The parameters affecting the production of
A biorefinery comprises a variety of process steps to synthesize products from sustainable natural resources. Dynamic plant‐wide simulation enhances the process understanding, leads to improved cost efficiency and enables model‐based operation and control. It is thereby important for an increased competitiveness to conventional processes. To this end, we developed a Modelica library with replaceable building blocks that allow dynamic modeling of an entire biorefinery. For the microbial conversion step, we built on the dynamic flux balance analysis (DFBA) approach to formulate process models for the simulation of cellular metabolism under changing environmental conditions. The resulting system of differential‐algebraic equations with embedded optimization criteria (DAEO) is solved by a tailor‐made toolbox. In summary, our modeling framework comprises three major pillars: A Modelica library of dynamic unit operations, an easy‐to‐use interface to formulate DFBA process models and a DAEO toolbox that allows simulation with standard environments based on the Modelica modeling language. A biorefinery model for dynamic simulation of the OrganoCat pretreatment process and microbial conversion of the resulting feedstock by Corynebacterium glutamicum serves as case study to demonstrate its practical relevance.
Abstract. Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of reproducibility (homogeneity) of the specimen. This makes it difficult to discriminate between different values of single roughness parameters.Therefore uncertainty assessment methods are required that take all relevant aspects into account. In the literature this is scarcely performed and examples specific for parameters used in friction and wear are not yet given.We propose a procedure to derive the uncertainty from a single profile employing a statistical method that is based on the statistical moments of the amplitude distribution and the autocorrelation length of the profile. To show the possibilities and the limitations of this method we compare the uncertainty derived from a single profile with that derived from a high statistics experiment.
Template and Preprocessor Metaprogramming are both wellknown in the C++ community to have much in common with Functional Programming (FP). Recently, very few research threads on underpinning these commonalities have emerged to empower cross-development of C++ Metaprogramming (C++MP) and FP. In this paper, we program a self-contained real-world example in a side-by-side fashion to explore the usefulness of a few mainstream FP languages for this purpose: We develop a compile-time abstract datatype for Rational Numbers in C++. We then present the runtime equivalent in HASKELL, F#, and Scala to discuss some FP parallels across the languages. Here, we consider semi-automatic translation between C++MP and FP languages, for earlier studies on these parallels have already obviated the impracticability of fully automatic translations. Our study also shows the superiority of multiparadigm FP languages over single-paradigm ones. In particular, we conclude Scala to currently be the most promising FP language for facilitating C++MP.
In nanotechnology and semiconductor fabrication geometry parameters of nanostructures such as curvatures and side wall angles are of increasing relevance with decreasing feature sizes. The atomic force microscope (AFM) is still one of the main measurement tools employed to investigate topographical parameters. It is generally operated in oscillation mode in order to avoid wear or damage of the probe. As imaging instruments deliver data that are influenced by the probing process, appropriate reconstruction processes are needed. This paper shows a significant contrast of the phase lag of the probe of an amplitude-modulated AFM (AM-AFM) and its driving force at the edge transition of nanostructures with a high aspect ratio. A simulation model reveals the relation between interaction forces and the observed phase behavior. It illustrates how the equilibrium positions of an oscillating probe differ from those of a sample geometry that is purely dilated by static probe tip contact. We show that AFM measurements in oscillation mode deliver a distorted topography image and that the greater the distortion the more energy dissipation is involved. An understanding of the distortion mechanism forms the basis for the development of reconstruction strategies.
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