Engineering (ENGR)

Introduction to the engineering profession, ethics, and disciplines; development of skills in teamwork, problem solving and design; other topics include computer applications and programming; Newton's laws, unit conversions, statistics. Offering: Fall and Spring.

Prerequisite: MATH 1314.

Topics include, depending on the major: emphasis on computer applications and programming and solids modeling using CAD tools or other software; fundamentals of engineering science; advanced graphic skills. Pre-req: MATH 1314 - College Algebra or equivalent academic preparation. Offered Fall and Spring.

Prerequisite: MATH 1314.

2 Lab hours, 0 Semester Credit Hours. General problem-solving techniques for Engineering students in the context of Statics topics and problems. ENGR 2325 and ENGR 2025 must be taken together in the same semester. ENGR 2025 is not counted toward graduation.

Laboratory experiments supporting theoretical principles presented in ENGR 2305 involving DC and AC circuit theory, network theorems, time, and frequency domain circuit analysis. Introduction to principles and operation of basic laboratory equipment; laboratory report preparation.

Prerequisite: ENGR 2305^*.
^* May be taken concurrently.

Basic laboratory experiments supporting theoretical principles presented in ENGR 2306 involving design, construction, and analysis of combinational and sequential digital circuits and systems, including logic gates, adders, multiplexers, encoders, decoders, arithmetic logic units, latches, flip-flops, registers, and counters; preparation of laboratory reports.

Principles of electrical circuits and systems. Basic circuit elements (resistance, inductance, mutual inductance, capacitance, independent and dependent controlled voltage, and current sources). Topology of electrical networks; Kirchhoff 's laws; node and mesh analysis; DC circuit analysis; operational amplifiers; transient and sinusoidal steady-state analysis; AC circuit analysis; first- and second-order circuits; Bode plots; and use of computer simulation software to solve circuit problems.

Prerequisite: PHYS 2426 and MATH 2414.

Introduction to theory and design of digital logic, circuits, and systems. Number systems, operations and codes; logic gates; Boolean Algebra and logic simplification; Karnaugh maps; combinational logic; functions of combinational Logic; flip-flops and related devices; counters; shift registers; sequential logic; memory and storage. 

Prerequisite: MATH 2305^*.
^* May be taken concurrently.

Theory of engineering mechanics involving forces, moments, and couples on stationary structures; equilibrium in two and three dimensions; free body diagrams; truss analysis; friction; centroids; centers of gravity and moments of inertia.

Prerequisite: PHYS 2425 and MATH 2414^*.
^* May be taken concurrently.

Theory of engineering mechanics involving the motion of particles, rigid bodies and systems of particles; Newton's Laws; work and energy relationships; principles of impulse and momentum; application of kinetics and kinematics to the solution of engineering problems. 

Prerequisite: ENGR 2325.

This course covers principles of electronics: charge, voltage, resistance, current, and power; Ohm's Law; Kirchhoff's voltage and current laws; RC and LC circuits; periodic functions, average and RMS measurements; transformers, electrical measurement instruments. The laboratory provides hands-on experience with devices and circuits discussed in the classroom.

Prerequisite: (PHYS 2426, MATH 2414 and 3315^*).
^* May be taken concurrently.

Fluid properties, fluid statics, dynamics, and kinematics, conservation of energy and momentum incompressible, laminar and turbulent flow. Similitude and dimensional analysis, and viscous flow. Offered: Fall Spring.

Prerequisite: MATH 3315^*, ENGR 2326 and MATH 2415.
^* May be taken concurrently.

Theory and application of energy methods in engineering; conservation of mass and energy; energy transfer by heat, work and mass; thermodynamic properties; analysis of open and closed systems; the second law of thermodynamics and entropy; gas, vapor and refrigeration cycles.

Prerequisite: (PHYS 2425 and MATH 2414).

Concepts in strength of materials, stress, strain; deformation under load, direct, shear, and combined stresses; stress concentrations, bending stresses and torsional shear stresses, deflection in beams and shafts; columns, and pressure vessels.

Prerequisite: ENGR 2325 and 3322 or ENGR 2322.

Structure and properties of metallic and nonmetallic materials; microstructure, mechanical testing, phase diagrams, heat treatment, testing, ceramics, polymers, composites, construction materials, failure analysis, nondestructive evaluation, corrosion and thermal properties of materials.

