Experimental study of a portable plasma arc cutting system using hybrid RSM-nature inspired optimization technique

Mangaraj, Soumya Ranjan; Bagal, Dilip Kumar; Parhi, Nirmalya; Panda, Surya Narayan; Barua, Abhishek; Jeet, Siddharth

doi:10.1016/j.matpr.2021.06.138

Cited by 16 publications

(7 citation statements)

References 41 publications

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“…If the calculated p-value for each factor is less than 0.05, the factor is significant. On the other hand, if it is more than 0.05, changing that factor has no significant effect on the response 37 , 38 . Moreover, a lack-of-fit with a p -value > 0.05 indicates that the model error is not significant, and the residual is due to a random error.…”

Section: Resultsmentioning

confidence: 98%

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples

Qiu

Baharinikoo

et al. 2022

Sci Rep

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In this study, we investigated the process of preconcentrate and determine trace amounts of Auramine O (AO) and methylene blue (MB) dyes in environmental water samples. For this purpose, the ultrasound-assisted dispersive-magnetic nanocomposites-solid-phase microextraction (UA-DMNSPME) method was performed to extract AO and MB from aqueous samples by applying magnesium oxide nanoparticles (MgO-NPs). The proposed technique is low-cost, facile, fast, and compatible with many existing instrumental methods. Parameters affecting the extraction of AO and MB were optimized using response surface methodology (RSM). Short extraction time, low experimental tests, low consumption of organic solvent, low limits of detection (LOD), and high preconcentration factor (PF) was the advantages of method. The PF was 44.5, and LOD for AO and MB was 0.33 ng mL−1 and 1.66 ng mL−1, respectively. The linear range of this method for AO and MB were 1–1000 ng mL−1 and 5–2000 ng mL−1, respectively. In addition, the relative standard deviation (RSD; n = 5) of the mentioned analytes was between 2.9% and 3.1%. The adsorption–desorption studies showed that the efficiency of adsorbent extraction had not declined significantly up to 6 recycling runs, and the adsorbent could be used several times. The interference studies revealed that the presence of different ions did not interfere substantially with the extraction and determination of AO and MB. Therefore, UA-DMNSPME-UV/Vis method can be proposed as an efficient method for preconcentration and extraction of AO and MB from water and wastewater samples.

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Section: Resultsmentioning

confidence: 98%

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples

Qiu

Baharinikoo

et al. 2022

Sci Rep

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“…They were also assessed the effects of cutting speed, gas pressure and plasma current and reported that the sheet deformation highly in uenced by the cutting current and speed whereas the HAZ primarily affected by cutting speed [18]. Mangaraj et al [19] performed experimental study on PAC of stainless steel (AISI 304) and reported that square of plasma current, cutting speedand the interaction between cutting speed and plasma current are the most in uential PAC process ing parameters. Abouzaid and Mousa [20] applied PAC for machining of copper and revealed that no change in its hardness and microstructure post PAC.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study on Oxygen Assisted Plasma Air Cutting of Low Carbon Steel

Petare,

Khan,

Madhukar

2024

Preprint

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Air plasma cutting technology is widely used for cutting complex profiles, geometrics, shapes, and sections in electrically conducting materials at high speed. In this experimental research, oxygen was introduced along with compressed air during plasma air cutting of 10 mm thick C-20 carbon steel plates and their effect on cut surface quality was studied. A total of twenty experiments with compressed air were performed using a full-factorial design of experiments to identify the optimum ranges of process parameters. Further, based on the obtained results from preliminary experiments, twenty experiments were designed using a central composite design (CCD) approach of response surface method (RSM) using compressed air and a mixture of compressed air and oxygen. The cut surface quality was analysed for both conditions in terms of kerf width, dross height, bevel angle, surface roughness, maximum cutting temperature and heat-affected zone (HAZ). A comparative study between compressed air plasma cutting and oxygen assisted compressed air plasma cutting reveals that the addition of oxygen with compressed air improves the arc quality of plasma, which consequently reduced cutting time, kerf width, dross height, and surface roughness of the work materials. The microstructure study of both the cut surfaces reveals that the addition of oxygen with compressed air reduced the length of HAZ significantly compared to compressed air plasma cutting. The outcome of this study would be beneficial for the researcher and engineers working in the area of plasma-assisted cutting of metals.

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“…Architects and designers are constantly aware of how reality is changing, thus they actively look for new approaches to challenge established ideas. The incorporation of cutting-edge optimization algorithms, which are inspired by the natural intelligence of the world, emphasizes this quest [16][17][18]. This combination has enormous disruptive potential and might lead to a new direction in architectural design.…”

Section: Introductionmentioning

confidence: 99%

Exploration of Natural Element Form Optimization Algorithm using Spatial-Temporal Multi-Scale Alignment Graph Neural Network in Architectural Design Based on Morphological Theory

Chen Liu

2024

jes

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The construction industry has experienced important changes in recent years due to advancements in digital, artificial intelligence, and construction technologies, as well as the sector's on-going development and the advancement of science and technology. The creative growth of building industry, creative creation of architectural forms are partially supported technically by sophisticated parametric design apparatuses, the potent computing benefits of computer technology. In this manuscript, Exploration of Natural Element Form Optimization Algorithm using Spatial-Temporal Multi-Scale Alignment Graph Neural Network in Architectural Design Based on Morphological Theory (ENEF-OA-ADMT) is proposed. The STMSA-GNN and the Chaotic Coyote Algorithm (CCA) are two tools used by the proposed ENEF-OA-ADMT approach to improve architectural design based on morphological theory. The ST-MSA GNN's ability to capture intricate interactions and dependencies between several components in both space and time allows it to perform a comprehensive study of the morphological aspects of architectural designs. This graph neural network's integration of spatial and temporal dimensions enables a deeper understanding of how the architectural structural form design changes over time. The CCA optimized the ST-MSA-GNN to enhance the architectural structural form design. The proposed ENEF-OA-ADMT methodology skill fully combines these methodologies, creating a strong framework that allows architects and designers to work together to explore, refine, and create architectural structural design forms. The framework provided serves as a spur for further research, encouraging a more complete integration of technology and environment in the architectural domain. The effectiveness of proposed method is executed in python, evaluated through performance metrics encompassing accuracy, precision, specificity, Recall, computational time, F1 score, population diversification, randomness. Proposed ENEF-OA-ADMT method 34.56%, 28.63% and 21.89% higher accuracy, 34.97%, 32.13% and 21.89% higher precision and 34.68%, 20.84% and 29.76% higher randomness when compared with the existing methods such as Study of Morphological Design of Architecture from Geometric Logic Perspective (SOT-MDA-GLP), learning deep morphological networks by neural architecture search (LD-MN-NAS) and identifying degrees of deprivation from space utilizing deep learning with morphological spatial analysis of deprived urban areas (IDDS-DLMSA-DUA) respectively.

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Experimental study of a portable plasma arc cutting system using hybrid RSM-nature inspired optimization technique

Cited by 16 publications

References 41 publications

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples

An Experimental Study on Oxygen Assisted Plasma Air Cutting of Low Carbon Steel

Exploration of Natural Element Form Optimization Algorithm using Spatial-Temporal Multi-Scale Alignment Graph Neural Network in Architectural Design Based on Morphological Theory

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