Nonisothermal melt-crystallization kinetics of isotactic polypropylene synthesized with a metallocene catalyst and compounded with different quantities of an α nucleator

The nonisothermal crystallization kinetics of a metallocene-made isotactic polypropylene (m-iPP) and its compounds with 0.1 wt % and 0.3 wt % of a sorbitol derivative [1,3:2,4-bis(3,4-dimethylbenzylidene)sorbitol (DMDBS); an α nucleator] were investigated by differential scanning calorimetry at different cooling rates from the melt. The nucleation efficiency was proved by a significant increase in the crystallization temperatures (accompanied by a slight augmentation of the degree of crystallinity and a decrease in the crystal sizes). This increase in the crystallization temperatures led to higher amounts of fractional content in the γ polymorph, even though DMDBS was supposed to be a nucleator for the α form. The Avrami and Ozawa methods effectively described only the early stage of crystallization, whereas a combined Avrami–Ozawa method was valid for the whole crystallization process. The values of the exponent for this method decreased for nucleated samples in the later stage of crystallization, especially in the case of m-iPP with 0.3 wt % DMDBS added (m-iPP03). The activation energy of the process and the surface free energy were also estimated. The production of considerable proportions of the γ polymorph in m-iPP03 corresponded to higher values of the activation energy and lower values of the surface free energy. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

The Utility of Land-Surface Model Simulations to Provide Drought Information in a Water Management Context Using Global and Local Forcing Datasets

Drought diagnosis and forecasting are fundamental issues regarding hydrological management in Spain, where recurrent water scarcity periods are normal. Land-surface models (LSMs) could provide relevant information for water managers on how drought conditions evolve. Here, we explore the usefulness of LSMs driven by atmospheric analyses with different resolutions and accuracies in simulating drought and its propagation to precipitation, soil moisture and streamflow through the system. We perform simulations for the 1980-2014 period with SASER (5 km resolution) and LEAFHYDRO (2.5 km resolution), which are forced by the Spanish SAFRAN dataset (at 5km and 30km resolutions), and the global eartH2Observe datasets at 0.25 degrees (including the MSWEP precipitation dataset). We produce standardized indices for precipitation (SPI), soil moisture (SSMI) and streamflow (SSI). The results show that the model structure uncertainty remains an important issue in current generation large-scale hydrological simulations based on LSMs. This is true for both the SSMI and SSI. The differences between the simulated SSMI and SSI are large, and the propagation scales for drought regarding both soil moisture and streamflow are overly dependent on the model structure. Forcing datasets have an impact on the uncertainty of the results but, in general, this impact is not as large as the uncertainty due to model formulation. Concerning the global products, the precipitation product that includes satellite observations (MSWEP) represents a large improvement compared with the product that does not.

     

Interactive visualization of medical volume models in mobile devices

Interactive visualization of volume models in standard mobile devices is a challenging present problem with increasing interest from new application fields like telemedicine. The complexity of present volume models in medical applications is continuously increasing, therefore increasing the gap between the available models and the rendering capabilities in low-end mobile clients. New and efficient rendering algorithms and interaction paradigms are required for these small platforms. In this paper, we propose a transfer function-aware compression and interaction scheme, for client-server architectures with visualization on standard mobile devices. The scheme is block-based, supporting adaptive ray-casting in the client. Our two-level ray-casting allows focusing on small details on targeted regions while keeping bounded memory requirements in the GPU of the client. Our approach includes a transfer function-aware compression scheme based on a local wavelet transformation, together with a bricking scheme that supports interactive inspection and levels of detail in the mobile device client. We also use a quantization technique that takes into account a perceptive metrics of the visual error. Our results show that we can have full interaction with high compression rates and with transmitted model sizes that can be of the order of a single photographic image.     

Robust network monitoring in the presence of non-cooperative traffic queries

We present the design of a predictive load shedding scheme for a network monitoring platform that supports multiple and competing traffic queries. The proposed scheme can anticipate overload situations and minimize their impact on the accuracy of the traffic queries. The main novelty of our approach is that it considers queries as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Our system only requires a high-level specification of the accuracy requirements of each query to guide the load shedding procedure and assures a fair allocation of computing resources to queries in a non-cooperative environment. We present an implementation of our load shedding scheme in an existing network monitoring system and evaluate it with a diverse set of traffic queries. Our results show that, with the load shedding mechanism in place, the monitoring system can preserve the accuracy of the queries within predefined error bounds even during extreme overload conditions.     

