Design of backtracking search heuristics for parameter estimation of power signals

Neural Computing and Applications - This study presents a novel implementation of evolutionary heuristics through backtracking search optimization algorithm (BSA) for accurate, efficient and robust...     

Micromechanical Investigation of the Fatigue Crack Propagation and Damage Development in Al/Al2O3/SiC Hybrid Metal Matrix Composite

Russian Journal of Non-Ferrous Metals - In this study, the micro-mechanisms involved in fatigue crack propagation are investigated qualitatively in a Al/Al2O3/SiC hybrid metal matrix composite...     

Rethinking Enterprise Architecture for Sustainable Energy System Development

The development of a sustainable energy system throughout an enterprise is a complex task, which requires an agile holistic approach. Such an approach needs to include a variety of objectives including energy strategy formation and strategic decision-making, which are directly related to the analysis and management of the main areas of sustainable development:The economic, technological, environmental, and social. These multidimensional requirements of sustainability are often difficult to achieve within the enterprise, because these aspects are interrelated and influenced by various internal and external environment factors. This paper first reviews the main challenges for an energy system, and then demonstrates how a strategic agile enterprise architecture driven approach could effectively guide the sustainable energy system development. The study presented in this paper provides a holistic approach that contributes to the advancement and usage of literature dealing with issues of sustainable energy system development and agile enterprise architecture, which has not been discussed before to any great extent.     

A Unified Decision-Making Technique for Analysing Treatments inPandemicContext

The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen before. Medical experts, on the other hand, are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of infection. Further, this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and preferable. The research analysis is based on vast data gathered from professionals and research journals, making this study a comprehensive reference. To solve this challenging task, the researchers used the HF AHP-TOPSIS Methodology, which is a well-known and highly effective Multi-Criteria Decision Making (MCDM) technique. The technique assesses the many treatment options identified through various research papers and guidelines proposed by various countries, based on the recommendations of medical practitioners and professionals. The review process begins with a ranking of different treatments based on their effectiveness using the HF-AHP approach and then evaluates the results in five different hospitals chosen by the authors as alternatives. We also perform robustness analysis to validate the conclusions of our analysis. As a result, we obtained highly corroborative results that can be used as a reference. The results suggest that convalescent plasma has the greatest rank and priority in terms of effectiveness and demand, implying that convalescent plasma is the most effective treatment for SARS-CoV-2 in our opinion. Peepli also has the lowest priority in the estimation.     

Investigation of charge transport mechanism in semiconducting La<Subscript>0.5</Subscript>Ca<Subscript>0.5</Subscript>Mn<Subscript>0.5</Subscript>Fe<Subscript>0.5</Subscript>O<Subscript>3</Subscript> manganite prepared by sol–gel method

Here in, we report the charge transport mechanism in semiconducting La_0.5Ca_0.5Mn_0.5Fe_0.5O₃ (LCMFO) polycrystalline material synthesized via sol–gel auto combustion route. X-ray diffraction (XRD) analysis confirmed the orthorhombic phase of the prepared material. Temperature dependent resistivity and impedance spectroscopy measurements have been carried out to probe the dielectric and electrical conduction mechanism which revealed a change of Mott variable range to the small polaronic hopping conduction mechanism around 303 K. The complex impedance and modulus spectra undoubtedly showed the contribution of both grain and grain boundary effect on the conduction properties of LCMFO. An equivalent circuit [(R_gbQ_gb) (R_gQ_g)] model has been used to address the electrical parameters associated with the different phases (grains and grain boundaries) having different relaxation times. The values of resistances of two phases obtained after fitting the equivalent circuit in the nyquist plot have been analyzed which confirmed the change of conduction mechanism around 303 K. The resultant change in conduction mechanism is also supported by the conductivity plots.     

