering Topics courses.

Design Content Description

Students design software in both homework and project assignments. Software and interface design are regularly discussed and demonstrated in lectures with the aid of a computer projector. Students design software for data acquisition and analysis for an existing experimental system.

Lectures: 70%
Laboratory Portion: 30%
Grading Criteria:
  • Homework: 40%
  • Design Project: 60%
  • Total: 100%
Estimated ABET Category Content:

Mathematics and Basic Science: 0.0 credit units

Computing: 0.0 credit units

Engineering Topics: 3.0 credit units

Engineering Science: 2.0 credit units

Engineering Design: 1.0 credit units

July 9, 2012
Senate Approved:
February 9, 2004
Approved Effective:
2004 Fall Qtr