Navigating Reactor Safety in Catalytic Microchannel Reactors

High temperature catalytic reactions are being intensely studied since many decades due to their large industrial potential, such as in pyrolysis, total oxidation (i.e. combustion) and partial oxidation of hydrocarbons. The reactions are characterized by extreme reaction temperatures (T> 1000°C) where homogeneous (i.e. non-catalytic gas phase) reactions can occur in parallel to catalytic reactions. This occurrence of homogeneous reactions is typically an undesired feature, since it complicates the understanding of reaction mechanisms, leads to selectivity losses, and often poses a safety hazard due to potentially explosive behavior. Since free surfaces tend to bind radical species, eventually lead to a quenching of gas-phase reactions. Microreactors, i.e. chemical reactors with characteristic dimensions in the sub-millimeter range, hold great promise for fundamental studies of existing processes offering small thermal inertia, high heat and mass transport rates, compactness etc. Due to their large surface-to-volume ratio, microreactors can be expected to suppress undesirable gas phase reactions and thus form safe reactor configurations for highly explosive processes. In the present study, we numerically investigate the reactive flow of H₂/air mixtures in a microchannel to gain insights into the reason for the absence of explosion observed in previous experiments. The H₂ oxidation reaction is chosen as model reaction due to its high exothermicity and wide flammability range. It also constitutes an important sub-set of reactions in hydrocarbon oxidation. In a two-dimensional boundary layer numerical model, we used coupled mechanisms with detailed elementary-step kinetics for gas-phase and catalytic surface reactions. The influence of different wall materials, reactor dimension, feed conditions and reaction pressure on the coupling of heterogeneous and homogeneous reaction pathways in the microreactor was studied. The results demonstrate that the attainability of 'intrinsic safety' in microchannel reactors is strongly dependent on a complex interplay between homogeneous and heterogeneous reaction pathways in the individual reaction system. In particular, it is found that intrinsic reactor safety breaks down at sufficiently high reactor pressure. Generalized equations for the current reaction systems are derived. As an outlook, other industrially relevant reaction systems, i.e. CO oxidation and NOx formation, are preliminary investigated with respect to the effect of heterogeneous-homogeneous interactions and radical quenching in particular, on the behaviour of these reaction systems

Recent Computer-Aided Design Techniques for Rectangular Microstrip Antenna

In modern microwave systems, rectangular microstrip patch antennas (RMPAs) are probably the most investigated topics among the planar antennas. There are several methods available in literature, for designing and analyzing such antennas, but most of them are very complex and give only approximate results. In this chapter, we have discussed the most accurate and updated computer-aided design (CAD) formulations related to probe-fed RMPA for computing its fundamental input characteristics (resonant frequency and input impedance) and improving radiation characteristics, i.e. gain and polarization purity (the parameter that signifies how much an RMPA is free from spurious modes). These formulations have evolved in the last decades and have been validated against numerous simulations and measurements. The present CAD formulas for resonant frequency and input impedance can accurately address a wide range of RMPA with patch width to patch length ratio (W/L) from 0.5 to 2.0, a substrate having thickness up to 0.23 λg where λg is the guide wavelength and relative permittivity (εr) ranging over 2.2–10.8. The role of a finite air gap on resonant frequency and gain of an RMPA have also been presented. The chapter will be surely useful to antenna designers to achieve a concrete understanding of the RMPA theory

TIME-PREDICTABLE EXECUTION OF EMBEDDED SOFTWARE ON MULTI-CORE PLATFORMS

Ph.DDOCTOR OF PHILOSOPH

Astraea: Grammar-based Fairness Testing

Software often produces biased outputs. In particular, machine learning (ML) based software are known to produce erroneous predictions when processing discriminatory inputs. Such unfair program behavior can be caused by societal bias. In the last few years, Amazon, Microsoft and Google have provided software services that produce unfair outputs, mostly due to societal bias (e.g. gender or race). In such events, developers are saddled with the task of conducting fairness testing. Fairness testing is challenging; developers are tasked with generating discriminatory inputs that reveal and explain biases. We propose a grammar-based fairness testing approach (called ASTRAEA) which leverages context-free grammars to generate discriminatory inputs that reveal fairness violations in software systems. Using probabilistic grammars, ASTRAEA also provides fault diagnosis by isolating the cause of observed software bias. ASTRAEA's diagnoses facilitate the improvement of ML fairness. ASTRAEA was evaluated on 18 software systems that provide three major natural language processing (NLP) services. In our evaluation, ASTRAEA generated fairness violations with a rate of ~18%. ASTRAEA generated over 573K discriminatory test cases and found over 102K fairness violations. Furthermore, ASTRAEA improves software fairness by ~76%, via model-retraining