0 or 4 credits
Fall 2026 Lecture Upper Division
An introduction to the relationships between fundamental structure of materials and their properties presented through a combination of materials science and engineering approaches. Emphasis on materials of particular interest for civil engineering applications, including metals, aggregates, portland cement concrete, bituminous materials, asphalt binders, asphalt mixtures, wood, polymers, composites, and masonry. Laboratory exercises illustrate atomic structure, elastic and inelastic properties, and demonstrate applications of selected principles of mechanics, testing of aggregates, as well as designing and testing of asphalt and concrete mixtures.
Learning Outcomes1Formulate equations that describe the properties of composite materials based on boundary conditions, assumptions and constituent properties.
2Design and conduct experiments, as well as to analyze and interpret data.
3Use non-destructive tests to estimate material properties.
4Use non-destructive test to locate flaws in engineering systems.
5Compare and contrast strength of materials and fracture mechanics solutions.
6Use mathematics, science and engineering principles to estimate the influence of cracks on the mechanical response of engineering materials.
7Use scientific and engineering principles to predict the elastic and viscoelastic of a material.
8Interpret engineering properties from test data.
9Use standardized test procedures to describe the properties of engineering materials.
10Use mathematical, scientific and engineering principles to compute the influence of material proportions on the structure property relationships for concrete materials.
11Design the proportions for a concrete mixture.
12Explain the relationship between the properties of an asphalt mixture and its performance.
13Select engineering materials for specific applications.
14Communicate effectively using graphs.
15Communicate effectively using an executive summary.
16Communicate effectively using an engineering report.
17Communicate the expected accuracy obtained from engineering data.
Prerequisites
made by Purdue students.