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Analysis of the (μ/μI,λ)-CSA-ES with repair by projection applied to a conically constrained problem
(2019)
A covariance matrix self-adaptation evolution strategy for optimization under linear constraints
(2018)
In recent years, ultrashort pulsed lasers have increased their applicability for industrial requirements, as reliable femtosecond and picosecond laser sources with high output power are available on the market. Compared to conventional laser sources, high quality processing of a large number of material classes with different mechanical and optical properties is possible. In the field of laser cutting, these properties enable the cutting of multilayer substrates with changing material properties. In this work, the femtosecond laser cutting of phosphor sheets is demonstrated. The substrate contains a 230 micrometer thick silicone layer filled with phosphor, which is embedded between two glass plates. Due to the softness and thermal sensitivity of the silicone layer in combination with the hard and brittle dielectric material, the separation of such a material combination is challenging for both mechanical separation processes and cutting with conventional laser sources. In our work, we show that the femtosecond laser is suitable to cut the substrate with a high cutting edge quality. In addition to the experimental results of the laser dicing process, we present a universal model that allows predicting the final cutting edge geometry of a multilayer substrate.
Investigation of non-uniformly emitting optical fiber diffusers on the light distribution in tissue
(2020)
The importance of Agent-Based Simulation (ABS) as scientific method to generate data for scientific models in general and for informed policy decisions in particular has been widely recognised. However, the important technique of code testing of implementations like unit testing has not generated much research interested so far. As a possible solution, in previous work we have explored the conceptual use of property-based testing. In this code testing method, model specifications and invariants are expressed directly in code and tested through automated and randomised test data generation. This paper expands on our previous work and explores how to use property-based testing on a technical level to encode and test specifications of ABS. As use case the simple agent-based SIR model is used, where it is shown how to test agent behaviour, transition probabilities and model invariants. The outcome are specifications expressed directly in code, which relate whole classes of random input to expected classes of output. During test execution, random test data is generated automatically, potentially covering the equivalent of thousands of unit tests, run within seconds on modern hardware. This makes property-based testing in the context of ABS strictly more powerful than unit testing, as it is a much more natural fit due to its stochastic nature.