Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

Preparation and characterization study on maleic acid cross-linked poly(vinyl alcohol)/chitin/nanocellulose composites

In the quest on improving composite formulations for environmental sustainability, maleic acid (MA) cross-linked poly(vinyl alcohol) (PVA)-α-chitin composites reinforced by oil palm empty fruit bunch fibers (OPEFB)-derived nanocellulose crystals (NCC) had been successfully prepared. Based on the Fourier transform infrared (FTIR) spectroscopic analysis, it was proven that molecular interactions of the cross-linker to the polymeric networks was through conjugated ester linkage. Differential scanning calorimetry (DSC) showed that the influence of MA was minimal toward crystallization in the PVA/chitin/NCC composite. Maximum tensile strength, elongation at break and Young's modulus of the respective PVA/chitin/NCC composites were achieved at different content of MA, dependent on the PVA/chitin mass ratio. Among all compositions, a maximum Young's modulus was achieved at 30 wt% MA loading in PVA/chitin-30/NCC, amounting to 2,413.81 ± 167.36 MPa. Moreover, the mechanical properties and selected physicochemical properties (swelling, gel content, and contact angle) of the PVA/chitin/NCC composites could be tailored by varying the chitin content (10–30 wt%) and MA content (10–50 wt% based on total mass of composite). In brief, this chemically cross-linked PVA-based biocomposites formulated with sustainable resources exhibited tunable physicochemical and mechanical properties.     

Solubility parameter estimation and phase inversion modeling of bentonite-doped polymeric membrane systems

Effects of bentonite concentration on morphology and permeation characteristics of bentonite-doped polysulfone membranes were investigated. Solubility sphere for bentonite was constructed to estimate its solubility parameter. Thermodynamic modeling of phase inversion of this system was carried out using Flory–Huggins theory. The trade-off between thermodynamic and kinetic parameters was used to predict the membrane morphology for bentonite concentration varying from 0 to 5 wt %. The porosity of bentonite-doped membranes decreased up to 3 wt % that increased thereafter. Morphological analysis showed dense cross section with finger-like macrovoids at 3 wt % beyond which it changed to honeycomb structure with large circular voids. Permeability of 3 wt % membrane was the lowest (5.6 × 10⁻¹² m/Pa s) with 95% bovine serum albumin rejection. Contact angle of the membranes decreased from 83 to 66° with bentonite addition making the membrane more hydrophilic. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48450.     

Extraction of Fe(III), Zn(II), and Mn(II) Using a System with a Green Solvent for Trioctylmethylammonium Thiocyanate

Theoretical Foundations of Chemical Engineering - An environmentally friendly solvent, namely, polypropylene glycol 425, has been proposed for the extraction of metal ions from chloride solutions...     

Fluorescence and photon transmission techniques for studying film formation from PS/GO nanocomposites

Polymer Bulletin - Steady-state fluorescence and UV–Vis techniques were used to study the film formation behavior of composites consisting of pyrene (P)-labeled polystyrene (PS) latex and...     

A Biogenic Silica Synthesis Method

Theoretical Foundations of Chemical Engineering - Silica separation and isolation methods providing energy conservation, a decrease in losses and waste of plant raw materials, and the environmental...