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In order to realize the waste heat recovery of the high-temperature semi-cokes, the heat exchanger with one time heat transfer was put forward and the fractal heat conduction model was established for the first time. The internal structure of semi-cokes with different diameters in the heat exchanger was analyzed, and the internal structure was taken into account in the fractal heat conduction model. Furthermore, the fractal heat conduction model is demonstrated through the experiment, and it is compared with the traditional volume average model. The results showed that, the internal structure of semi-cokes in the heat exchanger determines the fractal heat conduction characteristics, and the influence of porosity on the equivalent thermal conductivity calculated by the fractal heat conduction model is less than the fractal dimension and the contact resistance number. The equivalent thermal conductivity calculated by the fractal heat conduction model is closer to experimental values than that calculated by the traditional volume average model, and the error of the equivalent thermal conductivity between the experimental values and the fractal heat conduction model is less than 6%, thus the fractal heat conduction model is valid and feasible. • A new waste heat recovery system of semi-coke was put forward. • The internal structure of semi-coke bed was obtained and analyzed. • The fractal heat conduction model was established for the first time. • The fractal heat conduction model is superior to traditional volume average model. [ABSTRACT FROM AUTHOR]

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a "measurable, evaluable, and optimized" low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Laser surface quenching (LSQ) is gaining popularity in engineering applications, but it generates non-negligible carbon emissions. However, existing research mostly focuses on quenching performance. Little attention has been paid to carbon emissions of LSQ process. In this study, we build an experimental platform including fiber laser system (IPG YLR-4 kW) and carbon emission measurement system for a synergistic study of environmental impacts and processing quality in LSQ. Based on the L 16 (4 3 ) Taguchi matrix, LSQ experiments are conducted on the shield disc cutter. The influences of laser power, scanning speed, and defocusing distance on carbon emissions and hardening effects are studied. The carbon emission efficiency of LSQ is analyzed and compared with the competitive technology. The geometry and the maximum average hardness (MAH) of LSQ high-hardness zone (HHZ) are studied. A comprehensive evaluation considering carbon emissions and hardening effects is conducted. The results show that the maximum value of carbon emission is 1.4 times the minimum value. The maximum depth and width of HHZ are respectively 0.507 and 3.254 mm. The maximum MAH is 3.5 times the hardness of base metal. Compared to the average experimental responses, the experiment with the highest comprehensive score respectively increases by 26.4%, 17.1%, and 30.3% in depth, width, and MAH of HHZ, and reduces by 5.8% in carbon emissions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With the development of the industrial economy and the accelerated renewal of products, many end-of-life products (EOL) have been generated to pollute our environment. This fact highlights the importance of recycling and remanufacturing EOL products as an active research topic. An efficient disassembly line is one solution for improving the remanufacturing and recycling processes of EOL products while reducing the environmental pollution. Although many optimization models and intelligent algorithms were developed to address the disassembly line balancing problem (DLBP), uncertainty was ignored by them. To alleviate the drawbacks of uncertainty for the disassembly operation, this study proposes a stochastic multi-objective optimization model for the DLBP minimizing the disassembly idle rate, smoothness, and energy consumption generated during the operation under uncertain operation time. Another novelty of this paper is to present an improved version of the northern goshawk optimization algorithm using a stochastic simulation method to solve the proposed model. The feasibility of the proposed model and the applicability of the developed algorithm are shown by two extensive examples. Finally, the performance of the proposed algorithm is revealed by a comparison with recent and state-of-the-art algorithms from the literature., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Due to environmental pollution and resource shortages, the electric vehicle industry has been developing swiftly, and the market demand for batteries, as an essential part of electric vehicles, has also surged. Proper disassembly of end-of-life vehicle batteries (ELV batteries) is necessary to achieve the integrity and closure of their life cycle, promote the development of green remanufacturing, effectively reduce the pollution of the environment caused by metal ion leakage, and reduce people's dependence on natural resources to a certain extent. To schedule the disassembly operations of ELV batteries more rationally and further promote their disassembly quality and efficiency, this paper proposes a dual-objective disassembly sequence planning (DSP) optimisation model, which aims to minimise the hazard index and energy cost during ELV battery disassembly operations. Since the proposed model is a complex NP-hard optimisation problem, this study develops an efficient metaheuristic algorithm for solving this model based on the northern goshawk optimisation algorithm. The main algorithm adds two types of discrete recombination operators and a local search operator. At the same time, the predatory behaviour of the goshawk is optimised by combining the characteristics of the disassembly sequence planning problem to improve its performance. Finally, the disassembly of the battery of a Tesla Model 1 is used as a case study to demonstrate the effectiveness and feasibility of the proposed method., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Both vasovagal syncope (VVS) and epilepsy present with transient loss of consciousness and are often difficult to identify. Hence this study aimed to explore the value of QT interval in the differentiation of VVS and epilepsy in children., Methods: One hundred thirteen children with unexplained transient loss of consciousness were selected. 56 children with VVS (VVS group), including 37 males and 19 females, the average age is 9.88 ± 2.55 years old. 57 children with epilepsy (epilepsy group), including 36 males and 21 females, the average age is 8.96 ± 2.67 years old. At the same time, the 60 healthy individuals (control group) were examined according to age and sex. The QT interval of 12-lead electrocardiogram in a basal state of three groups was measured and statistically analyzed by SPSS 24.0 software., Results: Compared with the control group, (1) QTcmax, QTcmin and QTcd were significantly longer in VVS group (P < 0.05), QTmax and QTmin were significantly shorter in VVS group (P < 0.05), and there were no significant differences in QTd between the two groups (P > 0.05). (2) The QTmax and QTmin were significantly shorter in epilepsy group (P < 0.05), and there were no significant differences in QTd, QTcmax, QTcmin, QTcd between the two groups (P > 0.05). Compared with the epilepsy group, The QTcmax, QTcmin, QTcd were significantly longer in VVS group (P < 0.05), and there were no significant differences in QTd, QTmax, QTmin between the two groups (P > 0.05). When QTcmax > 479.84 ms, QTcmin > 398.90 ms and QTcd > 53.56 ms, the sensitivity and specificity of diagnosing VVS were 62.5% and 77.19%, 82.14% and 50.88%, 82.14% and 38.60% respectively., Conclusion: QTcmax, QTcmin and QTcd have certain value in differentiating VVS from epilepsy in children., (© 2022. The Author(s).)

