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Experimental and numerical investigation on the effect of pressure on micromix hydrogen combustion
(2021)
The micromix (MMX) combustion concept is a DLN gas turbine combustion technology designed for high hydrogen content fuels. Multiple non-premixed miniaturized flames based on jet in cross-flow (JICF) are inherently safe against flashback and ensure a stable operation in various operative conditions.
The objective of this paper is to investigate the influence of pressure on the micromix flame with focus on the flame initiation point and the NOx emissions. A numerical model based on a steady RANS approach and the Complex Chemistry model with relevant reactions of the GRI 3.0 mechanism is used to predict the reactive flow and NOx emissions at various pressure conditions. Regarding the turbulence-chemical interaction, the Laminar Flame Concept (LFC) and the Eddy Dissipation Concept (EDC) are compared. The numerical results are validated against experimental results that have been acquired at a high pressure test facility for industrial can-type gas turbine combustors with regard to flame initiation and NOx emissions.
The numerical approach is adequate to predict the flame initiation point and NOx emission trends. Interestingly, the flame shifts its initiation point during the pressure increase in upstream direction, whereby the flame attachment shifts from anchoring behind a downstream located bluff body towards anchoring directly at the hydrogen jet. The LFC predicts this change and the NOx emissions more accurately than the EDC. The resulting NOx correlation regarding the pressure is similar to a non-premixed type combustion configuration.
This study investigates the influence of pressure on the temperature distribution of the micromix (MMX) hydrogen flame and the NOx emissions. A steady computational fluid dynamic (CFD) analysis is performed by simulating a reactive flow with a detailed chemical reaction model. The numerical analysis is validated based on experimental investigations. A quantitative correlation is parametrized based on the numerical results. We find, that the flame initiation point shifts with increasing pressure from anchoring behind a downstream located bluff body towards anchoring upstream at the hydrogen jet. The numerical NOx emissions trend regarding to a variation of pressure is in good agreement with the experimental results. The pressure has an impact on both, the residence time within the maximum temperature region and on the peak temperature itself. In conclusion, the numerical model proved to be adequate for future prototype design exploration studies targeting on improving the operating range.
The term ocular rigidity is widely used in clinical ophthalmology. Generally it is assumed as a resistance of the whole eyeball to mechanical deformation and relates to biomechanical properties of the eye and its tissues. Basic principles and formulas for clinical tonometry, tonography and pulsatile ocular blood flow measurements are based on the concept of ocular rigidity. There is evidence for altered ocular rigidity in aging, in several eye diseases and after eye surgery. Unfortunately, there is no consensual view on ocular rigidity: it used to make a quite different sense for different people but still the same name. Foremost there is no clear consent between biomechanical engineers and ophthalmologists on the concept. Moreover ocular rigidity is occasionally characterized using various parameters with their different physical dimensions. In contrast to engineering approach, clinical approach to ocular rigidity claims to characterize the total mechanical response of the eyeball to its deformation without any detailed considerations on eye morphology or material properties of its tissues. Further to the previous chapter this section aims to describe clinical approach to ocular rigidity from the perspective of an engineer in an attempt to straighten out this concept, to show its advantages, disadvantages and various applications.
Phase change materials offer a way of storing excess heat and releasing it when it is needed. They can be utilized as a method to control thermal behavior without the need for additional energy. This work focuses on exploring the potential of using phase change materials to passively control the thermal behavior of a star tracker by infusing it with a fitting phase change material. Based on the numerical model of the star trackers thermal behavior using ESATAN-TMS without implemented phase change material, a fitting phase change material for selected orbits is chosen and implemented in the thermal model. The altered thermal behavior of the numerical model after the implementation is analyzed for different amounts of the chosen phase change materials using an ESATAN-based subroutine developed by the FH Aachen. The PCM-modelling-subroutine is explained in the paper ICES-2021-110. The results show that an increasing amount of phase change material increasingly damps temperature oscillations. Using an integral part structure some of the mass increase can be compensated.
The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.
Multi-attribute relation extraction (MARE): simplifying the application of relation extraction
(2021)
Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.
The hot spots conjecture is only known to be true for special geometries. This paper shows numerically that the hot spots conjecture can fail to be true for easy to construct bounded domains with one hole. The underlying eigenvalue problem for the Laplace equation with Neumann boundary condition is solved with boundary integral equations yielding a non-linear eigenvalue problem. Its discretization via the boundary element collocation method in combination with the algorithm by Beyn yields highly accurate results both for the first non-zero eigenvalue and its corresponding eigenfunction which is due to superconvergence. Additionally, it can be shown numerically that the ratio between the maximal/minimal value inside the domain and its maximal/minimal value on the boundary can be larger than 1 + 10− 3. Finally, numerical examples for easy to construct domains with up to five holes are provided which fail the hot spots conjecture as well.
For typical cases of non-isolated lightning protection systems (LPS) the impulse currents are investigated which may flow through a human body directly touching a structural part of the LPS. Based on a basic LPS model with conventional down-conductors especially the cases of external and internal steel columns and metal façades are considered and compared. Numerical simulations of the line quantities voltages and currents in the time domain are performed with an equivalent circuit of the entire LPS.
As a result it can be stated that by increasing the number of conventional down-conductors and external steel columns the threat for a human being can indeed be reduced, but not down to an acceptable limit. In case of internal steel columns used as natural down-conductors the threat can be reduced sufficiently, depending on the low-resistive connection of the steel columns to the lightning equipotential bonding or the earth termination system, resp. If a metal façade is used the threat for human beings touching is usually very low, if the façade is sufficiently interconnected and multiply connected to the lightning equipotential bonding or the earth termination system, resp.
The coupling of ligand-stabilized gold nanoparticles with field-effect devices offers new possibilities for label-free biosensing. In this work, we study the immobilization of aminooctanethiol-stabilized gold nanoparticles (AuAOTs) on the silicon dioxide surface of a capacitive field-effect sensor. The terminal amino group of the AuAOT is well suited for the functionalization with biomolecules. The attachment of the positively-charged AuAOTs on a capacitive field-effect sensor was detected by direct electrical readout using capacitance-voltage and constant capacitance measurements. With a higher particle density on the sensor surface, the measured signal change was correspondingly more pronounced. The results demonstrate the ability of capacitive field-effect sensors for the non-destructive quantitative validation of nanoparticle immobilization. In addition, the electrostatic binding of the polyanion polystyrene sulfonate to the AuAOT-modified sensor surface was studied as a model system for the label-free detection of charged macromolecules. Most likely, this approach can be transferred to the label-free detection of other charged molecules such as enzymes or antibodies.