Unsteady hybrid-nanofluid flow comprising ferrousoxide and CNTs through porous horizontal channel with dilating/squeezing walls

The key objective of the present research is to examine the hybrid magnetohydrodynamics (MHD) nanofluid (Carbon-nanotubes and ferrous oxide–water) CNT–Fe3O4/H2 flow into a horizontal parallel channel with thermal radiation through squeezing and dilating porous walls. The parting motion is triggered by the porous walls of the channel. The fluid flow is time-dependent and laminar. The channel is asymmetric and the upper and lower walls are distinct in temperature and are porous. With the combination of nanoparticles of Fe3O4 and single and multi-wall carbon nanotubes, the hybrid nanofluid principle is exploited. By using the similarity transformation, the set of partial differential equations (PDEs) of this mathematical model, governed by momentum and energy equations, is reduced to corresponding ordinary differential equations (ODEs). A very simple numerical approach called the Runge–Kutta system of order four along with the shooting technique is used to achieve the solutions for regulating ODEs. MATLAB computing software is used to create temperature and velocity profile graphs for various emerging parameters. At the end of the manuscript, the main conclusions are summarized. Through different graphs, it is observed that hybrid-nanofluid has more prominent thermal enhancement than simple nanofluid. Further, the single-wall nanotubes have dominated impact on temperature than the multi-wall carbon nanotubes. From the calculations, it is also noted that Fe2O3–MWCNT–water has an average of 4.84% more rate of heat transfer than the Fe2O3–SWCNT–water. On the other hand, 8.27% more heat flow observed in Fe2O3–SWCNT–water than the simple nanofluid. Such study is very important in coolant circulation, inter-body fluid transportation, aerospace engineering, and industrial cleaning procedures, etc.

Green synthesis and anticorrosion effect of Allium cepa peels extract-silver nanoparticles composite in simulated oilfield pickling solution

An alternative green approach through which nanoscience/nanotechnology could be applied in the industry is being demonstrated in this study. Ethanol extracts of Allium cepa peels (Et-ACPE) is used to mediate the synthesis of silver nanoparticles (Et-AgNPs) at room temperature. Stable crystalline, monodisperse and non-agglomerated spherical NPs with zeta potential of −46.2 ± 0.1 mV and plasmon absorption at 435 nm are obtained. Silver atoms are predominantly oriented towards the Ag (111) plane in a face centered cubic structure with a = b = c = 4.0968 Å having $$\alpha = \beta = \gamma = 90^\circ$$ α = β = γ = 90 ∘ . The surfaces of the NPs becomes rich in electron cloud due to O atoms supplied by capped phyto-compounds of Et-ACPE. This enhances adsorption potential and more efficient inhibition (up to 90% at 30 °C) of X80 steel corrosion in 1 M HCl solution than using the crude extract. Investigation of corrosion products and morphologies of the steel surface by FTIR, SEM/EDS and AFM techniques reveals efficient surface protection through adsorption of Et-AgNPs facilitated mainly by O and –C = C– sites. Findings prove that the Et-AgNPs is a more efficient and thermally stable alternative ecofriendly anticorrosion additive for industrial cleaning and pickling operations than the crude extract.

Mycoremediation of Soils Polluted with Trichloroethylene: First Evidence of Pleurotus Genus Effectiveness

Trichloroethylene (TCE) is a proven carcinogenic chlorinated organic compound widely used as a solvent in industrial cleaning solutions; it is easily found in the soil, air, and water and is a hazardous environmental pollutant. Most studies have attempted to remove TCE from air and water using different anaerobic bacteria species. In addition, a few have used white-rot fungi, although there are hardly any in soil. The objective of the present work is to assess TCE removal efficiency using two species of the genus Pleurotus that have not been tested before: Pleurotus ostreatus and Pleurotus eryngii, growing on a sandy loam soil. These fungi presented different intra- and extracellular enzymatic systems (chytochrome P450 (CYP450), laccase, Mn peroxidase (MnP)) capable of aerobically degrading TCE to less harmful compounds. The potential toxicity of TCE to P. ostreatus and P. eryngii was firstly tested in a TCE-spiked liquid broth (70 mg L−1 and 140 mg L−1) for 14 days. Then, both fungi were assessed for their ability to degrade the pollutant in sandy loam soil spiked with 140 mg kg−1 of TCE. P. ostreatus and P. eryngii improved the natural dissipation of TCE from soil by 44%. Extracellular enzymes were poorly expressed, but mainly in the presence of the contaminant, in accordance with the hypothesis of the involvement of CYP450.

