Developing advanced computational techniques, mathematical models and simulation tools to solve complex engineering, physical and industrial problems at the University of Lancashire.
Numerical methods research at the University of Lancashire combines mathematics, scientific computing, engineering and physics to develop efficient computational techniques for solving real-world problems. Research spans the development, analysis, implementation and application of numerical algorithms for differential equations, integral equations, inverse problems and engineering simulations.
The University has particular expertise in boundary element methods, computational acoustics, inverse modelling and scientific software development, supporting applications across engineering and applied science.
The LinkedIn Group Numerical Methods has been created to connect the people interested in the numerical mathematics field. You can also link to the LinkedIn profile Numerical Analyst.
The website www.numerical-methods.com has been created to share reources in numerical methods.
Research focuses not only on solving mathematical problems but also on understanding the accuracy, stability, efficiency and reliability of computational algorithms. Numerical analysis provides the theoretical foundation that underpins modern simulation, digital engineering and scientific computing.
Development and analysis of boundary element techniques for acoustic, engineering and physical applications. The LinkedIn Group Boundary Element Method has been created to connect the people interested in boundary elements.
Numerical simulation of sound propagation, aeroacoustics, loudspeaker systems and noise control. The LinkedIn Group Finite Difference Method has been created to connect the people interested in finite difference methods.
Recovering unknown physical information from measured data through advanced computational techniques.
Numerical approaches for solving differential equations arising in engineering and physics. The LinkedIn Group Finite Difference Methods has been created to connect the people interested in finite differences.
Computational modelling using finite-difference time-domain and related numerical techniques. The LinkedIn Group FDTD method in Electromagnetic and Acoustic Simulation has been created to connect the people interested in FDTD method.
Design and implementation of efficient algorithms and high-performance computational software.
Numerical methods developed at the University have been applied to a wide range of industrial and scientific challenges, particularly in acoustics and engineering analysis. Research has included the simulation of acoustic fields, loudspeaker systems, aircraft and engine noise, diffusion processes and electromagnetic devices. :contentReference[oaicite:1]{index=1}
A distinctive aspect of the University's research is the development of practical computational software implementing advanced numerical methods. Research has produced algorithms, codes and software tools supporting the solution of engineering and acoustics problems using boundary element and related computational techniques. :contentReference[oaicite:2]{index=2}
Algorithm development, numerical experimentation and modelling.
Specialist software for acoustic and engineering simulations.
Efficient implementations of large-scale numerical algorithms.
Supporting simulation, analysis and engineering design.
Numerical methods research is closely linked to mathematics, acoustics, engineering and physics activities within the University. The work contributes to the wider research strengths of the Jeremiah Horrocks Institute and supports interdisciplinary projects involving aerospace, acoustics, manufacturing and computational science. :contentReference[oaicite:3]{index=3}
Research-focused computational mathematics projects
Numerical analysis and scientific computing research
Collaborative engineering and modelling projects
Algorithm and simulation tool development
Research students have opportunities to investigate new numerical techniques, computational algorithms and engineering applications while working with experienced researchers in applied mathematics, acoustics and scientific computing.
Emerging areas of interest include large-scale simulation, high-performance computing, computational acoustics, digital engineering, data-driven modelling and the integration of advanced numerical techniques with artificial intelligence and machine learning technologies.