A few formal methods have been developed to support design by analogy such as Synectics which is a group idea generation method that uses four types of analogies to solve problems: personal (be the problem), direct (functional or natural), symbolic and fantasy . Synectics gives little guidance to designers about how to find successful analogies. Other methods also base analogies on the natural world. French [5, 8], highlights the powerful examples nature provides for design. Biomimetic concept generation provides a systematic tool to index biological phenomena [6, 9]. From the functional requirements of the problem, keywords are derived. The keywords are then referenced to an introductory college textbook and relevant entries can be found. Analogous concepts can also be identified by creating abstracted functional models of concepts and comparing the similarities between their functionalities. Analogous and non-obvious products can be explored using the functional and flow basis . This approach requires a database of products represented in the function and flow basis.
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The main objective of this work is to generate a mathematical model for the optimal design and strategic planning of the forest supply chain in order to optimize its economical performance. Different production facilities, products and raw materials are considered, as well as integrated industrial installation sites conforming production clusters. Forest industries are strongly related since raw materials have different uses. From its processing, diverse byproducts are obtained that, at the same time, can be used to manufacture different products. The proximity between facilities can encourage these integration approaches but affect severely transportation costs, for example. Also, the proposed approach considers in detail the processing of residues and byproducts. Many times, these elements are discarded, giving priority to the main components of the production system. The presented model considers that all these elements are critical for a correct assessment of the total system contemplated in the forest SC. Taking into account that the viability of many options depends on the appropriate byproducts processing, this work includes a detailed analysis of the different generated residues, their characteristics and the different possible production alternatives. Finally, the possibility of biofuels production from forest resources is incorporated considering that, nowadays, it is a basic option for the efficient performance of the forest sector.
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Abstract High-performance mechanical-transmission heads are one of the most complex, costly and problematic parts of a milling machine, owing to the large amount of piping required for transporting fluids and to the high level of mechanical performance that is required from them. This study proposes a strategy for optimising the design and manufacture of head bodies by using aluminium alloys and by integrating tubular stainless steel inserts in the casting of the head. These tubular inserts that are integrated into the aluminium mass are an alternative to cooling conduits currently made by machine drilling. As demonstrated in the experimental validation of the first prototype, the new method has created a design that retains the same mechanical performance, increases its reliability and reduces the weight of the milling machine’s moving parts.
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Such as the objective function g has been deﬁned, it could represent diﬀerent ways to measure energy depending on the choice of the parameters a α and a β . There- fore, the motivation for solving (V P ) would be to design macroscopic conducting devices, made up of graded materials with desired energy properties under the ac- tion of the charge density Q and the value of the temperature u 0 on the boundary. As we pointed before, a general feature of this kind of problems is the lack of optimal solutions within the class of characteristic functions, χ  (due to the non- convexity in the admissible set of designs). It is precisely this binary structure of the design problem that suggests us not to solve it directly because of two main rea- sons. The ﬁrst one is the fact that as ﬁner meshes are used, the number of material distribution combinations increases in an astronomical way, making the direct opti- mization process infeasible; and the second is that there does not exist convergence with mesh-reﬁnement in the successive optimized layouts (mesh-dependence). An alternative to overcome this ill-posedness of the problem would consist of using a relaxation method. In this case such relaxation, based on a recent perspective to tackle the design problem, proceeds in two steps :ﬁrst, the state law is included in the cost functional by saying that if an admisible pair (χ, u) veriﬁes the state equation, then the new cost functional is equal to the old one and otherwise, the integrand takes the value + ∞ , (so as to forbid this situation). In this way, we get a reformulated problem as a vector variational problem avoiding the nonlocal 6 nature of the state law. This new reformulation itself forces us to introduce a new scalar ﬁeld v and consequently, to consider now a vector problem in the pair (u, v) instead of the previous version, which was purely scalar. The second step consists of relaxing the reformulated problem. Since the reformulated one is a vector problem, the con- vexiﬁcation of the problem does not give the relaxation we are looking for (contrary as what happens for scalar problems). By contrast, it is the quasiconvexiﬁcation  which gives us the desired envelope. These two steps are discussed more in detailed in Chapter 2.
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Synopsis (100/100 words): Diffusion-Weighted MRI (DW-MRI) often suffers from motion-related artifacts in organs that experience physiological motion. Importantly, organ motion during the application of diffusion gradients results in signal losses, which complicate image interpretation and bias quantitative measures. Motion-compensated gradient designs have been proposed, however they typically result in substantially lower b-values or severe concomitant gradient effects. In this work, we develop an approach for design of first- and second-order motion-compensated gradient waveforms based on a b-value maximization formulation including concomitant gradient nulling, and we compare it to existing techniques. The proposed design provides optimized b-values with motion compensation and concomitant gradient nulling.
