I. Application of multi-Regge theory to production processes. II. High energy model for proton-proton scattering

This dissertation consists of two parts. The first part presents an explicit procedure for applying multi-Regge theory to production processes. As an illustrative example, the case of three body final states is developed in detail, both with respect to kinematics and multi-Regge dynamics. Next, the experimental consistency of the multi-Regge hypothesis is tested in a specific high energy reaction; the hypothesis is shown to provide a good qualitative fit to the data. In addition, the results demonstrate a severe suppression of double Pomeranchon exchange, and show the coupling of two "Reggeons" to an external particle to be strongly damped as the particle's mass increases. Finally, with the use of two body Regge parameters, order of magnitude estimates of the multi-Regge cross section for various reactions are given.

The second part presents a diffraction model for high energy proton-proton scattering. This model developed by Chou and Yang assumes high energy elastic scattering results from absorption of the incident wave into the many available inelastic channels, with the absorption proportional to the amount of interpenetrating hadronic matter. The assumption that the hadronic matter distribution is proportional to the charge distribution relates the scattering amplitude for pp scattering to the proton form factor. The Chou-Yang model with the empirical proton form factor as input is then applied to calculate a high energy, fixed momentum transfer limit for the scattering cross section, This limiting cross section exhibits the same "dip" or "break" structure indicated in present experiments, but falls significantly below them in magnitude. Finally, possible spin dependence is introduced through a weak spin-orbit type term which gives rather good agreement with pp polarization data.

The development and validation of computational MHD techniques for the modelling of metal production processes

Magnetic fields are used in a number of processes related to the extraction of metals, production of alloys and the shaping of metal components. Computational techniques have an increasingly important role to play in the simulation of such processes, since it is often difficult or very costly to conduct experiments in the high temperature conditions encountered and the complex interaction of fluid flow, heat transfer and magnetic fields means simple analytic models are often far removed from reality. In this paper an overview of the computational activity at the University of Greenwich is given in this area, covering the past ten years. The overview is given from the point of view of the modeller and within the space limitations imposed by the format it covers the numerical methods used, attempts at validation against experiments or analytic procedures; it highlights successes, but also some failures. A broad range of models is covered in the review (and accompanying lecture), used to simulate (a) A-C field applications: induction melting, magnetic confinement and levitation, casting and (b) D-C field applications such as: arc welding and aluminium electroloysis. Most of these processes involve phase change of the metal (melting or solidification), the presence of a dynamic free surface and turbulent flow. These issues affect accuracy and need to be address by the modeller.

Utilisation of by-products from sunflower-based biodiesel production processes for the production of fermentation feedstock

By-products streams from a sunflower-based biodiesel plant were utilised for the production of fermentation media that can be used for the production of polyhydroxyalkanoates (PHA). Sunflower meal was utilised as substrate for the production of crude enzyme consortia through solid state fermentation (SSF) with the fungal strain Aspergillus oryzae. Fermented solids were subsequently mixed with unprocessed sunflower meal aiming at the production of a nutrient-rich fermentation feedstock. The highest free amino nitrogen (FAN) and inorganic phosphorus concentrations achieved were 1.5 g L-1 and 246 mg L-1, respectively, when an initial proteolytic activity of 6.4 U mL-1 was used. The FANconcentrationwas increased to 2.3 g L-1 when the initial proteolytic activity was increased to 16 U mL-1. Sunflower meal hydrolysates were mixed with crude glycerol to provide fermentationmedia that were evaluated for the production of poly(3-hydroxybutyrateco- 3-hydroxyvalerate) (P(3HB-co-3HV)) using Cupriavidus necator DSM545. The P(3HB-co-3HV) (9.9 g l-1) produced contained 3HB and 3HV units with 97 and 3 mol %, respectively. Integrating PHA production in existing 1st generation biodiesel production plants through valorisation of by-product streams could improve their sustainability.

