Solvothermal synthesis,nanostructural characterization and gas cryo-adsorption studies in a metal–organic framework (IRMOF-1) material

A nanoporous metal–organic framework material, exhibiting an IRMOF-1 type crystalline structure, was prepared by following a direct solvothermal synthesis approach, using zinc nitrate and terephthalic acid as precursors and dimethylformamide as solvent, combined with supercritical CO₂ activation and vacuum outgassing procedures. A series of advanced characterization methods were employed, including scanning electron microscopy, Fourier-transform infrared radiation spectroscopy and X-ray diffraction, in order to study the morphology, surface chemistry and structure of the IRMOF-1 material directly upon its synthesis. Porosity properties, such as Brunauer–Emmet–Teller (BET) specific area (～520 m²/g) and micropore volume (～0.2 cm³/g), were calculated for the activated sample based on N₂ gas sorption data collected at 77 K. The H₂ storage performance was preliminary assessed by low-pressure (0–1 bar) H₂ gas adsorption and desorption measurements at 77 K. The activated IRMOF-1 material of this study demonstrated a fully reversible H₂ sorption behavior combined with an adequate gravimetric H₂ uptake relative to its BET specific area, thus achieving a value of ～1 wt.% under close-to-atmospheric pressure conditions.     

Leading edge erosion of wind turbines: Effect of solid airborne particles and rain on operational wind farms

Leading edge erosion (LEE) affects almost all wind turbines, reducing their annual energy production and lifetime profitability. This study presents results of an investigation into 18 operational wind farms to assess the validity of the current literature consensus surrounding LEE. Much of the historical research focuses on rain erosion, implying that this is the predominant causal factor. However, this study showed that the impact of excessive airborne particles from seawater aerosols or from adverse local environments such as nearby quarries greatly increases the levels of LEE. Current testing of leading edge protection coatings or tapes is based on a rain erosion resistivity test, which does little to prove its ability to withstand solid particle erosion and may drive coating design in the wrong direction. Furthermore, it was shown that there is little correlation between test results and actual field performance. A method of monitoring the expected level of erosion on an operational wind turbine due to rain erosion is also presented. Finally, the energy losses associated with LEE on an operational wind farm are examined, with the average annual energy production dropping by 1.8% due to medium levels of erosion, with the worst affected turbine experiencing losses of 4.9%.     

Discharge Redistribution as a Key Process for Heuristic Optimization of Energy Production with Pumps as Turbines in a Water Distribution Network

Water Resources Management - Water distribution networks often exhibit excess pressure that could lead to extensive leakage and infrastructure damages. While this problem can be mitigated with...     

On using reservoir computing for sensing applications: exploring environment-sensitive memristor networks

Abstract

Recently, the SWEET sensing setup has been proposed as a way of exploiting reservoir computing for sensing. The setup features three components: an input signal (the drive), the environment and a reservoir, where the reservoir and the environment are treated as one dynamical system, a super-reservoir. Due to the reservoir-environment interaction, the information about the environment is encoded in the state of the reservoir. This information can be inferred (decoded) by analysing the reservoir state. The decoding is done by using an external drive signal. This signal is optimised to achieve a separation in the space of the reservoir states: Under different environmental conditions, the reservoir should visit distinct regions of the configuration space. We examined this approach theoretically by using an environment-sensitive memristor as a reservoir, where the memristance is the state variable. The goal has been to identify a suitable drive that can achieve the phase space separation, which was formulated as an optimization problem, and solved by a genetic optimization algorithm developed in this study. For simplicity reasons, only two environmental conditions were considered (describing a static and a varying environment). A suitable drive signal has been identified based on intuitive analysis of the memristor dynamics, and by solving the optimization problem. Under both drives the memristance is driven to two different regions of the one-dimensional state space under the influence of the two environmental conditions, which can be used to infer about the environment. The separation occurs if there is a synchronisation between the drive and the environmental signals. To quantify the magnitude of the separation, we introduced a quality of sensing index: The ability to sense depends critically on the synchronisation between the drive and environmental conditions. If this synchronisation is not maintained the quality of sensing deteriorates.     

