Course Overview

This course focuses on advanced mathematical methods used in mechanical engineering. It covers topics such as differential equations, linear algebra, complex analysis, and numerical methods. The emphasis is on applying these mathematical techniques to solve engineering problems.

Course Objectives

  • Develop proficiency in advanced mathematical methods relevant to mechanical engineering.
  • Apply differential equations and linear algebra to model and solve engineering problems.
  • Understand the principles of complex analysis and its applications in engineering.
  • Utilize numerical methods for solving mathematical problems in engineering contexts.

Weekly Topics

Week 1: Review of Basic Mathematics

  • Functions, limits, and continuity
  • Basic calculus concepts: differentiation and integration
  • Matrix algebra fundamentals

Week 2: Differential Equations

  • First-order differential equations (separation of variables, integrating factors)
  • Higher-order linear differential equations
  • Applications of differential equations in mechanical systems

Week 3: Partial Differential Equations

  • Introduction to partial differential equations (PDEs)
  • Methods of solving PDEs (separation of variables, Fourier series)
  • Applications of PDEs in heat transfer and fluid dynamics

Week 4: Linear Algebra

  • Vector spaces and subspaces
  • Linear transformations and matrix representation
  • Eigenvalues and eigenvectors, applications in stability analysis

Week 5: Complex Variables

  • Introduction to complex numbers and functions
  • Analytic functions and Cauchy-Riemann equations
  • Contour integration and residue theorem

Week 6: Fourier Series and Transforms

  • Fourier series: derivation and applications
  • Fourier transform and its applications in signal processing
  • Inverse Fourier transform and convolution

Week 7: Laplace Transforms

  • Introduction to Laplace transforms and their properties
  • Applications of Laplace transforms in solving ordinary differential equations
  • Inverse Laplace transform techniques

Week 8: Numerical Methods

  • Numerical solutions of linear and non-linear equations
  • Numerical integration and differentiation
  • Introduction to numerical methods for solving ordinary differential equations

Week 9: Optimization Techniques

  • Introduction to optimization in engineering
  • Techniques for constrained and unconstrained optimization
  • Applications in engineering design and analysis

Week 10: Stochastic Processes

  • Basics of probability theory and random variables
  • Introduction to stochastic processes and their applications
  • Markov chains and queuing theory in engineering contexts

Week 11: Mathematical Modeling

  • Approaches to mathematical modeling in mechanical engineering
  • Case studies of engineering problems modeled mathematically
  • Validation and verification of models

Week 12: Project Presentations and Review

  • Student presentations on mathematical models applied to engineering problems
  • Discussion of findings and implications for mechanical engineering
  • Course review and final assessment

Assessment Methods

  • Exams: Midterm and final exams to assess understanding of key concepts.
  • Assignments: Regular assignments on problem sets and theoretical concepts.
  • Projects: Individual or group projects focusing on applying mathematical methods to engineering challenges.
  • Participation: Active participation in discussions and peer reviews.

Recommended Textbooks

  1. "Advanced Engineering Mathematics" by Erwin Kreyszig
  2. "Engineering Mathematics" by K.A. Stroud
  3. "Numerical Methods for Engineers" by Steven C. Chapra and Raymond P. Canale

This syllabus can be tailored further to meet specific institutional requirements and student interests.

Course Overview

This course focuses on advanced mathematical methods used in mechanical engineering. It covers topics such as differential equations, linear algebra, complex analysis, and numerical methods. The emphasis is on applying these mathematical techniques to solve engineering problems.

Course Objectives

  • Develop proficiency in advanced mathematical methods relevant to mechanical engineering.
  • Apply differential equations and linear algebra to model and solve engineering problems.
  • Understand the principles of complex analysis and its applications in engineering.
  • Utilize numerical methods for solving mathematical problems in engineering contexts.