Clavulanic acid production processes in a tower bioreactor with immobilised cells

The feasibility of using Streptomyces clavuligerus ATCC 27064 bioparticles supported on alginate gel containing alumina to produce clavulanic acid (CA) was investigated. To this end, effectiveness factors for spherical bioparticles, relating respiration rates of immobilised and free cells, were experimentally determined for various dissolved oxygen (DO) levels and bioparticle radii. Monod kinetics was assumed as representative of the oxygen consuming reaction, while internal oxygen diffusion was considered the limiting step. A comparison was made of the results from a tower bioreactor operating under batch, repeated-batch and continuous conditions with immobilised bioparticles. The theoretical curve of the effectiveness factor for the zero-order reaction model, considering an inert nucleus - the dead core model - was very well fitted to the experimental data. The results of the bioprocess indicated that the batch operation was the most efficient and productive, requiring a do concentration in the reactor above 60% of the saturation value. (C) 2007 Elsevier B.V. All rights reserved.

Exergy efficiency analysis of chemical and biochemical stages involved in liquid biofuels production processes

Liquid biofuels can be produced from a variety of feedstocks and processes. Ethanol and biodiesel production processes based on conventional raw materials are already commercial, but subject to further improvement and optimization. Biofuels production processes using lignocellulosic feedstocks are still in the demonstration phase and require further R&D to increase efficiency. A primary tool to analyze the efficiency of biofuels production processes from an integrated point of view is offered by exergy analysis. To gain further insight into the performance of biofuels production processes, a simulation tool, which allows analyzing the effect of process variables on the exergy efficiency of stages in which chemical or biochemical reactions take place, were implemented. Feedstocks selected for analysis were parts or products of tropical plants such as the fruit and flower stalk of banana tree, palm oil, and glucose syrups. Results of process simulation, taking into account actual process conditions, showed that the exergy efficiencies of the acid hydrolysis of banana fruit and banana pulp were in the same order (between 50% and 60%), lower than the figure for palm oil transesterification (90%), and higher that the exergy efficiency of the enzymatic hydrolysis of flower stalk (20.3%). (C) 2011 Elsevier Ltd. All rights reserved.

High precision tools for slepton pair production processes at hadron colliders

In this thesis, we develop high precision tools for the simulation of slepton pair production processes at hadron colliders and apply them to phenomenological studies at the LHC. Our approach is based on the POWHEG method for the matching of next-to-leading order results in perturbation theory to parton showers. We calculate matrix elements for slepton pair production and for the production of a slepton pair in association with a jet perturbatively at next-to-leading order in supersymmetric quantum chromodynamics. Both processes are subsequently implemented in the POWHEG BOX, a publicly available software tool that contains general parts of the POWHEG matching scheme. We investigate phenomenological consequences of our calculations in several setups that respect experimental exclusion limits for supersymmetric particles and provide precise predictions for slepton signatures at the LHC. The inclusion of QCD emissions in the partonic matrix elements allows for an accurate description of hard jets. Interfacing our codes to the multi-purpose Monte-Carlo event generator PYTHIA, we simulate parton showers and slepton decays in fully exclusive events. Advanced kinematical variables and specific search strategies are examined as means for slepton discovery in experimentally challenging setups.

Knowledge-Production Processes in Practice Research - Outcomes and Critical Elements

The welfare sector has seen considerable changes in its operational context. Welfare services respond to an increasing number of challenges as citizens are confronted with life’s uncertainties and a variety of complex situations. At the same time the service-delivery system is facing problems of co-operation and the development of staff competence, as well as demands to improve service effectiveness and outcomes. In order to ensure optimal user outcomes in this complex, evolving environment it is necessary to enhance professional knowledge and skills, and to increase efforts to develop the services. Changes are also evident in the new emergent knowledge-production models. There has been a shift from knowledge acquisition and transmission to its construction and production. New actors have stepped in and the roles of researchers are subject to critical discussion. Research outcomes, in other words the usefulness of research with respect to practice development, is a topical agenda item. Research is needed, but if it is to be useful it needs to be not only credible but also useful in action. What do we know about different research processes in practice? What conceptions, approaches, methods and actor roles are embedded? What is the effect on practice? How does ‘here and now’ practice challenge research methods? This article is based on the research processes conducted in the institutes of practice research in social work in Finland. It analyses the different approaches applied by elucidating the theoretical standpoints and the critical elements embedded in them, and reflects on the outcomes in and for practice. It highlights the level of change and progression in practice research, arguing for diverse practice research models with a solid theoretical grounding, rigorous research processes, and a supportive infrastructure.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.