Computational Wave Dynamics© Physics and Engineering today still uses almost entirely a Particle Model of reality. The mathematical modelling of fluid flows starts with an arbitrary "fluid particle" that undergoes motion and deformation according to the "laws" of Newtonian Mechanics. The so called Fundamental Equations of Fluid Motion, the Navier Stokes Equations, were derived in the first half of the Nineteenth Century. They still form the foundation of fluid mechanics today. Particles vs. Waves This attachment to the Particular View is preventing progress in many areas of Science and Engineering. It has been known since the formulation of the Heisenberg Uncertainty Principle and the development of Quantum Mechanics that matter is not particulate but composed of the interference patterns of electromagnetic wave fields. If one observes the most obvious body of fluid on the planet - the Sea - the first thing one notices is that all motion in and on the sea is of a wave nature. Similarly, all motion and disturbance of the atmosphere is also of a wave nature - otherwise known as sound. Even in solids, all forces, stresses and strains are transmitted by wave motion. Apparently solid matter can in fact be considered to be composed of standing waves of ultrasound. Therefore, all mechanical interactions arise from the interference of Electromagnetic Wave Fields. In order to reflect nature as accurately and efficiently as possible in our engineering modelling and simulation tools, we must develop systems that are based on this fundamental reality - that all mechanical interactions are fundamentally of a wave nature, not the "particular" interactions of classical mechanics. Digital to Analogue Conversion This approach cannot be achieved with the now predominant digital computer architecture. The reason for this is Chaos, in particular Sensitive Dependence on Initial Conditions - the "Butterfly Effect". Until the end of the 1960s, Analogue and Digital Computers played an equal role in science and engineering. The analogue computer is an inherently massively parallel system that can solve many engineering problems in a fraction of the time required by digital computers. A digital computer on the other hand creates a numeric approximation and discretisation to solve the relevant (partial) differential equations. The iterative numerical methods used to then solve the equations are themselves subject to the Laws of Chaos, on top of the effects of Chaos on the reality itself that we are trying to simulate.  In addition, the partial differential equations of fluid flow are based on a fallacy - the particle model.  In effect, our digital computer techniques are only useable within regimes that have already been explored experimentally. In short, they are useful for refining what lies within known domains - they are not useful for real discovery. The Analogue Computational Model offers the potential to directly simulate the underlying Wave Fields of matter with a direct physical wave analogue, not an abstracted "mathematical model" of those waves. MIR are working to develop an analogue computational system that will allow 100% accurate predictive simulation of fluid flow - or as near to 100% as the inherent uncertainty of the nature of Chaos and Sensitive Dependence on Initial Conditions allows. We call this Computational Wave Dynamics. Real Time Simulation This analogue computational model also promises to allow real time simulation of any regime of fluid flow and solid matter interactions - to replace CFD and Finite Element Analysis.  It will be a real Computational Wind Tunnel. Predictive Life Modelling An adjunct to this is a system for predictive modelling and simulation of the future life, maintenance requirements and reliability of engineering artifacts and their ongoing in-service monitoring. This could ultimately be extended to the medical diagnosis of living beings. Further Information For more information on Computational Wave Dynamics you can download the following introductory paper: Observations on the Application of Chaos Theory to the Modelling of Fluid Flows