Macroscopic analysis of design processes based on a scheme for coding designers' cognitive actions

We have devised a new scheme for coding designers' cognitive actions from video/audio design protocols. Designers' actions are coded into four cognitive levels; physical, perceptual, functional and conceptual. Relations between actions belonging to different levels, such as dependencies and triggering relations, are also coded. The present scheme has two benefits. First, we found that design actions are definable in a systematic way using the vocabulary of the scheme, and thus a designer's cognitive behaviours in each of local design stages is represented as a structure composed of defined primitive actions. This is expected to lay the foundation for microscopic analyses of how particular types of actions contribute to the formation of key design ideas. Second, this scheme is suitable for macroscopic analyses of how designers cognitively interact with their own sketches. We examined, for a practising architect, the ways in which drawing, inspection of drawings, perception, and functional thoughts correlated with one another in his design process. The findings suggest that design sketches serve not only as external memory or as a provider of visual cues for association of non-visual information, but also as a physical setting in which design thoughts are constructed on the fly.     

Design optimization of 3D steel structures: Genetic algorithms vs. classical techniques

In this paper an elitist genetic algorithm (GA) developed by the authors is compared with common commercial solutions for complex structural optimization. After its prior validation on two-dimensional (2D) structures, the GA was tuned and improved in order to obtain structural elements with minimum weights that satisfy the ultimate limit states of the applicable building code. Subsequently, the same spatial structures were optimized using a commercial structural analysis program. Finally, the cost and weight improvements obtained using the GA, although at a higher computational cost, are discussed.     

Application of reinforcement learning to the game of Othello

Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such complex problems are associated with some difficulties. As we discuss in this article, these methods are plagued by the so-called curse of dimensionality and the curse of modelling. In this article, we discuss reinforcement learning, a machine learning technique for solving sequential decision making problems with large state spaces. We describe how reinforcement learning can be combined with a function approximation method to avoid both the curse of dimensionality and the curse of modelling. To illustrate the usefulness of this approach, we apply it to a problem with a huge state space—learning to play the game of Othello. We describe experiments in which reinforcement learning agents learn to play the game of Othello without the use of any knowledge provided by human experts. It turns out that the reinforcement learning agents learn to play the game of Othello better than players that use basic strategies.     

Capillary-driven pumping for passive degassing and fuel supply in direct methanol fuel cells

In this paper we present a new concept of creating and using capillary pressure gradients for passive degassing and passive methanol supply in direct methanol fuel cells (DMFCs). An anode flow field consisting of parallel tapered channels structures is applied to achieve the passive supply mechanism. The flow is propelled by the surface forces of deformed CO₂ bubbles, generated as a reaction product during DMFC operation. This work focuses on studying the influence of channel geometry and surface properties on the capillary-induced liquid flow rates at various bubbly gas flow rates. Besides the aspect ratios and opening angles of the tapered channels, the static contact angle as well as the effect of contact angle hysteresis has been identified to significantly influence the liquid flow rates induced by capillary forces at the bubble menisci. Applying the novel concept, we show that the liquid flow rates are up to thirteen times higher than the methanol oxidation reaction on the anode requires. Experimental results are presented that demonstrate the continuous passive operation of a DMFC for more than 15 h.     

An Evolutionary Model of Price Competition Among Spatially Distributed Firms

Various studies have shown the emergence of cooperative behavior in evolutionary models with repeated local interaction among spatially distributed agents. We investigate to what extent these findings generalize to evolutionary models of price competition among spatially distributed firms. We consider both one- and two-dimensional models, and we vary the amount of information firms have about competitors in their neighborhood. Our computer simulations show that the emergence of cooperative behavior depends strongly on the amount of information available to firms. Firms tend to behave most cooperatively if they have only a very limited amount of information about their competitors. We provide an intuitive explanation for this phenomenon. Our simulations further indicate that three other factors in our models, namely the accuracy of firms’ information, the probability of experimentation, and the spatial distribution of consumers, have little effect on the emergence of cooperative behavior.     

Through Process Modelling of Surface Densified PM Gears

Through process modelling of surface densified gears produced by powder metallurgy (PM) was established by coupling the modelling of the manufacturing processes surface densification, carburization, and heat treatment. The complete model allows the prediction of the local microstructure and hardness in the gear as well as the appearance and direction of residual stresses in the final part. The structural integrity of the part is governed, on the one hand, by the local material properties and residual stresses and, on the other hand, by the load stresses calculated for typical operating conditions. A simplified hardness dependent Haigh diagram was used to calculate the maximum allowable cyclic stresses for the gear tooth and to derive a local utilization ratio as target entity for optimization of the individual steps of the production chain.     

A qualitative energy-based unified representation for buildings

This paper presents the development of energy-based unified representations for buildings called Archi Bond Graphs and then specialises them as qualitative Archi Bond Graphs that combine graphical representations and qualitative equations. They can be applied to simulations of people behaviour and people-energy behaviour in space-people systems, building energy flows and building energy variations in different building energy systems, and energy interactions between these building subsystems. The applicability of qualitative Archi Bond Graphs is demonstrated through a building simulation for the dynamic energy interactions between the space-people system and building energy systems, including lighting system, and hydraulic system in a town-house design.     

Efficient polymer nanocrystal hybrid solar cells by improved nanocrystal composition

We demonstrate the importance of the nanocrystal surface treatment and the inorganic composition for hybrid solar cells. Mixtures of CdSe nanorods and CdSe quantum dots integrated in hybrid solar cells together with the conjugated polymer poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b']-dithiophene)-alt-4,7-(2,1,3-benzothiadiazole)] (PCPDTBT) perform better than nanorod and quantum dot only based devices. In addition larger sized quantum dots show a similar improvement after integration in respective solar cells. Power conversion efficiency values exceeding 3% are observed. A first result on the shelf lifetime of such a device is highlighted.