Energy conservation in the steel industry

The last few years have witnessed an unprecedented increase in the price of energy available to industry in the United Kingdom and worldwide. The steel industry, as a major consumer of energy delivered in U.K. (8% of national total and nearly 25% of industrial total) and whose energy costs currently form some 28% of the total manufacturing cost, is very much aware of the need to conserve energy. Because of the complexities of steelmaking processes it is imperative that a full understanding of each process and its interlinking role in an integrated steelworks is understood. An analysis of energy distribution shows that as much as 70% of heat input is dissipated to the environment in a variety of forms. Of these, waste gases offer the best potential for energy conservation. The study identifies areas for and discusses novel methods of energy conservation in each process. Application of these schemes in BSC works is developed and their economic incentives highlighted. A major part of this thesis describes design, development and testing of a novel ceramic rotary regenerator for heat recovery from high temperature waste gases, where no such system is available. The regenerator is a compact, efficient heat exchanger. Application of such a system to a reheating furnace provides a fuel saving of up to 40%. A mathematical model developed is verified on the pilot plant. The results obtained confirm the success of the concept and material selection and outlines the work needed to develop an industrial unit. Last, but not least, the key position of an energy manager in an energy conservation programme is identified and a new Energy Management Model for the BSC is developed.

The modelling of energy efficient drying for DSM (BL)

This thesis investigates the modelling of drying processes for the promotion of market-led Demand Side Management (DSM) as applied to the UK Public Electricity Suppliers. A review of DSM in the electricity supply industry is provided, together with a discussion of the relevant drivers supporting market-led DSM and energy services (ES). The potential opportunities for ES in a fully deregulated energy market are outlined. It is suggested that targeted industrial sector energy efficiency schemes offer significant opportunity for long term customer and supplier benefit. On a process level, industrial drying is highlighted as offering significant scope for the application of energy services. Drying is an energy-intensive process used widely throughout industry. The results of an energy survey suggest that 17.7 per cent of total UK industrial energy use derives from drying processes. Comparison with published work indicates that energy use for drying shows an increasing trend against a background of reducing overall industrial energy use. Airless drying is highlighted as offering potential energy saving and production benefits to industry. To this end, a comprehensive review of the novel airless drying technology and its background theory is made. Advantages and disadvantages of airless operation are defined and the limited market penetration of airless drying is identified, as are the key opportunities for energy saving. Limited literature has been found which details the modelling of energy use for airless drying. A review of drying theory and previous modelling work is made in an attempt to model energy consumption for drying processes. The history of drying models is presented as well as a discussion of the different approaches taken and their relative merits. The viability of deriving energy use from empirical drying data is examined. Adaptive neuro fuzzy inference systems (ANFIS) are successfully applied to the modelling of drying rates for 3 drying technologies, namely convective air, heat pump and airless drying. The ANFIS systems are then integrated into a novel energy services model for the prediction of relative drying times, energy cost and atmospheric carbon dioxide emission levels. The author believes that this work constitutes the first to use fuzzy systems for the modelling of drying performance as an energy services approach to DSM. To gain an insight into the 'real world' use of energy for drying, this thesis presents a unique first-order energy audit of every ceramic sanitaryware manufacturing site in the UK. Previously unknown patterns of energy use are highlighted. Supplementary comments on the timing and use of drying systems are also made. The limitations of such large scope energy surveys are discussed.

Localized waves in optical systems with periodic dispersion and nonlinearity management

We overview our recent developments in the theory of dispersion-managed (DM) solitons within the context of optical applications. First, we present a class of localized solutions with a period multiple to that of the standard DM soliton in the nonlinear Schrödinger equation with periodic variations of the dispersion. In the framework of a reduced ordinary differential equation-based model, we discuss the key features of these structures, such as a smaller energy compared to traditional DM solitons with the same temporal width. Next, we present new results on dissipative DM solitons, which occur in the context of mode-locked lasers. By means of numerical simulations and a reduced variational model of the complex Ginzburg-Landau equation, we analyze the influence of the different dissipative processes that take place in a laser.