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As we can see in the designs obtained in this thesis, we can find patches of electrodes over all the structure. These electrodes can take positive of nega- tive polarity. In Figure 4.3 an example of a manufactured optimized design is shown. We can see two different electrodes. Each electrode is connected to two paths of different colors (pink and yellow) that are connected to the voltage source. They are used to introduce and collect the current. This optimized design is probably one of the most simples examples, however there exist other designs whose polarization is much more complicated. In these case the wiring of the electrical connections will be too much complicated because we have only one path for each polarity. The reduction of the number of electrodes a poste- riori may cause that the response of the device is not the one expected. New ideas are required to be able to introduce this connectivity constraint into the optimization process.
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With the aim of finding friendly celiac food, sor- ghum is presented as a cereal with a high content of nutrients, which has several beneficial properties, especially for those countries that lack other tradi- tional cereals such as wheat, corn, or rice. In addi- tion, sorghum cultivation is economically profitable and it does not contain the proteins that affect celiac patients. In the last years, a variety of “free gluten” food products were developed for improving the celi- ac diet, as well as sorghum beers, which are frequent- ly produced in a home-made manner on a very small scale by individual brewers. However, to the best of our knowledge, there is not a non-alcoholic beverage from sorghum. In this work, a mathematical model for the optimal design of a batch plant for producing malt drink from sorghum at industrial level is pro- posed. The model is formulated as a mixed integer linear problem, which is implemented and solved in GAMS using the CPLEX solver. Through experimen- tal results, design and operation model parameters are obtained in order to develop real-fit formulation. The investment cost is minimized, and a techni- cal-social-economical analysis is presented in order to evaluate the more profitable and sustainable option to produce malt drink from sorghum. For a produc- tion of 5,000 L/d, the payback period is equal to 4.8 years and the unit cost per bottle of 300 mL is $ 0.312. The obtained malt drink with technology presented in this work, meets the physical and organoleptics re- quirements established for its consumption according with the comparison reported by Nieblas 1 , with two
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The optimal design of experiments is based on a theory which, like any general theory, provides a unification of many separate results and a way of genera- ting new results in novel situations. Part of this flexibility results from the algorithms derived from the General Equivalence Theorem, combined with computer-intensive search methods. The use of optimal or highly efficient de- signs in scientific or social research has advantages. Fewer observations and therefore smaller sample sizes are required to find real effects, thus reducing the costs of the study. Our examples in this thesis show that optimal designs can reduce the number of observations even in 40% in some cases when com- pared with the traditional used designs. This is especially beneficial in light of the ever-rising cost of conducting scientific or social studies. From an ethical viewpoint, a smaller sample is also highly desirable. For example, fewer pa- tients may be required to undergo a controversial treatment or fewer animals need to be sacrificed in a toxicology study.
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A new strategy to approach multiresponse optimization in conjunction to a D-optimal design for simultaneously optimizing a large number of experimental factors is proposed. The procedure is applied to the determination of biogenic amines (histamine, putrescine, cadaverine, tyramine, tryptamine, 2-phenylethylamine, spermine and spermidine) in swordfish by HPLC-FLD after extraction with an acid and subsequent derivatization with dansyl chloride. Firstly, the extraction from a solid matrix and the derivatization of the extract are optimized. Ten experimental factors involved in both stages are studied, seven of them at two levels and the remaining at three levels; the use of a D-optimal design leads to optimize the ten experimental variables, significantly reducing by a factor of 67 the experimental effort needed but guaranteeing the quality of the estimates. A model with 19 coefficients, which includes those corresponding to the main effects and two possible interactions, is fitted to the peak area of each amine. Then, the validated models are used to predict the response (peak area) of the 3456 experiments of the complete factorial design. The variability among peak areas ranges from 13.5 for 2-phenylethylamine to 122.5 for spermine, which shows, to a certain extent, the high and different effect of the pretreatment on the responses. Then the percentiles are calculated from the peak areas of each amine. As the experimental conditions are in conflict, the optimal solution for the multiresponse optimization is chosen from among those which have all the responses greater than a certain percentile for all the amines. The developed procedure reaches decision limits down to 2.5 µg L -1 for cadaverine or 497 µg L -1 for histamine in solvent and 0.07 mg kg -1 and 14.81 mg kg -1 in fish (probability of false positive equal to 0.05), respectively.