Novel Al2O3‐C Refractories with Less Residual Carbon Due to Nanoscaled Additives for Continuous Steel Casting Applications

A new generation of thermal shock resistant Al₂O₃‐C refractories with approximately 30% less residual carbon and functionalized due to nanoscaled additives based on carbon nanotubes (CNTs) and alumina nanosheets (α‐Al₂O₃) were developed and investigated after coking at 1000 and 1400 °C. With the aid of electron backscatter diffraction analyses (EBSD) on fracture surfaces of the carbon bonded samples, Al₃CON was identified on the nanosheet shapes already at 1000 °C coking temperature. The Al₃CON new phase based on the reaction between alumina nanosheets and CNTs offers a chemical interconnecting phase for the carbon as well as for the oxide alumina filler. The new refractory composite structure presents excellent thermo‐mechanical properties in spite the lower carbon content. In addition, due to EDS and EBSD analyses amorphous whiskers and platelets within the system of Si? O were observed in samples coked at 1000 °C, that were transformed to crystalline β‐SiC‐whiskers in samples coked at 1400 °C.     

A triple exponentially weighted moving average control chart for monitoring time between events

Time between events (TBE) charts are used in high-yield processes where the rate of occurrences is very low. In the current article, we propose a triple exponentially weighted moving average control chart to monitor TBE (regarded as triple exponentially weighted moving average TEWMA-TBE chart) modeled by a gamma distribution. One- and two-sided schemes of the proposed chart are designed and compared with the double EWMA DEWMA-TBE and EWMA-TBE charts. It is shown that the lower- and two-sided TEWMA-TBE charts outperform its competitors, especially for small to moderate downward shifts, while the upper-sided TEWMA-TBE chart has very good detection ability for small shifts. We also study the robustness of the proposed chart when the true distribution is a Weibull or a lognormal and it is found that the TEWMA-TBE chart has better robustness properties than its competitors, especially for small shifts. Two illustrative examples from airplane accidents and earthquakes are also provided to display the application of the proposed chart.     

Monitoring of zero-inflated Poisson processes with EWMA and DEWMA control charts

The zero-inflated Poisson (ZIP) distribution is an extension of the ordinary Poisson distribution and is used to model count data with an excessive number of zeros. In ZIP models, it is assumed that random shocks occur with probability p, and upon the occurrence of random shock, the number of nonconformities in a product follows the Poisson distribution with parameter λ. In this article, we study in more detail the exponentially weighted moving average control chart based on the ZIP distribution (regarded as ZIP-EWMA) and we also propose a double EWMA chart with an upper time-varying control limit to monitor ZIP processes (regarded as ZIP-DEWMA chart). The two charts are studied to detect upward shifts not only in each parameter individually but also in both parameters simultaneously. The steady-state performance and the performance with estimated parameters are also investigated. The performance of the two charts has been evaluated in terms of the average and standard deviation of the run length, and compared with Shewhart-type and CUSUM schemes for ZIP distribution, it is shown that the proposed chart is very effective especially in detecting shifts in p when λ remains in control (IC) and in both parameters simultaneously. Finally, one real example is given to display the application of the ZIP charts on practitioners.     

Alzheimer’s Disease as Type 3 Diabetes: Common Pathophysiological Mechanisms between Alzheimer’s Disease and Type 2 Diabetes

Globally, the incidence of type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) epidemics is increasing rapidly and has huge financial and emotional costs. The purpose of the current review article is to discuss the shared pathophysiological connections between AD and T2DM. Research findings are presented to underline the vital role that insulin plays in the brain’s neurotransmitters, homeostasis of energy, as well as memory capacity. The findings of this review indicate the existence of a mechanistic interplay between AD pathogenesis with T2DM and, especially, disrupted insulin signaling. AD and T2DM are interlinked with insulin resistance, neuroinflammation, oxidative stress, advanced glycosylation end products (AGEs), mitochondrial dysfunction and metabolic syndrome. Beta-amyloid, tau protein and amylin can accumulate in T2DM and AD brains. Given that the T2DM patients are not routinely evaluated in terms of their cognitive status, they are rarely treated for cognitive impairment. Similarly, AD patients are not routinely evaluated for high levels of insulin or for T2DM. Studies suggesting AD as a metabolic disease caused by insulin resistance in the brain also offer strong support for the hypothesis that AD is a type 3 diabetes.