Developing a knowledge-based perspective on coordination:the case of global software projects

We have attempted to bring together two areas which are challenging for both IS research and practice: forms of coordination and management of knowledge in the context of global, virtual software development projects. We developed a more comprehensive, knowledge-based model of how coordination can be achieved, and\illustrated the heuristic and explanatory power of the model when applied to global software projects experiencing different degrees of success. We first reviewed the literature on coordination and determined what is known about coordination of knowledge in global software projects. From this we developed a new, distinctive knowledge-based model of coordination, which was then employed to analyze two case studies of global software projects, at SAP and Baan, to illustrate the utility of the model.

Supply chain optimisation of pyrolysis plant deployment using goal programming

This paper presents a goal programming model to optimise the deployment of pyrolysis plants in Punjab, India. Punjab has an abundance of waste straw and pyrolysis can convert this waste into alternative bio-fuels, which will facilitate the provision of valuable energy services and reduce open field burning. A goal programming model is outlined and demonstrated in two case study applications: small scale operations in villages and large scale deployment across Punjab's districts. To design the supply chain, optimal decisions for location, size and number of plants, downstream energy applications and feedstocks processed are simultaneously made based on stakeholder requirements for capital cost, payback period and production cost of bio-oil and electricity. The model comprises quantitative data obtained from primary research and qualitative data gathered from farmers and potential investors. The Punjab district of Fatehgarh Sahib is found to be the ideal location to initially utilise pyrolysis technology. We conclude that goal programming is an improved method over more conventional methods used in the literature for project planning in the field of bio-energy. The model and findings developed from this study will be particularly valuable to investors, plant developers and municipalities interested in waste to energy in India and elsewhere. © 2014 Elsevier Ltd. All rights reserved.

Reconfiguration of supply chain network:an ISM-based roadmap to performance

Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

Experimental Support of Argument-based Syntactic Computation

Linguistic theory, cognitive, information, and mathematical modeling are all useful while we attempt to achieve a better understanding of the Language Faculty (LF). This cross-disciplinary approach will eventually lead to the identification of the key principles applicable in the systems of Natural Language Processing. The present work concentrates on the syntax-semantics interface. We start from recursive definitions and application of optimization principles, and gradually develop a formal model of syntactic operations. The result – a Fibonacci- like syntactic tree – is in fact an argument-based variant of the natural language syntax. This representation (argument-centered model, ACM) is derived by a recursive calculus that generates a mode which connects arguments and expresses relations between them. The reiterative operation assigns primary role to entities as the key components of syntactic structure. We provide experimental evidence in support of the argument-based model. We also show that mental computation of syntax is influenced by the inter-conceptual relations between the images of entities in a semantic space.

Localized waves in optical systems with periodic dispersion and nonlinearity management

We overview our recent developments in the theory of dispersion-managed (DM) solitons within the context of optical applications. First, we present a class of localized solutions with a period multiple to that of the standard DM soliton in the nonlinear Schrödinger equation with periodic variations of the dispersion. In the framework of a reduced ordinary differential equation-based model, we discuss the key features of these structures, such as a smaller energy compared to traditional DM solitons with the same temporal width. Next, we present new results on dissipative DM solitons, which occur in the context of mode-locked lasers. By means of numerical simulations and a reduced variational model of the complex Ginzburg-Landau equation, we analyze the influence of the different dissipative processes that take place in a laser.

Cultural Knowledge for Named Entity Disambiguation: A Graph-Based Semantic Relatedness Approach

One of the ultimate aims of Natural Language Processing is to automate the analysis of the meaning of text. A fundamental step in that direction consists in enabling effective ways to automatically link textual references to their referents, that is, real world objects. The work presented in this paper addresses the problem of attributing a sense to proper names in a given text, i.e., automatically associating words representing Named Entities with their referents. The method for Named Entity Disambiguation proposed here is based on the concept of semantic relatedness, which in this work is obtained via a graph-based model over Wikipedia. We show that, without building the traditional bag of words representation of the text, but instead only considering named entities within the text, the proposed method achieves results competitive with the state-of-the-art on two different datasets.

A New Class of Processes for Formalizing and Generalizing Individual-Based Models: The Semi-Semi-Markov Processes

2000 Mathematics Subject Classification: 60K15, 60K20, 60G20,60J75, 60J80, 60J85, 60-08, 90B15.

NLSE-based modelling of a random distributed feedback fiber laser

Random distributed feedback (DFB) fiber lasers have attracted a great attention since first demonstration [1]. Despite big advance in practical laser systems, random DFB fiber laser spectral properties are far away to be understood or even numerically modelled. Up to date, only generation power could be calculated and optimized numerically [1,2] or analytically [3] within the power balance model. However, spectral and statistical properties of random DFB fiber laser can not be found in this way. Here we present first numerical modelling of the random DFB fiber laser, including its spectral and statistical properties, using NLSE-based model. © 2013 IEEE.