Weekly Topics

Week 1: Review of Basic Mathematics

  • Functions, limits, and continuity
  • Basic calculus concepts: differentiation and integration
  • Matrix algebra fundamentals

Week 2: Differential Equations

  • First-order differential equations (separation of variables, integrating factors)
  • Higher-order linear differential equations
  • Applications of differential equations in mechanical systems

Week 3: Partial Differential Equations

  • Introduction to partial differential equations (PDEs)
  • Methods of solving PDEs (separation of variables, Fourier series)
  • Applications of PDEs in heat transfer and fluid dynamics

Week 4: Linear Algebra

  • Vector spaces and subspaces
  • Linear transformations and matrix representation
  • Eigenvalues and eigenvectors, applications in stability analysis

Week 5: Complex Variables

  • Introduction to complex numbers and functions
  • Analytic functions and Cauchy-Riemann equations
  • Contour integration and residue theorem

Week 6: Fourier Series and Transforms

  • Fourier series: derivation and applications
  • Fourier transform and its applications in signal processing
  • Inverse Fourier transform and convolution

Week 7: Laplace Transforms

  • Introduction to Laplace transforms and their properties
  • Applications of Laplace transforms in solving ordinary differential equations
  • Inverse Laplace transform techniques

Week 8: Numerical Methods

  • Numerical solutions of linear and non-linear equations
  • Numerical integration and differentiation
  • Introduction to numerical methods for solving ordinary differential equations

Week 9: Optimization Techniques

  • Introduction to optimization in engineering
  • Techniques for constrained and unconstrained optimization
  • Applications in engineering design and analysis

Week 10: Stochastic Processes

  • Basics of probability theory and random variables
  • Introduction to stochastic processes and their applications
  • Markov chains and queuing theory in engineering contexts

Week 11: Mathematical Modeling

  • Approaches to mathematical modeling in mechanical engineering
  • Case studies of engineering problems modeled mathematically
  • Validation and verification of models

Week 12: Project Presentations and Review

  • Student presentations on mathematical models applied to engineering problems
  • Discussion of findings and implications for mechanical engineering
  • Course review and final assessment

Assessment Methods

  • Exams: Midterm and final exams to assess understanding of key concepts.
  • Assignments: Regular assignments on problem sets and theoretical concepts.
  • Projects: Individual or group projects focusing on applying mathematical methods to engineering challenges.
  • Participation: Active participation in discussions and peer reviews.

Recommended Textbooks

  1. "Advanced Engineering Mathematics" by Erwin Kreyszig
  2. "Engineering Mathematics" by K.A. Stroud
  3. "Numerical Methods for Engineers" by Steven C. Chapra and Raymond P. Canale

This syllabus can be tailored further to meet specific institutional requirements and student interests.

Numerical Methods

Course Overview

This course provides an in-depth understanding of numerical methods and their applications in mechanical engineering. It emphasizes algorithm development, error analysis, and the implementation of numerical techniques to solve engineering problems.

Course Objectives

  • Understand the fundamental concepts of numerical methods and their applications.
  • Develop skills in formulating and implementing numerical algorithms.
  • Analyze and interpret results from numerical simulations.
  • Apply numerical methods to solve real-world engineering problems.

Weekly Topics

Week 1: Introduction to Numerical Methods

  • Overview of numerical methods in engineering
  • Importance of numerical analysis
  • Types of errors (round-off, truncation, absolute and relative errors)

Week 2: Solutions of Nonlinear Equations

  • Bisection method
  • Newton-Raphson method
  • Secant method and fixed-point iteration

Week 3: System of Linear Equations

  • Gaussian elimination and LU decomposition
  • Iterative methods (Jacobi and Gauss-Seidel methods)
  • Condition number and stability analysis

Week 4: Interpolation and Polynomial Approximation

  • Lagrange and Newton interpolation
  • Spline interpolation
  • Polynomial fitting and least squares approximation

Week 5: Numerical Differentiation and Integration

  • Numerical differentiation techniques
  • Trapezoidal and Simpson’s rules
  • Numerical integration of ordinary differential equations