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Abstract Optimal design is a crucial issue in Environ- mental measurement with typical time–space correlated observations. A modified Arrhenius model with a particular correlation structure will be applied to the methane removal in the atmosphere, a very important environmental issue at this moment. We introduce a class of integrated compound criteria for obtaining robust designs. In partic- ular, the paper provides an insight into the relationship of a compound D-optimality criterion for both the trend and covariance parameters, and the Integrated Mean Squared Prediction Error (IMSPE) criterion. In general, if there are two or more approaches of a given problem, e.g. two rival models or two different parts of a model, an integral relationship may be constructed with the aim of finding a suitable compromise between them. The Fisher informa- tion matrix (FIM) will be used in both cases. Then the
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Optimal control reached maturity in the 1960’s, with the development of the linear quadratic (LQ) optimal control methodology, for its application in spacecraft control during the Space Race between the former Soviet Union and the United States. For these kind of applications, to achieve a good rocket manoeuvring with minimum fuel consumption can be well defined and easily formulated as an optimization problem [Skogestad and Postlethwaite, 2007]. Even though LQ optimal control, in particular Linear Quadratic Gaussian (LQG) control, was proved successful for aerospace engineering and other frameworks, its use in other industrial applications is, in practice, not robust enough; accurate plant models were frequently not available, and the assumption of white noise disturbances was not always relevant or meaningful to practising control engineers [Skogestad and Postlethwaite, 2007]. This resulted in the development of other optimal control frameworks, like the H ∞ control synthesis used in this dissertation.
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Emotion and motivation are considered key factors in educational processes, to the point that emotions such as anxiety or frustration can impede learning and decrease student’s perception of self-efficacy, while emotions such as joy, awe, and arousal increase the interest and motivation to learn. This thesis defines an optimal learning experience as one that creates conditions that promote learning and emotions that facilitate it. Designing an optimal experience for all is complex, since experience is a personal and subjective interpretation of our interaction with the world, and therefore different for each student. It is for this reason that a learning environment that promotes an optimal experience requires the provision of ways for the expression of individual differences and conditions so that students can manage them. An example of these conditions is the perception of difficulty of an activity. It should be possible to adjust the difficulty to the ability of each student, since an imbalance between these two elements fosters emotions such as anxiety or boredom (Nakamura & Csikszentmihalyi, 2014) that negatively impact learning and academic achievement (Prekrun, 2006; Pekrun, 2010). To manage this and other relevant conditions, this thesis aims to design the learning experience by combining theories that describe the needs that motivate people with the conditions of interaction that foster an optimal experience according to psychology, the design of learning environments, user experiences and video games.
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Abstract. In this work, an improved approach for Takagi-Sugeno sys tem identification is used. Linear Quadratic Regulator is applied for an optimal state feedback. Duality theorem and Linear Quadratic Regula tor is applied for an optimal state estimation. Simulation results over the ball and beam nonlinear model show a stable closed loop in the full range and good transient response.
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In electronics, noise is a random fluctuation in an electrical signal, and is present in all electronic circuits. It constitutes an important issue in the design of integrated cir- cuits, since it affects the accuracy of the signals processed. Noise generated by electronic devices, such as bipolar transistors and MOSFETs, varies greatly, as it can be produced by several different physical processes. There are three sources of fundamental noise in MOSFETs (Gray et al., 2001): shot noise due to gate leakage current, thermal (for strong inversion operation) or shot (for weak inversion operation) noise in the channel, which is always white, and flicker or 1/f noise, also called low-frequency noise. These noise sources have been widely studied throughout the years, and several works about them can be found in the literature. References (Gray et al., 2001; Jindal, 2006) are good start points for introducing the reader into this subject.
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– Design patterns help you identify less-obvious abstractions and the objects that can capture them. For example, objects that represent a objects that can capture them. For example, objects that represent a process or algorithm don't occur in nature, yet they are a crucial part of flexible designs. The Strategy (315) pattern describes how to implement interchangeable families of algorithms. The State (305) pattern represents each state of an entity as an object. These objects are seldom found
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A computational fluid dynamics-based design system with the integration of three blade de- sign approaches, automatic mesh generator and CFD codes enables a quick and efficient design optimization of turbine components. This examples include sophisticated Large Eddy Simula- tions (LES) in a Francis turbine and in a centrifugal pump impeller at design and off-design conditions. However, a robust and fully 3D inverse design approach, by which the required flow characteristics and parameters are specified as inputs and the corresponding blade geometry is computed and generated as output, is still not commonly implemented. The governing equa- tions for this phenomena are for turbulent flow, but the current assumptions still dwell on the inviscid approach. A viscous CFD solver is needed. The design has to be evaluated by the solver and the solution must be updated to modify the input (Wu et al., 2007). The inviscid Quasi 3-Dimensional (Q3D) codes by means of both finite difference method and FEM incorporated into this system are primarily employed in the preliminary optimization stages due to their rapid convergence rate and reliability. Using the methodology described in Fig.1.6 a francis turbine is optimized. Developed for nearly 2 decades, mesh handling and generation, CFD analysis and design optimization is integrated under one single iterative process. As an example, on the right hand side of the figure, a redesigning the vanes of the runner is shown.
