Mechanics of Materials Laboratory Course

This book is designed to provide lecture notes (theory) and experimental design of major concepts typically taught in most Mechanics of Materials courses in a sophomore- or junior-level Mechanical or Civil Engineering curriculum. Several essential concepts that engineers encounter in practice, such as statistical data treatment, uncertainty analysis, and Monte Carlo simulations, are incorporated into the experiments where applicable, and will become integral to each laboratory assignment. Use of common strain (stress) measurement techniques, such as strain gages, are emphasized. Application of basic electrical circuits, such as Wheatstone bridge for strain measurement, and use of load cells, accelerometers, etc., are employed in experiments. Stress analysis under commonly applied loads such as axial loading (compression and tension), shear loading, flexural loading (cantilever and four-point bending), impact loading, adhesive strength, creep, etc., are covered. LabVIEW software with relevant data acquisition (DAQ) system is used for all experiments. Two final projects each spanning 2‒3 weeks are included: (i) flexural loading with stress intensity factor determination and (ii) dynamic stress wave propagation in a slender rod and determination of the stress‒strain curves at high strain rates.

The book provides theoretical concepts that are pertinent to each laboratory experiment and prelab assignment that a student should complete to prepare for the laboratory. Instructions for securing off-the-shelf components to design each experiment and their assembly (with figures) are provided. Calibration procedure is emphasized whenever students assemble components or design experiments. Detailed instructions for conducting experiments and table format for data gathering are provided. Each lab assignment has a set of questions to be answered upon completion of experiment and data analysis. Lecture notes provide detailed instructions on how to use LabVIEW software for data gathering during the experiment and conduct data analysis.