Fundamental studies on the application of enzymes when brewing with unmalted oats and sorghum

The use of unmalted oats or sorghum in brewing has great potential for creating new beer types/flavors and saving costs. However, the substitution of barley malt with oat or sorghum adjunct is not only innovative but also challenging due to their specific grain characteristics. The overall objectives of this Ph.D. project were: 1) to investigate the impact of various types and levels of oats or sorghum on the quality/processability of mashes, worts, and beers; 2) to provide solutions as regards the application of industrial enzymes to overcome potential brewing problems. For these purposes, a highly precise rheological method using a controlled stress rheometer was developed and successfully applied as a tool for optimizing enzyme additions and process parameters. Further, eight different oat cultivars were compared in terms of their suitability as brewing adjuncts and two very promising types identified. In another study, the limitations of barley malt enzymes and the benefits of the application of industrial enzymes in high-gravity brewing with oats were determined. It is recommended to add enzymes to high-gravity mashes when substituting 30% or more barley malt with oats in order to prevent filtration and fermentation problems. Pilot-scale brewing trials using 10–40% unmalted oats revealed that the sensory quality of oat beers improved with increasing adjunct level. In addition, commercially available oat and sorghum flours were implemented into brewing. The use of up to 70% oat flour and 50% sorghum flour, respectively, is not only technically feasible but also economically beneficial. In a further study on sorghum was demonstrated that the optimization of industrial mashing enzymes has great potential for reducing beer production costs. A comparison of the brewing performance of red Italian and white Nigerian sorghum clearly showed that European grown sorghum is suitable for brewing purposes; 40% red sorghum beers were even found to be very low in gluten.

Hardware reduction in digital delta-sigma modulators via error masking - part I: MASH DDSM

Two classes of techniques have been developed to whiten the quantization noise in digital delta-sigma modulators (DDSMs): deterministic and stochastic. In this two-part paper, a design methodology for reduced-complexity DDSMs is presented. The design methodology is based on error masking. Rules for selecting the word lengths of the stages in multistage architectures are presented. We show that the hardware requirement can be reduced by up to 20% compared with a conventional design, without sacrificing performance. Simulation and experimental results confirm theoretical predictions. Part I addresses MultistAge noise SHaping (MASH) DDSMs; Part II focuses on single-quantizer DDSMs..

Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework

Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

Inter-ELM evolution of the edge current density profile on the ASDEX upgrade tokamak

The sudden decrease of plasma stored energy and subsequent power deposition on the first wall of a tokamak due to edge localised modes (ELMs) is potentially detrimental to the success of a future fusion reactor. Understanding and control of ELMs is critical for the longevity of these devices and also to maximise their performance. The commonly accepted picture of ELMs posits a critical pressure gradient and current density in the plasma edge, above which coupled magnetohy drodynamic peeling-ballooning modes become unstable. Much analysis has been presented in recent years on the spatial and temporal evolution of the edge pressure gradient. However, the edge current density has typically been overlooked due to the difficulties in measuring this quantity. In this thesis, a novel method of current density recovery is presented, using the equilibrium solver CLISTE to reconstruct a high resolution equilibrium utilising both external magnetic and internal edge kinetic data measured on the ASDEX Upgrade tokamak. The evolution of the edge current density relative to an ELM crash is presented, showing that a resistive delay in the buildup of the current density is unlikely. An uncertainty analysis shows that the edge current density can be determined with an accuracy consistent with that of the kinetic data used. A comparison with neoclassical theory demonstrates excellent agreement be- tween the current density determined by CLISTE and the calculated profiles. Three ELM mitigation regimes are investigated: Type-II ELMs, ELMs sup- pressed by external magnetic perturbations, and Nitrogen seeded ELMs. In the first two cases, the current density is found to decrease as mitigation on- sets, indicating a more ballooning-like plasma behaviour. In the latter case, the flux surface averaged current density can decrease while the local current density increases, providing a mechanism to suppress both the peeling and ballooning modes.