CCMAS Course Search

The practical exposure of the student through direct participation in the work of an industry, to real life working condition. During the training, the student acquires a familiarity with Engineering works, organization, physical layout, and the flow of information, materials and operations. This information is expected to complement and integrate the student’s classroom instruction and laboratory/workshop exercises. Duration: 6 months. 500 Level

On the job experience in industry chosen for practical working experience but not necessarily limited to the student’s major (24 weeks from the end of the First Semester at 400-Level to the beginning of the First Semester of the following session. Thus, the second semester at 400-Level is spent in industry). Each student is expected to work in a programme related industry, research institute or regulatory agencies etc. for a period of 6 months under the guidance of an appropriate personnel in the establishment, but supervised by an academic staff of the Department. On completion of the training the student submits the completed Log book on the experience at the establishment, identifying a special theme. Also, there will be a comprehensive report covering the whole of his/her industrial training experiences (GET 299, GET 399 and GET 499), on which a seminar will be presented to the Department for overall assessment. 500 Level Courses

The course consists of three blocks, each consisting of a project assignment, lectures and exercise sessions: Block One includes analysis and modeling of the need for Information exchange for power system control. The aim is to train the students to analyse different perspectives on information necessary for power system control. The project assignment in the block includes implementation of a simple information model for the exchange of data on power systems. Block Two includes basics in programming techniques and computer science focusing on machine learning methods with applications in power systems. The project assignment in the block consists of developing machine learning algorithms for forecasting. Block Three includes Introduction to matlab: Laboratory oriented course designed to introduce students who already have taken a programming course to programming in MATLAB. Topics include introduction to the MATLAB environment, matrix manipulation and computation, MATLAB programming language, writing functions and scripts, and production of 2D graphical output.

Soil structures, compaction and soil stabilisation, stability of slopes earth pressures, retaining walls. Concepts of permeability, stress distribution, shear strength and pressure in relation to foundation engineering; bearing capacity of soils; shallow and deep foundations, pile foundations; Site Investigation.

Mineralogy of soils. Soil structures. Formation of soils. Soil classification. Engineering properties of soils. Soil in water relationship – void ratio, porosity, specific gravity, permeability, and other factors. Atterberg limits – particle size distribution. shear strength of soils, Mohr’s stress circle. Compaction and soil stabilization. Settlement. Theory of consolidation. Laboratory work.

Mineralogy of soils and soil structures. Formation of soils, soil classification, engineering properties of soils. Soil in water relationships - void ratio, porosity, specific gravity, permeability and other factors. Atterberg limits, particle size distribution, Shear strength of soils and Mohr’s stress circle. Compaction and soil stabilisation, settlement, theory of consolidation. Laboratory work.

Origin and formation of soils. Physical properties of soils. Basic concept of soil paedology. Soil colloids; soil reaction; soil mineralogy. Soil organic matter. Soil survey and mapping. Soil classification. Soil fertility and fertilizers. Particle size distribution analysis/sieve analysis. Properties and management of Nigerian soils.

Solid, surface and shell modeling. Faces, bodies and surface intersections. Component-based design. Component assembly and motion constraints. Constrained motions and animation. Introduction to electronics modeling. Electronics board layout preparation, Component libraries and Schematic design. Parametric modeling and adaptive design. Simulation for material optimization. Designing for manufacturing. Additive and subtractive manufacturing. Production for 3-D printing, Laser cutting and CNC machinery. Prerequisite: GET 102 300 Level

Processes of freezing: nucleation and growth of solid phase; Plannar and dendritic growth freezing of alloys; constitutional super-cooling. Solidification of two-phase alloy; structure of cast alloy; effect of cast structure on properties; segregation in ingots. Casting techniques and finishing operations; defects in casting.

Chemical engineers must have an appreciation of the accuracy and reliability of measurements. This course provides a broad introductory knowledge of statistical techniques used in data analysis. It also seeks to link the measurement of various quantities with statistics to enable the analysis of the accuracy of the measurements. Statistical inference intervals, tests hypothesis and significance. Regression and correlation. Introduction to big data analytics and cloud computing applications. Students to have weekly or fortnightly computer laboratory-based assignments. 300 Level