Game-based Approach in e-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

Practice based learning approaches in collaborative design and engineering education:a case study investigation into the benefits of a crossdisciplinary practice based learning strategy

This study explores the ongoing pedagogical development of a number of undergraduate design and engineering programmes in the United Kingdom. Observations and data have been collected over several cohorts to bring a valuable perspective to the approaches piloted across two similar university departments while trialling a number of innovative learning strategies. In addition to the concurrent institutional studies the work explores curriculum design that applies the principles of Co-Design, multidisciplinary and trans disciplinary learning, with both engineering and product design students working alongside each other through a practical problem solving learning approach known as the CDIO learning initiative (Conceive, Design Implement and Operate) [1]. The study builds on previous work presented at the 2010 EPDE conference: The Effect of Personality on the Design Team: Lessons from Industry for Design Education [2]. The subsequent work presented in this paper applies the findings to mixed design and engineering team based learning, building on the insight gained through a number of industrial process case studies carried out in current design practice. Developments in delivery also aligning the CDIO principles of learning through doing into a practice based, collaborative learning experience and include elements of the TRIZ creative problem solving technique [3]. The paper will outline case studies involving a number of mixed engineering and design student projects that highlight the CDIO principles, combined with an external industrial design brief. It will compare and contrast the learning experience with that of a KTP derived student project, to examine an industry based model for student projects. In addition key areas of best practice will be presented, and student work from each mode will be discussed at the conference.

Knowledge representation and evaluation an ontology-based knowledge management approach

Competition between Higher Education Institutions is increasing at an alarming rate, while changes of the surrounding environment and demands of labour market are frequent and substantial. Universities must meet the requirements of both the national and European legislation environment. The Bologna Declaration aims at providing guidelines and solutions for these problems and challenges of European Higher Education. One of its main goals is the introduction of a common framework of transparent and comparable degrees that ensures the recognition of knowledge and qualifications of citizens all across the European Union. This paper will discuss a knowledge management approach that highlights the importance of such knowledge representation tools as ontologies. The discussed ontology-based model supports the creation of transparent curricula content (Educational Ontology) and the promotion of reliable knowledge testing (Adaptive Knowledge Testing System).

Delay-sensitive service request scheduling for cloud computing

Cloud computing realizes the long-held dream of converting computing capability into a type of utility. It has the potential to fundamentally change the landscape of the IT industry and our way of life. However, as cloud computing expanding substantially in both scale and scope, ensuring its sustainable growth is a critical problem. Service providers have long been suffering from high operational costs. Especially the costs associated with the skyrocketing power consumption of large data centers. In the meantime, while efficient power/energy utilization is indispensable for the sustainable growth of cloud computing, service providers must also satisfy a user's quality of service (QoS) requirements. This problem becomes even more challenging considering the increasingly stringent power/energy and QoS constraints, as well as other factors such as the highly dynamic, heterogeneous, and distributed nature of the computing infrastructures, etc. ^ In this dissertation, we study the problem of delay-sensitive cloud service scheduling for the sustainable development of cloud computing. We first focus our research on the development of scheduling methods for delay-sensitive cloud services on a single server with the goal of maximizing a service provider's profit. We then extend our study to scheduling cloud services in distributed environments. In particular, we develop a queue-based model and derive efficient request dispatching and processing decisions in a multi-electricity-market environment to improve the profits for service providers. We next study a problem of multi-tier service scheduling. By carefully assigning sub deadlines to the service tiers, our approach can significantly improve resource usage efficiencies with statistically guaranteed QoS. Finally, we study the power conscious resource provision problem for service requests with different QoS requirements. By properly sharing computing resources among different requests, our method statistically guarantees all QoS requirements with a minimized number of powered-on servers and thus the power consumptions. The significance of our research is that it is one part of the integrated effort from both industry and academia to ensure the sustainable growth of cloud computing as it continues to evolve and change our society profoundly.^