Prerequisite: (CHEM 1411 and PHYS 2425).

Introduction to metal and non-metallic manufacturing processes; casting, forging, rolling, extrusion, sheet metal forming, cutting tools turning and milling operations, abrasive machining, welding and joining, powder compaction, molding, forming of plastics, surface treatment, human factors and safety.

Prerequisite: ENGR 1312 and 3322.

Students participating in an Engineering co-op program will register for this course each off-campus work semester to maintain continuous enrollment status at TAMU-CC. Each student and the student’s supervisor will both submit to the instructor end-of-term reports at the end of the off-campus work semester. Students will receive 1 semester credit hour (SCH) for each internship semester completed. The course may be repeated; if a student takes the course three times, the student may count the 3 SCH as one technical elective. Completion of required courses in first year of student’s Engineering degree plan with at least a 3.0 GPA.

Foundations of engineering economy, cash flow and equivalence, and project justification. Introduction to project management, planning, scheduling, and control, use of project management software, GANTT charts, PERT charts, and critical path. Students prepare proposals, including specifications, timelines, schedule, and budget, for projects to be implemented in ENGR 4370 - Capstone Projects. This course should be taken the semester preceding ENGR 4370 - Capstone Projects. 

Prerequisite: (MEEN 3330 and 3345) or (EEEN 3330, 3350 and 3418^*) or (IEEN 3302 and 3320) or (CEEN 3320 and 3321).
^* May be taken concurrently.

Introduces students to automated vision systems and components, camera models, testing and measurement, and fundamentals of image processing. Topics include image analysis and processing in binary, gray scale and color images in spatial- and frequency-domain. Texture and shape analysis, hyperspectral imaging, other transforms, and filters are discussed and applied.

Prerequisite: (COSC 1330 or 1435) and ENGR 2460 and MATH 2414.

In this course, the concepts for Internet of Things (IoT), and related devices, sensors, and communication protocols will be introduced. The students will engage in hands-on assignments with the IoT kits. These hands-on experiences will allow students to develop skill to create specific tools and programs that are applicable to the hardware, software, and the cloud. Final project will involve the incorporation of learned concepts to solve a real-world problem using IoT devices, sensors, and communication protocols. Final project will be a team assignment. Junior or Senior standing.

Prerequisite: COSC 1320 or (COSC 1330 or 1435).

This course will introduce the student to AI, ML and Deep Learning topics. In addition, the students will investigate different AI applications in engineering and sciences. The course entails general concepts of AI as well as AI models, selecting an AI model for an application. Some theory will be covered. Transfer learning and reinforcement learning in deep convolutional neural networks will be discussed. Ethics in AI and limitations of AI will also be discussed. The course culminates in a class team project that involves use of AI tools for machine learning/deep learning for data classification/regression analysis or other applications selected by students and approved by instructor. Different AI implementations will be surveyed in a variety of AI applications. Students will get hands on experience with programming in MATLAB, Python or other AI tools. Junior/Senior standing.

Prerequisite: COSC 1330, 1320 or 1435.

This course allows students to employ the knowledge attained in other courses to implement (including building, testing, and documenting) an approved project, within budget and on schedule. Course requirements include a written report and oral presentations.

Prerequisite: ENGR 4240.

Three SCH may be earned by working in an internship position in a governmental agency, private industry, or other appropriate venue for a full-time, 8- to 10-week summer internship. At least Junior standing; requires approval of a faculty member who will review and approve the proposed work to be submitted for a grade and administer the internship. May not be repeated.

Subject material variable. May be repeated for credit when topics are different.

Principles of physical measurements; standards, calibration, error estimation; static and dynamic performance of measuring systems; laboratory experience, experiment planning, report writing. The purpose of this course is for students to gain proficiency in designing, assembling, and operating an experiment; and analyzing and presenting experimental results. This encompasses skills such as an understanding control and data acquisition electronics, operation and limitation of modern sensors, calibration and error analysis, assessing applicability of theory and the impact of secondary experimental variables, and writing and presenting reports and analysis.

Prerequisite: PHYS 2426 and (MATH 3342 or 3345).