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normal vectors. An SMS skinning process can finally be used to fill the gaps between the sep- arated points, fully defining both optical surfaces. A segment can be interpolated between the two symmetric adjacent points of the bottom surface, as indicated as solid lens profile in Fig. 1. As a boundary condition, the segment has to match point coordinates and normal vectors at the initial points, which requires at least a 2 nd order polynomial function. However, in principle, any analytical function satisfying this boundary condition can be applied - which correspon- dents to an infinite parameter space for the initial segment problem. For small design angles and moderate lens thicknesses, the initial segment represents only a small fraction of the en- tire lens profiles. However, with increasing design angles and/or distances between the optical surfaces the relative importance of the initial segment increases as well. In extreme cases, the initial segment can completely define the full lens profiles as shown in Fig. 1(f). A selected 2 nd order polynomial segment may guarantee coupling of two ray sets with chosen design angles of opposite sign, but it does not make any further use of the full potential offered by an unre- stricted initial segment satisfying the boundary condition. Therefore, the main objective of this work is to find ways to construct initial segments which ensure maximum benefit from these infinite degrees of freedom.
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In the last years, Evolutionary Algorithms (EA's) have come to be considered as a very powerful and versatile class of techniques for a wide variety of complex optimisation tasks. Different evolution-inspired paradigms have been proposed (genetic algorithms, evolution programs, evolution strategies, genetic programming ,), each of them best suited for a particular type of problem. The efficiency of these approaches is out of question (at least in this paper). What we want to examine here is a rather theoretical side of the general evolutionary approach. This aspect is the question about the conditions of convergence of an evolution-inspired program, i.e. under which conditions such type of program can be guaranteed to attain, in a finite time, the optimal solution for a given problem. We said rather, but in no way purely theoretical, since the conclusions of this analysis could be, in certain cases, decisive for the usefulness of a technique.
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Asymmetric structures experience uneven deformation demand among different resisting planes and stories when subjected to earthquake excitation. Damage is focused in some elements jeopardizing structural integrity. These structures are common in professional practice because of architectural and functionality constraints. In this scenario the use of energy dissipation devices (EDD) has arisen as an advisable solution to balance and minimize structural damage. Procedures for the design of linear structures equipped with EDD have been widely proposed in the literature, few of them deal with the optimum spatial distribution of nonlinear systems. This paper evaluates and compares the optimized spatial damper distribution of linear and nonlinear systems. An optimization technique is presented based on control indexes called min – max algorithm. Then, this technique is compared with two simple methodologies: (i) the fully stressed design, which is an analysis-redesign procedure, and (ii) the simpli ﬁ ed sequential search algorithm (SSSA), which is a sequential method. It is pointed out that the SSSA is a ﬁ xed step coordinate descent type method. The examples considered show that the SSSA is a discrete approximation of the min – max algorithm, not only for linear but also for nonlinear structures equipped with linear and nonlinear EDD. Furthermore, it is found that the distribution of EDD obtained from a linear analysis is a good approximation of the nonlinear optimal solution. The SSSA is a reliable method that can be applied to achieve drift and torsional balance for design purposes; moreover, it can be implemented with conventional tools available in professional practice. Copyright © 2012 John Wiley & Sons, Ltd.
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4. The previous design methodology obtains optimal filters using the classical and symmet- ric structure of a PLF. Going beyond this structure, a new design methodology has been developed to obtain responses of filters that cannot be otherwise possible, thanks, mainly, to the mode conversion phenomenon. In chapter 7 this phenomenon is studied in detail through two modal models that characterize the modal behavior of networks with CMCs and capacitors placed in the PLN terminals. These models allow the direct visualization of the effects produced by their asymmetrization. Analyzing the results obtained from synthetic DUTs and PLNs, it is shown that, under certain conditions, specially for unbal- anced DUTs and/or PLNs, the mode conversion improves the response of the PLF using the same or even less number of components than the symmetric one. This fact has also been corroborated with actual implementations of asymmetric filters connected to actual devices, allowing the elimination of superfluous components or the improvement of the filtering response at some particular frequencies.
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