Tools
SolEthEn bases its offer on the use of simulative techniques that combine and integrate engineering and mathematical methods based on the applied statistic, design of experiments, mathematical modeling and numerical simulation.
DoE
DoE
The Design of Experiment (DoE) is used to investigate the causal relationship between the input and output parameters of an "experiment", by statistical analysis. For "experiment" we means any process whose you want analyzing one or more of the following characteristics:
 the main causes that affect the output;
 the entry conditions that determine the minimum and maximum response;
 the output sensitivity respect to the main control variables;
 the mathematical model that best approximates the physical problem.
This methodology for design and planning of experimental tests allows obtaining their maximum effectiveness by analyzing systematically the nature, objectives, and significant elements of the process. So, by a reasoned application of DOE techniques, it is possible to drastically reduce planning cost of tests (conventional and / or virtual) and extrapolate by them statistically significant informations.
Modeling
Modeling
Mathematical modeling simplifies and describes complex problems in mathematical terms, reducing them to "model problems" that are easier to analyze. In the cognitive and descriptive processes  of disciplines such as engineering, physics, chemistry, life sciences, medicine and economics  mathematical modeling, starting from a real phenomenological or otherwise problem, shall:

identify and understand the intrinsic nature;

determine the relevant characteristics;

represent it in the language of mathematics (for example by partial differential equations);

analyze the model equations.
Simulation
Simulation
Numerical simulation  in fluid dynamics, electromagnetism, thermal and structural analisys  is a technique of virtual prototyping that allows you to simulate a mathematical model (after spatiotemporal and equations discretization) on highperformance computing platforms. Starting from the equations of the model:

you can identify the most suitable numerical method for the approximation;

you can implement and execute this method on the computer using appropriate algorithms;

you can display and analyze the results obtained;

you can interpret the results bringing back the problem to its original contest.