System Modelling and Analysis to Support Economic Assessment of Product-Service Systems

The evolution towards more customer-centric operations within manufacturing and service industries gave rise to novel ways of value creation and delivery such as Product–Service Systems (PSS). PSS integrate tangible and intangible elements to create new values for both customers and providers. Therefore, a close collaboration is required among various actors in a value network to co-create values towards win–win gains. For companies to keep up with this pace, new decision support tools are needed to accompany PSS engineering and to adjust business models. This need is confronted with the scarcity of PSS-oriented economic assessment models and methods. This paper presents a comprehensive framework for the economic assessment of PSS. The framework relies on a novel combination of system modelling and analysis approaches to enable cost and revenue attribution to different actors in a value network. The applicability and relevance of the framework are demonstrated through a case study in the industrial cleaning sector.

Intelligent Industrial Cleaning: A Multi-Sensor Approach Utilising Machine Learning-Based Regression

Effectively cleaning equipment is essential for the safe production of food but requires a significant amount of time and resources such as water, energy, and chemicals. To optimize the cleaning of food production equipment, there is the need for innovative technologies to monitor the removal of fouling from equipment surfaces. In this work, optical and ultrasonic sensors are used to monitor the fouling removal of food materials with different physicochemical properties from a benchtop rig. Tailored signal and image processing procedures are developed to monitor the cleaning process, and a neural network regression model is developed to predict the amount of fouling remaining on the surface. The results show that the three dissimilar food fouling materials investigated were removed from the test section via different cleaning mechanisms, and the neural network models were able to predict the area and volume of fouling present during cleaning with accuracies as high as 98% and 97%, respectively. This work demonstrates that sensors and machine learning methods can be effectively combined to monitor cleaning processes.

Migrant Labour and Workers' Struggles: The German Meatpacking Industry as Contested Terrain

This article summarises results of a project whose aim was to analyse the role of migration within the current recomposition of the working class in Germany. We focus on the example of the meat industry in the Oldenburger Münsterland, a region that is experiencing a strong economic boom based on the expansion and modernisation of industrial work. The exploitation of migrant labour, composed of “newcomers” to the industry with both European Union and refugee backgrounds, is a pivotal feature of that boom. Most research on migrant labour focuses on legal frameworks and labour market dynamics. By focusing instead on the labour process, we are able to examine the connections between exploitation, resistance and collective organisation among migrant workers. We show that the experience of migrant workers is not one of complete powerlessness and subjugation. We contrast workers in two sub-sectors, slaughtering and packing on the one hand and industrial cleaning on the other. Although both of these activities are similarly low-wage and migrant-dominated, we find variation in the ability of these workers to exercise power. The importance of skill and the need to avoid turnover gives workers in slaughtering and packing some levers of power, despite their vulnerable immigration status. This power has even instigated a shift towards some formalisation of these jobs on the part of management. In contrast, the different labour process has prevented industrial cleaning workers from accessing the same levels of power, despite sharing a similar labour market position to their co-workers in slaughtering and packing. KEY WORDS: Migration; refugees; labor unrest; trade unions; subcontracting; meat industry

Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments : Moving towards sustainable process manufacturing

Circular economy (CE) thinking has emerged as a route to sustainable manufacture, with related cradle-to-cradle implications requiring implementation from the design stage. The challenge lies in moving manufacturing environments away from the traditional linear economy paradigm, where materials, energy and water have often been designed to move out of the system and into receivership of waste management bodies after use. Recent applications of industrial digital technologies (IDTs: for example internet of things, data-driven modelling, cyber-physical systems, cloud manufacturing, cognitive computing) to manufacturing may be instrumental in transforming manufacturing from linear to circular. However, although IDTs and CE have been the focus of intensive research, there is currently limited research exploring the relationship between IDTs and the CE and how the former may drive the implementation of CE. This article aims to close the knowledge gap by exploring how an IDT (data-driven modelling) may facilitate and advance CE principles within process manufacturing systems, specifically waste valorisation and process resilience. These applications are then demonstrated through two real-world manufacturing case studies: (a) minimising resource consumption of industrial cleaning processes and (b) transforming wastewater treatment plants (WWTPs) into manufacturing centres.