The p-Adaptive Biem Approach for Two-Dimensional Elasticity Analysis

This paper presents the development and application of the p-adaptive BIEM version in elastostatics. The basic concepts underlying the p-adaptive technique are summarized and discussed. Some Pascal pseudocodes which show the way how such a technique can be implemented easily in microcomputers are also provided. Both the applicability and the accuracy of the method proposed here are illustrated through a numerical example.

Toward mass production of microtextured microdevices: linking rapid prototyping with microinjection molding

The possibility of manufacturing textured materials and devices, with surface properties controlled from the design stage, instead of being the result of machining processes or chemical attacks, is a key factor for the incorporation of advanced functionalities to a wide set of micro and nanosystems. Recently developed high-precision additive manufacturing technologies, together with the use of fractal models linked to computer-aided design tools, allow for a precise definition and control of final surface properties for a wide set of applications, although the production of larger series based on these resources is still an unsolved challenge. However, rapid prototypes, with controlled surface topography, can be used as original masters for obtaining micromold inserts for final large-scale series manufacture of replicas using microinjection molding. In this study, an original procedure is presented, aimed at connecting rapid prototyping with microinjection molding, for the mass production of two different microtextured microsystems, linked to tissue engineering tasks, using different thermoplastics as ultimate materials.

Particle swarm optimization with sequential niche technique for dynamic finite element model updating

Peer reviewed

A novel hybrid simulation-optimization approach for the optimal design of multicomponent distillation columns

Póster presentado en Escape 22, European Symposium on Computer Aided Process Engineering, University College London, UK, 17-20 June 2012.

Optimal synthesis of liquid-liquid multistage extractors

Presentation in the 11th European Symposium of the Working Party on Computer Aided Process Engineering, Kolding, Denmark, May 27-30, 2001.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Logic-Based Outer Approximation for the Design of Discrete-Continuous Dynamic Systems with Implicit Discontinuities

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).

MINLP Optimization Algorithm for the Synthesis of Heat and Work Exchange Networks

This paper introduces a new optimization model for the simultaneous synthesis of heat and work exchange networks. The work integration is performed in the work exchange network (WEN), while the heat integration is carried out in the heat exchanger network (HEN). In the WEN synthesis, streams at high-pressure (HP) and low-pressure (LP) are subjected to pressure manipulation stages, via turbines and compressors running on common shafts and stand-alone equipment. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as helper motors and generators to respond to any shortage and/or excess of energy, respectively, in the SSTC axes. The heat integration of the streams occurs in the HEN between each WEN stage. Thus, as the inlet and outlet streams temperatures in the HEN are dependent of the WEN design, they must be considered as optimization variables. The proposed multi-stage superstructure is formulated in mixed-integer nonlinear programming (MINLP), in order to minimize the total annualized cost composed by capital and operational expenses. A case study is conducted to verify the accuracy of the proposed approach. The results indicate that the heat integration between the WEN stages is essential to enhance the work integration, and to reduce the total cost of process due the need of a smaller amount of hot and cold utilities.

MINLP Model for the Synthesis of Heat Exchanger Networks with Handling Pressure of Process Streams

This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs), wherein the handling pressure of process streams is used to enhance the heat integration. The proposed approach combines generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation, in order to minimize the total annualized cost composed by operational and capital expenses. A multi-stage superstructure is developed for the HEN synthesis, assuming constant heat capacity flow rates and isothermal mixing, and allowing for streams splits. In this model, the pressure and temperature of streams must be treated as optimization variables, increasing further the complexity and difficulty to solve the problem. In addition, the model allows for coupling of compressors and turbines to save energy. A case study is performed to verify the accuracy of the proposed model. In this example, the optimal integration between the heat and work decreases the need for thermal utilities in the HEN design. As a result, the total annualized cost is also reduced due to the decrease in the operational expenses related to the heating and cooling of the streams.

Optimal Design of a Hybrid Membrane System Combining Reverse and Forward Osmosis for Seawater Desalination

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.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

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.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

3D teaching: the ideal complement for professionals in design and construction

Today, the requirement of professional skills to university students is constantly increasing in our society. In our opinion, the content offered in official degrees need to be nourished with different variables, enriching their global professional knowledge in a parallel way; that is why, in recent years, there is a great multiplicity of complementary courses at university. One of the most socially demanded technical requirements within the architectural, design or engineering field is the management of 3D drawing software, becoming an indispensable reality in these sectors. Thus, this specific training becomes essential over two-dimension traditional design, because the inclusion of great possibilities of spatial development that go beyond conventional orthographic projections (plans, sections or elevations), allowing modelling and rotation of the selected items from multiple angles and perspectives. Therefore, this paper analyzes the teaching methodology of a complementary course for those technicians in the construction industry interested in computer-aided design, using modelling (SketchupMake) and rendering programs (Kerkythea). The course is developed from the technician point of view, by learning computer management and its application to professional development from a more general to a more specific view through practical examples. The proposed methodology is based on the development of real examples in different professional environments such as rehabilitation, new constructions, opening projects or architectural design. This multidisciplinary contribution improves criticism of students in different areas, encouraging new learning strategies and the independent development of three-dimensional solutions. Thus, the practical implementation of new situations, even suggested by the students themselves, ensures active participation, saving time during the design process and the increase of effectiveness when generating elements which may be represented, moved or virtually tested. In conclusion, this teaching-learning methodology improves the skills and competencies of students to face the growing professional demands of society. After finishing the course, technicians not only improved their expertise in the field of drawing but they also enhanced their capacity for spatial vision; both essential qualities in these sectors that can be applied to their professional development with great success.

A Sequential Algorithm for the Rigorous Design of Thermally Coupled Distillation Sequences

A sequential design method is presented for the design of thermally coupled distillation sequences. The algorithm starts by selecting a set of sequences in the space of basic configurations in which the internal structure of condensers and reboilers is explicitly taken into account and extended with the possibility of including divided wall columns (DWC). This first stage is based on separation tasks (except by the DWCs) and therefore it does not provide an actual sequence of columns. In the second stage the best arrangement in N-1 actual columns is performed taking into account operability and mechanical constraints. Finally, for a set of candidate sequences the algorithm try to reduce the number of total columns by considering Kaibel columns, elimination of transfer blocks or columns with vertical partitions. An example illustrate the different steps of the sequential algorithm.

Optimization of Chemical Processes Using Surrogate Models Based on a Kriging Interpolation

Superstructure approaches are the solution to the difficult problem which involves the rigorous economic design of a distillation column. These methods require complex initialization procedures and they are hard to solve. For this reason, these methods have not been extensively used. In this work, we present a methodology for the rigorous optimization of chemical processes implemented on a commercial simulator using surrogate models based on a kriging interpolation. Several examples were studied, but in this paper, we perform the optimization of a superstructure for a non-sharp separation to show the efficiency and effectiveness of the method. Noteworthy that it is possible to get surrogate models accurate enough with up to seven degrees of freedom.