Week 6: Ordinary Differential Equations (ODEs)

  • Initial value problems: Euler’s method, Runge-Kutta methods
  • Boundary value problems: Shooting method and finite difference method
  • Stability and convergence analysis

Week 7: Partial Differential Equations (PDEs)

  • Classification of PDEs (elliptic, parabolic, and hyperbolic)
  • Finite difference methods for solving PDEs
  • Applications in heat conduction and fluid flow

Week 8: Numerical Methods for Optimization

  • Introduction to optimization techniques
  • Gradient-based methods and non-gradient methods
  • Applications of optimization in engineering design

Week 9: Monte Carlo Methods

  • Introduction to Monte Carlo simulation
  • Applications in uncertainty analysis and risk assessment
  • Random number generation and statistical sampling

Week 10: Finite Element Method (FEM)

  • Introduction to the finite element method
  • Formulation of finite element equations
  • Applications in structural analysis and heat transfer

Week 11: Software Implementation of Numerical Methods

  • Overview of programming languages and tools (MATLAB, Python, C++)
  • Developing algorithms for numerical methods
  • Case studies and project work

Week 12: Project Presentations and Review

  • Student presentations on numerical methods applied to engineering problems
  • Discussion of project findings and methodologies
  • Course review and final assessment

Assessment Methods

  • Exams: Midterm and final exams to assess understanding of numerical techniques.
  • Assignments: Regular problem sets and computational assignments.
  • Projects: Individual or group projects focusing on implementing numerical methods to solve engineering challenges.
  • Participation: Active participation in class discussions and peer reviews.

Recommended Textbooks

  1. "Numerical Methods for Engineers" by Steven C. Chapra and Raymond P. Canale
  2. "Numerical Analysis" by Richard L. Burden and J. Douglas Faires
  3. "Finite Element Method: Linear Static and Dynamic Finite Element Analysis" by Thomas J.R. Hughes

This syllabus can be tailored further to meet specific institutional requirements and the interests of the students.

رؤية الكلية

كلية رائدة تُعنى بالعلوم التطبيقية من خلال تطوير الفكر والابداع و مصدر رئيسي للدراسات والابحاث العلمية في مختلف العلوم التطبيقية الحديثة.

مهمة الكلية

تخريج كوادر ذوي كفاءة عالية في مجالات العلوم التطبيقية تسهم في تطوير المجتمع وحل مشاكله. إرساء نظام جودة شاملة بالكلية للوصول بها الى مستويات منافسة محليا وعالميا. تطوير البنية التحتية للكلية وتعظيم الاستفادة من مواردها المادية والبشرية.

أهداف الكلية

  1. العمل ضمن برنامج واهداف الاكاديمية العسكرية للعلوم الامنية والاستراتيجية.

  2. تهيئة واعداد خرجين يمتميزون بمهارات فكرية ومهنية وبحثية فاعلة وتنافسية في مختلف مجالات العلوم التطبيقية وتطبيقيات فيزيائية وكيمياء وتطبيقية وكذلك التقنيات الحديثة

  3. تطوير طرق وسبل البحث العلمي في التخصصات ذات العلاقة باقسام الكلية الفاعلة في ايجاد حلول للمشكلات العلمية التطبيقية في مختلف المجالات – العلوم – الاقتصاد وغيرها

  4. دعم النهضة الثقافية والاجتماعية والنشاطات الفنية للمجتمع من خلال البرامج العلمية التي تنظمها الكلية والكادر العلمي فيها

  5. ايجاد علاقات ثقافية وعلمية محلية ودولية مع الكليات ذات العلاقة والمشاركة في المؤتمرات المحلية والعالمية بشكل فاعل وعلى مستويات مختلفة وتنظيم النشاطات المناظرة في الكلية

