Results in engineering
About: Results in engineering is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Materials science & Computer science. It has an ISSN identifier of 2590-1230. It is also open access. Over the lifetime, 905 publications have been published receiving 2835 citations.
TL;DR: In this paper , a review of methylene blue dye wastewater decontamination methods is presented, and the state-of-the-art review comprehensively discussed each of these techniques while gaps and/or areas for future research are highlighted.
Abstract: One of the popular cationic dyes that is environmentally persistent, toxic, carcinogenic and mutagenic is methylene blue (MB) dye. It is commonly applied as synthetic dye for dyeing fabrics in clothing and textile industries and also for dyeing papers and leathers. Sequel to the magnitude of industrial usage, a large volume of methylene blue dye containing wastewater is discharged into groundwater and surface water. At doses more than 5 mk/kg, the monoamine oxidate inhibitory characteristics of MB dye can induce fatal serotonin toxicity in human, apart from being a threat to fauna in aquatic ecosystem. Thus, it is highly imperative to eliminate MB dye from wastewaters. A number of different removal strategies have been reported in literature for treating methylene blue dye wastewater. In this state-of-the-art review, about 240 review and/or research published articles on methods for methylene blue dye wastewater decontamination or decontamination strategies were chosen for evaluation. This synthesis also discussed the various toxicities linked to MB dye. The assessment of elimination methods revealed that chemical removal methods (photochemical and non-photochemical) could generate secondary pollutants while biological methods are characterized with sensitivity of enzyme to pH. These drawbacks limit their industrial full-scale applications while adsorption technology was found to offer merits over others. The review comprehensively discussed each of these techniques while gaps and/or areas for future research are highlighted.
TL;DR: In this article , a comparative study of nanofluid and pure fluid (water) is investigated over a moving upright plate surrounded by a porous surface, which includes the unsteady laminar MHD natural transmission flow of an incompressible fluid.
Abstract: A comparative study of nanofluid (Cu–H2O) and pure fluid (water) is investigated over a moving upright plate surrounded by a porous surface. The novelty of the study includes the unsteady laminar MHD natural transmission flow of an incompressible fluid, to get thermal conductivity of nanofluid is more than pure fluid. The chemical reaction of this nanofluid with respect to radiation absorption is observed by considering the nanoparticles to attain thermal equilibrium. The present work is validated with the previously published work. The upright plate travels with a constant velocity u0, and the temperature and concentration are considered to be period harmonically independent with a constant mean at the plate. The most excellent appropriate solution to the oscillatory pattern of boundary layer equations for the governing flow is computed utilizing the Perturbation Technique. The impacts of factors on velocity, temperature, and concentration are visually depicted and thoroughly elucidated. The fluid features in the boundary layer regime are explored visually and qualitatively. This enhancement is notably significant for copper nanoparticles.
TL;DR: In this paper , the authors proposed a system to forecast solar radiation using Neural Networks, which can forecast radiation values for any day using different meteorological data from the previous day using Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU).
Abstract: Solar radiation is the energy or radiation we get from the sun, time-varying data. Solar radiation plays a vital role in various sectors. With better prediction, performances in these sectors can be enhanced. In this work, we proposed a system to forecast solar radiation using Neural Networks. Meteorological data from five different cities of Bangladesh were used. The system can forecast radiation values for any day using different meteorological data from the previous day. Three different networks were trained using the meteorological data, which are the Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). Also, predictions were made for all five cities separately. An elaborate evaluation of all three models has been done to produce a comparison using widely used performance metrics. The GRU model produced the best result among all three models, with a MAPE score of 19.28%.
TL;DR: In this article , a bibliographic review of the current state-of-the-art of the biomass gasification is carried out, focusing in the gasification technologies, syngas cleaning processes, simulation methodologies on process parameters.
Abstract: The search for alternatives to fossil energy traditional sources led to the development of a set of energy conversion processes, which include biomass thermochemical conversion technologies, such as torrefaction, pyrolysis, hydrothermal liquefaction, or gasification. These conversion technologies have shown significant evolutions, and there are already several examples available of application on an industrial scale. Biomass gasification processes have also presented significant developments, mainly when associated with the production of syngas with potential for energy recovery or to produce synthetic fuels, but mainly due to its potential to be used as a sustainable hydrogen production technology. In the present work, a bibliographic review of the current state-of-the-art of the biomass gasification is carried out, focusing in the gasification technologies, syngas cleaning processes, simulation methodologies on process parameters. Finally, future developments and possibilities are also analyzed and discussed, with the introduction of a new approach to hydrogen production based on the use of an adapted combustion process with air deficit.
TL;DR: In this paper , a detailed review of wire arc additive manufacturing (WAAM) hardware systems, physical process, monitoring, property characterization, application and future prospects is presented to facilitate quick and easy understanding of current status and future prospect of WAAM.
Abstract: Wire arc additive manufacturing (WAAM) outstandingly features in lower cost and higher efficiency than other metal additive manufacturing technologies, which has a great potential in large-scale industrial production. The paper gives a detailed review, which involves WAAM hardware system, physical process, monitoring, property characterization, application and future prospects, to facilitate quick and easy understanding of current status and future prospects of WAAM. WAAM hardware systems are of primary importance and mainly based on four types of arc welding machine. The paper summarized the features of different hardware systems, displayed their suitability for different raw materials, and discussed their respective advantages. There is complex physical phenomenon in WAAM, and many technological parameters, such as heat input, current, wire feeding speed and so on, are investigated to understand the physical mechanism. Monitoring is essential for the additive process, in which optical inspection, spectral sensing, acoustic sensing, thermal sensing, electrical sensing and multi-sensor monitoring system all have been applied. Property characterization is always done to evaluate the quality of additive parts, and typical defects such as high residual stress, deformation, porosity, crack and delamination are reported. Examples of industrial products fabricated by WAAM are introduced. Finally, the paper concluded six possible research directions in future. It is necessary to establish detailed databases about additive parts for sorted hardware systems and metals with suitable operating conditions. Hybrid additive and subtractive technology, additional rolling or temperature control process, multi-scale and multi-physics research, multi-variable monitoring system, and artificial intelligence would help to improve the manufacturing level.