Pentane isomerization and disproportionation catalyzed by sulfated zirconia promoted with iron and manganese

Fe- and Mn-promoted sulfated zirconia was used to catalyze the conversion ofn-pentane in a flow reactor at temperatures in the range of –25 to 40C andn-pentane partial pressures in the range of 0.005 to 0.01 atm. The rates of reaction increased with time on stream during an induction period and then decreased rapidly. The predominant reaction at –25C and short times on stream was isomerization to give isopentane; no dibranched products were observed. The selectivity for isomerization decreased and that for disproportionation increased with increasing temperature, with disproportionation becoming predominant at 40C; the principal product was then isobutane. The product distribution data are consistent with acid-base catalysis and carbocation intermediates. However, there appears to be more to the reaction mechanism than acid-base chemistry, and the roles of the iron and manganese promoters are not yet explained.     

Activity Awareness as an Enabler for Communication and Network Building in Construction Design Teams

The paper reports on ongoing research into the facilitation of communication in distributed design teams of the type typically encountered in the construction sector. Ideas around social aspects in such design teams are discussed followed by our previous research efforts as an evolutionary process that has led us to develop in this direction. It is argued that facilitating timely and contextually grounded communication in a distributed environment can help to build the social networks and associated social capital common in collocated design teams but often absent in distributed ones. We describe our framework for providing such facilitation through monitoring and awareness of the information “space” of a construction project. We believe that by leveraging the relationships in the information space, we can go some way to identifying those individuals who would benefit from developing interpersonal relations in their work and further by exploiting those relationships in real time we can accelerate the formation of personal social networks and social capital between those individuals.     

Ontology-Centered Knowledge Management Using Information Retrieval Techniques

The paper argues that an effective solution to information and knowledge management (KM) needs of practitioners in the construction industry can be found in the provision of an adapted knowledge environment that makes use of user profiling and document summarization techniques based on information retrieval sciences. The conceptualization of the domain through ontology takes a pivotal role in the proposed knowledge environment and provides a semantic referential to ensure relevance, accuracy, and completeness of information. A set of KM services articulated around the selected ontology have been developed, using the Web services model, tested, and validated in real organizational settings. This provided the basis for formulating recommendations and key success factors for any KM project development.     

Microarchitected Stretching‐Dominated Mechanical Metamaterials with Minimal Surface Topologies

Historically, the creation of lightweight, yet mechanically robust, materials have been the most sought‐after engineering pursuit. For that purpose, research efforts are dedicated to finding pathways to emulate and mimic the resilience offered by natural biological systems (i.e., bone and wood). These natural systems evolved over time to provide the most attainable structural efficiency through their architectural characteristics that can span over multiple length scales. Nature‐inspired man‐made cellular metamaterials have effective properties that depend largely on their topology rather than composition and are hence remarkable candidates for a wide range of application. Despite their geometrical complexity, the fabrication of such metamaterials is made possible by the emergence of advanced fabrication techniques that permit the fabrication of complex architectures down to the nanometer scale. In this work, we report the fabrication and mechanical testing of nature‐inspired, mathematically created, micro‐architected, cellular metamaterials with topologies based on triply periodic minimal surfaces (TPMS) with cubic symmetries fabricated through direct laser writing two‐photon lithography. These TPMS‐based microlattices are sheet/shell‐ and strut‐based metamaterials with high geometrical complexity. Interestingly, results show that TPMS sheet‐based microlattices follow a stretching‐dominated mode of deformation, and further illustrate their mechanical superiority over the traditional and well‐known strut‐based microlattices and microlattice composites. The TPMS sheet‐based polymeric microlattices exhibited mechanical properties superior to other micrloattices comprising metal‐ and ceramic‐coated polymeric substrates and, interestingly, are less affected by the change in density, which opens the door for fabricating ultralightweight materials without much sacrificing mechanical properties.

     

Ethylene‐methyl acrylate‐glycidyl methacrylate toughened poly(lactic acid) nanocomposites

Poly (lactic acid) (PLA) was melt blended in a twin screw extruder using an ethylene‐methyl acrylate‐glycidyl methacrylate rubber as a toughener. PLA/rubber blends were immiscible as observed by scanning electron microscopy. Impact strength and ductility of PLA were improved by the addition of the rubber at the expense of strength and stiffness. An organo‐montmorillonite (OMMT) was used at 2 wt % to counteract the negative effect of the rubber on modulus, and balanced properties were observed at 10 wt % rubber content. X‐ray diffraction and transmission electron microscopy revealed the formation of intercalated/exfoliated structure in the ternary nanocomposites. Thermal behavior analysis indicated that the degree of crystallinity is slightly affected by the clay and the rubber. Both the clay and the rubber decreased the crystallization temperature of PLA and acted as nucleating agents for PLA. The viscosity of the mixtures as measured by melt flow index was highly influenced by the rubber and the OMMT. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Computational intelligence techniques for HVAC systems: A review

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.     

Mixing Static and Dynamic Partitioning to Parallelize a Constraint Programming Solver

This paper presents an external parallelization of Constraint Programming (CP) search tree mixing both static and dynamic partitioning. The principle of the parallelization is to partition the CP search tree into a set of sub-trees, then assign each sub-tree to one computing core in order to perform a local search using a sequential CP solver. In this context, static partitioning consists of decomposing the CP variables domains in order to split the CP search tree into a set of disjoint sub-trees to assign them to the cores. This strategy performs well without adding an extra cost to the parallel search, but the problem is the load imbalance between computing cores. On the other hand, dynamic partitioning is based on preservation of the search state to generate, dynamically or on demand, the sub-trees that are assigned to the cores. This strategy offers good load balancing between the different computing cores, but computing overcosts appear due to the initialisation of the search when a sub-tree is migrated from one core to another. In this paper, we propose a new partitioning strategy that mixes the static and dynamic partitioning and enjoys the benefits of each strategy. This mixed partitioning is designed to run on shared and distributed memory architectures. The performances obtained are illustrated by solving the CP problems modelled using the FlatZinc format and solved using the Google OR-Tools solver on top of the parallel Bobpp framework.