  6. تشجيع ودعم الطلبة على تطوير مستوياتهم وقابلياتهم العلمية وتوجيهها باتجاه خلق هوية فنية علمية لهم من اجل بناء مجتمع متوازن علميا واكاديميا

  7. تحقيق اعلى مستويات التفاعل والاسهم بين اقسام الكلية والكليات الاخرى والمنظمات والمراكز والمعاهد ذات الاهداف القربية من اهداف الكلية

  8. تقديم برامج اكاديمية متميزة وفقا لمعاير الجودة والاعتماد الاكاديمي

  9. دعم اجراء ونشر البحوث التطبيقية التي تسهم في التقديم العلمي والتقني

اولا قسم الهندسة الصناعية

يحتاج الطالب الى إتمام 33 وحدة دراسية منها 27 واحدة الزامية (7 مواد دراسية + الرسالة) و 6وحدات اختيارية ( مادتين يتم اختيارهن من المواد الاختيارية) 

الرمز

المادة

الساعات

مواد الزامية

G-500 Research methods 3
Med-501 Engineering Mathematics  3
Med-502 Numerical Methods  3
Med-503 Manufacturing Processes 3
Med-504 Modern Metal Cutting 3
Med-505 Non-Destructive Testing (NDT) 3
Med-506 Application of CAD/CAM 3
  Master's thesis 6

مواد اختيارية

 Med-507 Design for Manufacturing (DFM) 3
 Med-508 Engineering Economics and Cost Accounting 3
 Med-509 Engineering Management/Operation Research 3
 Med-510 Welding and Casting Technology 3
 Med-511 Advanced Quality Engineering 3
    3
    3

 

ثانيا قسم الامن السيبراني

يحتاج الطالب الى إتمام 33 وحدة دراسية منها 27 واحدة الزامية (7 مواد دراسية + الرسالة) و 6وحدات اختيارية ( مادتين يتم اختيارهن من المواد الاختيارية) 

الرمز

المادة

الساعات

مواد الزامية

ACY-501 Research Methods in Computational Studies 3
ACY-502 Introduction to Cyber Security and Digital Crime 3
ACY-503 Digital Forensics and Investigation 3
ACY-504 Ethical Hacking and Penetration Testing 3
ACY-505 Computer Security Risk Management and Legal Issues 3
ACY-506 Cryptography and Data Protection 3
ACY-507 Security Enterprise Infrastructure Using Cyber Security Techniques 3
  Master's thesis 6

مواد اختيارية

ACY-508 Innovative Solutions in Software Security 3
ACY-509 Cloud Security 3
ACY-510 Mobile Security 3
ACY-511 Security Analysis and Incident Response 3
ACY-512 Risk Management and Compliance 3
    3
    3

 

رؤية الكلية

التميّز والريادة في البحث والتحليل الإستراتيجي.

رسالة الكلية

إعداد الكوادر المتخصصة في العلوم الإستراتيجية , وإجراء البحوث والدراسات ونقل المعارف حرصاً  على خدمة وتطوير الفهم الصحيح للقضايا الإستراتيجية.

أهداف الكلية

  1. إعداد الدراسات التحليليه للمواضيع التى تتعلق بالأمن الليبي على المستويات المختلفة (دولياً- إقليمياً - محلياً) .
  2. تطوير الفكر الإستراتيجي فى كافة المجالات (السياسية - العسكرية - الاقتصادية - الاجتماعية - الثقافية) .
  3. المساهمة فى طرح الرؤى والأفكار ذات البعد الإستراتيجي التى تشارك فيها القوات المسلحة مع باقى أجهزة الدولة.
  4. إعداد متخصصين على مستوى عالٍ من المعرفة في الدراسات الإستراتيجيه بما يتناسب والمسؤوليات التي تنتظره في ميدان العمل المهني والتحليل الإستراتيجي.
  5. تطوير الوعي الإستراتيجي لتعزيز القدرات في اتخاذ القرار.

اولا قسم الدراسات الاستراتيجية