Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Application of Vector Integral Theorems in Engineering

View through CrossRef
 Vector integral theorems are foundational to the mathematical analysis of physical systems in mechanical and electrical engineering. This paper provides a comprehensive examination of Gauss’s Divergence Theorem and Stokes’ Theorem, covering their historical origins, rigorous mathematical derivations, physical interpretations, and engineering applications. Gauss’s theorem, which equates the outward flux of a vector field through a closed surface to the volume integral of its divergence, is applied to problems in fluid mechanics, heat transfer, elasticity, and electrostatics. Stokes’ theorem, which relates the circulation of a vector field around a closed curve to the surface integral of its curl, is applied to problems in electromagnetism, circuit analysis, and electromagnetic wave propagation. Both theorems are further situated within a broader mathematical framework that includes Green’s theorem and the generalised Stokes’ theorem. This paper presents multiple worked engineering examples—including pressure vessel analysis, pipe flow, heat flux computation, Ampère’s law, and magnetic flux linkage—alongside a comparative analysis, a discussion of numerical implementation, and a critical evaluation of the theorems’ limitations. The results affirm that these theorems remain indispensable tools for engineering analysis and design, with expanding relevance in computational methods and simulation.
Title: Application of Vector Integral Theorems in Engineering
Description:
 Vector integral theorems are foundational to the mathematical analysis of physical systems in mechanical and electrical engineering.
This paper provides a comprehensive examination of Gauss’s Divergence Theorem and Stokes’ Theorem, covering their historical origins, rigorous mathematical derivations, physical interpretations, and engineering applications.
Gauss’s theorem, which equates the outward flux of a vector field through a closed surface to the volume integral of its divergence, is applied to problems in fluid mechanics, heat transfer, elasticity, and electrostatics.
Stokes’ theorem, which relates the circulation of a vector field around a closed curve to the surface integral of its curl, is applied to problems in electromagnetism, circuit analysis, and electromagnetic wave propagation.
Both theorems are further situated within a broader mathematical framework that includes Green’s theorem and the generalised Stokes’ theorem.
This paper presents multiple worked engineering examples—including pressure vessel analysis, pipe flow, heat flux computation, Ampère’s law, and magnetic flux linkage—alongside a comparative analysis, a discussion of numerical implementation, and a critical evaluation of the theorems’ limitations.
The results affirm that these theorems remain indispensable tools for engineering analysis and design, with expanding relevance in computational methods and simulation.

Related Results

AI Engineering: A Strategic Research Framework to Benefit Society
AI Engineering: A Strategic Research Framework to Benefit Society
The strategic convergence of artificial intelligence (AI) and engineering, envisioned as AI Engineering, represents a generational opportunity to supercharge engineering for the be...
AI Engineering: A Strategic Research Framework to Benefit Society - Executive Summary
AI Engineering: A Strategic Research Framework to Benefit Society - Executive Summary
The strategic convergence of artificial intelligence (AI) and engineering, envisioned as AI Engineering, represents a generational opportunity to supercharge engineering for the be...
MECHANISMS OF SCHEMATIC MODELING BASED ON VECTOR LOGIC
MECHANISMS OF SCHEMATIC MODELING BASED ON VECTOR LOGIC
Context. This paper addresses issues relevant to the EDA market – reducing the cost and time of testing and verification of digital projects by synthesizing the logic vector of a d...
Vector SHAP Values for Machine Learning Time Series Forecasting
Vector SHAP Values for Machine Learning Time Series Forecasting
ABSTRACTWe propose a new vector SHapley Additive exPlanations (SHAP) to interpret machine learning models for forecasting time series using lags of predictor variables. Unlike the ...
General Stochastic Vector Integration: A New Approach
General Stochastic Vector Integration: A New Approach
This paper presents a topology-based approach to the general vector-valued stochastic integral for predictable integrands and semimartingale integrators. The integral is defined as...
Using covariance weighted euclidean distance to assess the dissimilarity between integral experiments
Using covariance weighted euclidean distance to assess the dissimilarity between integral experiments
Integral experiments especially criticality experiments help a lot in designing either new nuclear reactor or criticality assembly. The calculation uncertainty of the integral para...

Back to Top