Catalytic hydrogenation of CO2 from 600 MW supercritical coal power plant to produce methanol: A techno-economic analysis

Electricity and water from renewable hydropower plant are used as input for electrolysis unit to generate hydrogen, while CO₂ is captured from 600 MW supercritical coal power plant using post-combustion chemical solvent based technology. The captured CO₂ and H₂ generated through electrolysis are used to synthesize methanol through catalytic thermo-chemical reaction. The methanol synthesis plant is designed, modeled and simulated using commercial software Aspen Plus^®. The reactor is analyzed for two widely adopted kinetic models known as Graaf model and Vanden-Bossche (VB) model to predict the methanol yield and CO₂ conversion. The results show that the methanol reactor based on Graaf kinetic model produced 0.66 tonne of methanol per tonne of CO₂ utilized which is higher than that of the VB kinetic model where 0.6 tonne of methanol is produced per tonne of CO₂ utilized. The economic analysis reveals that 1.2 billion USD annually is required at the present cost of both H₂ production and CO₂ abatement to utilize continuous emission of 3.2 million tonne of CO₂ annually from 600 MW supercritical coal power unit to synthesize methanol. However, sensitivity analysis indicates that methanol production becomes feasible by adopting anyone of the route such as by increasing methanol production rate, by reducing levelised cost of hydrogen production, by reducing CO₂ mitigation cost or by increasing the current market selling price of methanol and oxygen.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.     

Numerical Study of NOx Abatement Using Ozone Injection Integrated with Wet Absorption

Nitrogen oxides emitted from power plants and the chemical industry are poisonous to humans and animals, contribute to ozone depletion, and cause acid rain. More than 90% of nitrogen oxides (NO_x) consist of nitric oxide (NO), which is insoluble in water. Among the various available techniques of NO_x abatement, ozone injection is a promising method in which NO is oxidized to higher-order nitrogen oxides (NO₃, N₂O₃, N₂O₄, and N₂O₅), which can easily be absorbed in a wet scrubber. In this article, the ozone injection process integrated with an absorber column is numerically modeled and simulated at various operating conditions. The predicted results of NO_x oxidation with ozone injection and absorption in water agree with the published experimental results. The ozone injection process is modeled using a plug flow reactor, while the wet absorption is based on a rigorous rate-based RateFrac model. Detailed kinetic mechanisms of O₃-NO_x oxidation and absorption of nitrogen oxides in water are incorporated in the model to simultaneously predict the performance efficiency of the ozone reactor and absorber column. Thermodynamic properties of the components are estimated using an Electrolyte NRTL model. The influence of performance parameters (such as feed gas flow rate, inlet gas temperature, reactor configurations, ozone concentration, and NO/NO₂ molar ratio) on the oxidation efficiency of NO_x in the reactor and absorber column is investigated to predict the optimal operating conditions.     

Structural and magnetic properties of Pr–Ni substituted Ca0.5Ba0.5Fe12O19 hexa-ferrite nanoparticles

Effect of Pr–Ni substitution on structural and magnetic properties of Ca_0.5Ba_0.5−xPr_xNi_yFe_12−yO₁₉ (x=0.00–0.10 and y=0.00–1.00) prepared by the sol–gel auto combustion method were investigated. The XRD analysis confirmed the single phase M-type hexa-ferrite structure. The lattice parameters were found to increase as Pr–Ni content increases, which is attributed to the ionic size of the implicated cations. The Pr–Ni seems to be completely soluble in the lattice. Transmission electron microscopy reveals that the grain size decreases with increase of Pr–Ni substitution. The coercivity and remanent magnetization ranges from 1511 to 1925 (Oe) and 21.4 to 26.5 (emu/g), respectively. The coercivity values of all the samples fall in the range of M-type hexa-ferrites.     

平纹机织玄武岩纤维/环氧树脂复合材料冲击拉伸行为

以常规机织工艺生产织物增强体,以真空辅助树脂转移模塑法(VARTM)制备成型复合材料,研究单层平纹玄武岩长丝增强环氧树脂复合材料在准静态和高应变率加载下的拉伸性能。准静态和高应变率拉伸试验分别在MTS-810.23试验仪和分离式霍普金森拉杆(SHTB)测试系统上完成。试验结果表明该材料的力学性能具有应变率依赖性:随着应变速率的增加,拉伸模量和拉伸强度单调增加,失效应变单调减小,弹性能先增加后减小。材料的失效破坏特征也呈现明显的应变率效应:准静态拉伸时,材料断口整齐,树脂的破碎少,几乎没有纤维的抽拔和经纬向纤维束间的滑移;高应变率拉伸时,材料断口参差错乱,树脂完全破碎,纤维束抽拔严重、相互崩裂和滑移,织物增强体结构的整体性破坏严重。