Femtosecond Ti: Sa ultra short-pulse laser irradiation effects on the properties and morphology of the zirconia surface after ageing

Femtosecond pulses from a Ti:Sapphire laser were used to irradiate specimens of yttria-stabilised (35% mol) tetragonal zirconia (Y-TZP) with the purpose of studying the effects of the irradiations on their surface properties and morphology after ageing. Zirconia disks were divided into eight groups (n = 32) according to their surface treatment and subsequent ageing: Control: no treatment; sandblasting: Al₂O₃ sandblasting 50 μm; and ultrashort laser pulses irradiation with 25 μJ pulses, considering two different scanning steps based on the width between two grooves. These groups were duplicated and submitted to ageing. The surfaces were analysed using scanning electron microscopy (SEM), and X-ray diffraction. A finite element analysis, a biaxial flexure test, as well as fractographic and Weibull analyses, were performed. The strengths of the disks were statistically different for the treatment factor, and the principal stresses seemed to be concentrated at the centre of the specimens, as predicted by the computer simulations. Ageing decreased the strengths for all groups and increased the Weibull modulus for the laser group with the 40 μm-width between two grooves. The sandblasting group presented the highest monoclinic phase peak. Although the most significant strength was found within the sandblasting group, the phase transformation was favourable to the laser groups. The Weibull modulus was higher for the laser group with the 60 μm-width between two grooves, confirming the highest homogeneity of its failure distribution. Regardless of the surface treatment, strength was decreased with ageing in all groups. The femtosecond Ti:Sa ultra-short pulse laser irradiation can be suggested as an alternative to the gold standard sandblasting in long-term Y-TZP zirconia rehabilitations, such as crowns and veneers.     

New ways to improve the damping properties in high‐performance thermoplastic vulcanizates

The incorporation of viscoelastic materials represents an effective strategy to reduce the vibratory level of structural components. Thermoplastic vulcanizates (TPVs) are a special type of viscoelastic material that combines the elastomeric properties of rubbers with the easy processing of thermoplastics. In the present work, we propose innovative ways to improve the damping properties of high‐performance TPVs by using rubbers with carboxylic functionalities. For that, TPVs from physical blends of carboxylated hydrogenated acrylonitrile butadiene rubber (XHNBR) and polyamide 6 (PA6) were prepared. The chain dynamics of different mixed crosslink systems containing peroxide, metal oxides and hindered phenolic antioxidants were investigated in order to find the most suitable strategy to design a high‐performance TPV system with upgraded damping properties. The results indicate that the damping performance of the TPV system can be tailored by controlling the type and magnitude of the bonding interactions between the mixed crosslink system and the XHNBR rubber phase. Therefore, this study demonstrates the potential of TPV systems containing carboxylic rubbers as high‐performance damping materials. © 2020 Society of Chemical Industry     

Theoretical Study of the Water–Gas Shift Reaction on a Au/Hematite Model Catalyst

Topics in Catalysis - Using the density functional theory, the mechanism of the water–gas shift reaction has been investigated employing a model catalyst formed by a Au5 cluster supported on...     

Rheokinematics for product development—Formulation screening in rotational rheometers

Product formulations for industrial processes are typically developed at laboratory scale. However, the mixing conditions are not easily mimicked in the laboratory. A rotational device is proposed in this study as a fast laboratory-scale formulation development, which enables mimicking the mixing conditions in the industrial process. The geometrical configurations of the rotational device are from rheometry devices (plate-plate and cone-plate). The main advantages of this method are the small amounts of raw materials and shorter testing times. This methodology is applied to an industrial case study, the reaction injection molding (RIM) process. The mixing length scales evolution in the rotational rheometer were matched to those in RIM machines. The main novelty of this study is the introduction of a protocol that bridges the processing conditions at laboratory using small amounts of raw materials to high throughput continuous flow reactors.     

Influence of photovoltaic generation model and time resolution on the reliability evaluation of distribution systems

This paper aims to investigate the influence of photovoltaic (PV) generation on reliability evaluation of distribution systems. Two PV generation models are used to predict the output power injected into the grid, taking into account the main relevant environmental variables, the irradiance and ambient temperature. Issues that directly affect the output power, such as the spatial smoothing effect due to the plant size and the influence of the irradiance and temperature measurement interval are taken into consideration. Using measurement time series of irradiance and local temperature, the models are used to generate power series in 4‐minute and hourly resolutions. The generated power series are used in a reliability assessment model, with the objective of evaluating the impact of solar resource variability on the reliability indices of the system. Case studies on the IEEE RBTS‐Bus 2 and on the real distribution system of Fernando de Noronha in Brazil are presented and discussed, for power plants of different capacities, considering the effect of the PV generation models, the temporal resolution of the time series and the spatial smoothing of the power output fluctuations. The results show that the power time series in hourly resolution significantly underestimates the frequency of interruptions. For the real system, this index is underestimated at the system level (up to 43%) and at the load points (up to 72%). On the other hand, for the interruption duration index, the temporal aggregation results in a small underestimation (just 4%). The results also indicates that the smoothing effect is irrelevant for typical PV system sizes of distribution systems with discretization equal to or above 4 minutes.     

An unsupervised approach for fault diagnosis of power transformers

Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.     

Hybrid methodology for precipitation estimation using Hydro-Estimator over Brazil

Rainfall measurement is a very important topic to society and for the understanding of the weather and climate, therefore needs to be calculated as accurately as possible. Counteracting the problem of the high temporal and spatial variability of precipitation, geostationary satellites sensors have been proved an excellent tool to this task, providing scans with high temporal resolution and detecting the growth and decay of rain cells. Using infra-red (IR) images obtained from the Geostationary Operational Environmental Satellites (GOES), the Hydro-Estimator (HYDRO) algorithm produces instantaneous precipitation estimates with 30 min temporal resolution and 4 km spatial resolution with a very low latency compared with other more sophisticated methodologies (i.e. passive microwave-based algorithms). However, the IR algorithm has some limitations to estimate precipitation on some cloud systems. In order to overcome this problem, the main objective of this study is to develop a light and fast algorithm, based on the histogram matching (HM) technique, to combine the superior sampling and low latency of the HYDRO IR product with more accurate active microwave-based products over Brazil. The adjusted HYDRO (AHYDRO) product was validated against Brazil rain gauge network for two years (2016–2017) and the performance was assessed by using standard statistical metrics and categorical indices. Results show that the HM technique is able to minimize the large variability and discrepancies among HYDRO and observed precipitation over Brazil. At same time, is able to generate a better bias performance while maintaining the same correlation levels before the adjustment.