Selecting Significant Effects in Factorial Designs Taking Type II Errors into Account

When analysing the effects of a factorial design, it is customary to take into account the probability of making a Type I error (the probability of considering an effect significant when it is non‐significant), but not to consider the probability of making a Type II error (the probability of considering an effect as non‐significant when it is significant). Making a Type II error, however, may lead to incorrect decisions regarding the values that the factors should take or how subsequent experiments should be conducted. In this paper, we introduce the concept of minimum effect size of interest and present a visualization method for selecting the critical value of the effects, the threshold value above which an effect should be considered significant, which takes into account the probability of Type I and Type II errors. Copyright © 2006 John Wiley & Sons, Ltd.     

The effect of ultra-thin graphite on the morphology and physical properties of thermoplastic polyurethane elastomer composites

Composites of thermoplastic polyurethane (TPU) and ultra-thin graphite (UTG) with concentrations ranging from 0.5 wt.% to 3 wt.% were prepared using a solution compounding strategy. Substantial reinforcing effects with increased loadings are achieved. Compared to neat TPU, values for storage modulus and shear viscosity are enhanced by 300% and 150%, respectively, for UTG concentrations of 3 wt.%. Additionally, an enhancement of thermal properties is accomplished. The crystallization temperature and thermal stability increased by 30 °C and 10 °C, respectively, compared to neat TPU. Furthermore, the use of oxidized UTG (UTGO) with its added functional oxygen groups suggests the presence of chemical interactions between UTG and TPU, which additionally impact on the thermal properties of the corresponding composites. Controlling the oxidation degree, thus offers further possibilities to obtain composites with tailored properties. The presented approach is straightforward, leads to homogeneous TPU-UTG composites with improved materials properties and is especially suitable for commercial UTG materials and further up-scaled production.     

Engineering model for intumescent coating behavior in a pilot‐scale gas‐fired furnace

In the event of a fire, intumescent fire protective coatings expand and form a thermally insulating char that protects the underlying substrate from heat and subsequent structural failure. The intumescence includes several rate phenomena, which have been investigated and quantified in the literature for several decades. However, various challenges still exist. The most important one concerns mathematical model validation under realistic exposure conditions and/or time scales. Another is the simplification of advanced models to overcome the often‐seen lack of a complete set of input and adjustable model parameters for a given coating, thereby providing models for industrial applications. In this work, these two challenges are addressed. Three experimental series, with an intumescent coating inside a 0.65 m³ gas‐fired furnace, heating up according to so‐called cellulosic fire conditions, were conducted and a very good repeatability was evident. The experiments were run for almost 3 h, reaching a final gas temperature of about 1100°C. Measurements include transient temperature developments inside the expanding char, at the steel substrate, and in the mineral wool insulation placed behind the substrate. A mathematical model, describing the intumescent coating behavior and temperatures in the furnace using a single overall reaction was developed and validated against experimental data. By including a decomposition front movement through the char, a good qualitative agreement was obtained. After further validation against experiments with other coating formulations, it has potential to become a practical engineering tool. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3947–3962, 2016     

Absorbing photonic crystals for silicon thin-film solar cells: Design,fabrication and experimental investigation

In this paper, we present the integration of an absorbing photonic crystal within a thin-film photovoltaic solar cell. Optical simulations performed on a complete solar cell revealed that patterning the hydrogenated amorphous silicon active layer as a 2D photonic crystal membrane enabled to increase its integrated absorption by 28 % between 300 and 720 nm, comparing to a similar but unpatterned stack. In order to fabricate such promising cells, we developed a high throughput process based on holographic lithography and reactive ion etching. The influences of the parameters taking part in those processes on the obtained patterns are discussed. Optical measurements performed on the resulting “photonized” solar cell structures underline the regularity of the 2D pattern and a significant absorption increase above 550 nm, similarly to what is observed on the simulated absorption spectra. Moreover, our patterned cells are found to be robust with regards to the angle of incidence of the light.