21 resultados para Design of communication
em Universidad de Alicante
Resumo:
Pster presentado en Escape 22, European Symposium on Computer Aided Process Engineering, University College London, UK, 17-20 June 2012.
Resumo:
Applied colorimetry is an important module in the program of the elective subject "Colour Science: industrial applications. This course is taught in the Optics and Optometry Degree and it has been used as a testing for the application of new teaching and assessment techniques consistent with the new European Higher Education Area. In particular, the main objective was to reduce the attendance to lessons and encourage the individual and collective work of students. The reason for this approach is based on the idea that students are able to work at their own learning pace. Within this dynamic work, we propose online lab practice based on Excel templates that our research group has developed ad-hoc for different aspects of colorimetry, such as conversion to different colour spaces, calculation of perceptual descriptors (hue, saturation, lightness), calculation of colour differences, colour matching dyes, etc. The practice presented in this paper is focused on the learning of colour differences. The session is based on a specific Excel template to compute the colour differences and to plot different graphs with these colour differences defined at different colour spaces: CIE E, CIE E94 and the CIELAB colour space. This template is implemented on a website what works by addressing the student work at a proper and organized way. The aim was to unify all the student work from a website, therefore the student is able to learn in an autonomous and sequential way and in his own pace. To achieve this purpose, all the tools, links and documents are collected for each different proposed activity to achieve guided specific objectives. In the context of educational innovation, this type of website is normally called WebQuest. The design of a WebQuest is established according to the criteria of usability and simplicity. There are great advantages of using WebQuests versus the toolbox Campus Virtual available in the University of Alicante. The Campus Virtual is an unfriendly environment for this specific purpose as the activities are organized in different sectors depending on whether the activity is a discussion, an activity, a self-assessment or the download of materials. With this separation, it is more difficult that the student follows an organized sequence. However, our WebQuest provides a more intuitive graphical environment, and besides, all the tasks and resources needed to complete them are grouped and organized according to a linear sequence. In this way, the student guided learning is optimized. Furthermore, with this simplification, the student focuses on learning and not to waste resources. Finally, this tool has a wide set of potential applications: online courses of colorimetry applied for postgraduate students, Open Course Ware, etc.
Resumo:
This work addresses the optimization of ammoniawater absorption cycles for cooling and refrigeration applications with economic and environmental concerns. Our approach combines the capabilities of process simulation, multi-objective optimization (MOO), cost analysis and life cycle assessment (LCA). The optimization task is posed in mathematical terms as a multi-objective mixed-integer nonlinear program (moMINLP) that seeks to minimize the total annualized cost and environmental impact of the cycle. This moMINLP is solved by an outer-approximation strategy that iterates between primal nonlinear programming (NLP) subproblems with fixed binaries and a tailored mixed-integer linear programming (MILP) model. The capabilities of our approach are illustrated through its application to an ammoniawater absorption cycle used in cooling and refrigeration applications.
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Paper submitted to AIChE 2012 Annual Meeting: Energy Efficiency by Process Intensification, Pittsburgh, PA, October 28-November 2, 2012.
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In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer with an external NLP solver implemented in Matlab. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.
Resumo:
The main goal of this paper is to present the initial version of a Textile Chemical Ontology, to be used by textile professionals with the purpose of conceptualising and representing the banned and harmful chemical substances that are forbidden in this domain. After analysing different methodologies and determining that Methontology is the most appropriate for the purposes, this methodology is explored and applied to the domain. In this manner, an initial set of concepts are defined, together with their hierarchy and the relationships between them. This paper shows the benefits of using the ontology through a real use case in the context of Information Retrieval. The potentiality of the proposed ontology in this preliminary evaluation encourages extending the ontology with a higher number of concepts and relationships, and validating it within other Natural Language Processing applications.
Resumo:
With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the best available model. However, in practice, these models are usually little more than a black box with a rigid inputoutput structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modularequation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.
Resumo:
We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 43264335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.
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Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.
Resumo:
The footwear industry is a traditional craft sector, where technological advances are difficult to implement owing to the complexity of the processes being carried out, and the level of precision demanded by most of them. The shoe last joining operation is one clear example, where two halves from different lasts are put together, following a specifically traditional process, to create a new one. Existing surface joining techniques analysed in this paper are not well adapted to shoe last design and production processes, which makes their implementation in the industry difficult. This paper presents an alternative surface joining technique, inspired by the traditional work of lastmakers. This way, lastmakers will be able to easily adapt to the new tool and make the most out of their know-how. The technique is based on the use of curve networks that are created on the surfaces to be joined, instead of using discrete data. Finally, a series of joining tests are presented, in which real lasts were successfully joined using a commercial last design software. The method has shown to be valid, efficient, and feasible within the sector.
Resumo:
This article is an updated and modified version of a Spanish article published in MonTi 6 (cf. Tarp 2014a). It deals with specialised translation dictionaries. Based on the principles of the function theory, it analyses the different phases and sub-phases of the translation process from a lexicographical perspective and shows that a translation dictionary should be much more than a mere bilingual dictionary if it really pretends to meet its users complex needs. Thereafter, it presents a global concept of a translation dictionary which includes various mono- and bilingual components in both language directions. Finally, the article discusses, by means of two concrete online projects, how this concept can be applied on the Internet in order to develop high-quality translation dictionaries with quick access to data that are still more adapted to the needs of each translator.
Resumo:
We address the optimization of discrete-continuous dynamic optimization problems using a disjunctive multistage modeling framework, with implicit discontinuities, which increases the problem complexity since the number of continuous phases and discrete events is not known a-priori. After setting a fixed alternative sequence of modes, we convert the infinite-dimensional continuous mixed-logic dynamic (MLDO) problem into a finite dimensional discretized GDP problem by orthogonal collocation on finite elements. We use the Logic-based Outer Approximation algorithm to fully exploit the structure of the GDP representation of the problem. This modelling framework is illustrated with an optimization problem with implicit discontinuities (diver problem).
Resumo:
In this work we study Forward Osmosis (FO) as an emerging desalination technology, and its capability to replace totally or partially Reverse Osmosis (RO) in order to reduce the great amount of energy required in the current desalination plants. For this purpose, we propose a superstructure that includes both membrane based desalination technologies, allowing the selection of only one of the technologies or a combination of both of them seeking for the optimal configuration of the network. The optimization problem is solved for a seawater desalination plant with a given fresh water production. The results obtained show that the optimal solution combines both desalination technologies to reduce not only the energy consumption but also the total cost of the desalination process in comparison with the same plant but operating only with RO.
Resumo:
In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.