Global environmental governance is the fundamental way to solve the human environmental crisis. With China as the world's largest emitter of greenhouse gases, the development of China's environmental law is a key component of global environmental governance. In order to better realize the construction of an ecological civilization, the compilation of China's Environmental Code has been officially put on the work schedule of the legislature. The compilation of the code is a sincere action, showing that China has taken the initiative to assume its own responsibility for environmental governance. In the past 50 years, China's environmental legislation has achieved a great leap forward: from nothing to something, from something to something more comprehensive. Aside from this progress, defects such as the internal imbalance of the environmental law system, the backwardness of some environmental legislation ideas, and the inability of environmental legislation and its academic research to fully match China's national conditions also exist. With the helping hands of conditions and times, it is most appropriate for China to start the compilation of the Environmental Code now. Environmental Codes such as the Swedish Environmental Code, the French Environmental Code and the German Environmental Code (Draft of the Committee of Experts) provide many empirical references for the compilation of China's Environmental Code. China will make important an contribution to world environmental governance again-an Environmental Code in line with international standards while maintaining native characteristics.

This work proposes a capacitated fuzzy disassembly scheduling model with cycle time and environmental cost as parameters, which has broad applications in remanufacturing and many other production systems. Disassembly scheduling is not always given accurately as a time quota in a production system, particularly in the obsolete product remanufacturing process. It is important to study novel models and algorithms based on uncertainty processing time to solve uncertainty disassembly scheduling problems. In this paper, a mixed-integer mathematical programming model is proposed to minimize the cycle time and environmental cost, whilst a metaheuristic approach based on a fruit fly optimization algorithm (FOA) is developed to find a fuzzy disassembly scheduling scheme. To estimate the effectiveness of the proposed method, the proposed algorithm is tested with different size cases of product disassembly scheduling. Furthermore, experiments are conducted to compare with other multi-objective optimization algorithms. The computational results demonstrate the proposed algorithm outperforms other algorithms on computational efficiency and applicability to different problems. Finally, a case study is described to illustrate the proposed method. The main contribution of this current work shows the proposed algorithm to solve the problem of disassembly scheduling in an uncertain environment practically and efficiently., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As one of the mainstream development directions of remanufacturing industry, remanufacturing system scheduling has become a hot research topic recently. This study regards a scheduling problem for remanufacturing systems where end-of-life (EOL) products are firstly disassembled into their constituent components, and next these components are reprocessed to like-new states. At last, the reprocessed components are reassembled into new remanufactured products. Among various system configurations, we investigate a scheduling problem for the one with parallel disassembly workstations, several parallel flow-shop-type reprocessing lines and parallel reassembly workstations for the objective of minimize total energy consumption. To address this problem, a mathematical model is established and an improved genetic algorithm (IMGA) is proposed to solve it due to the problem complexity. The proposed IMGA adopts a hybrid initialization method to improve the solution quality and diversity at the beginning. Crossover operation and mutation operation are specially designed subject to the characteristics of the optimization problem. Besides, an elite strategy is combined to gain a faster convergence speed. Numerical experiments are conducted and the results verify the effectiveness of the scheduling model and proposed algorithm. The work can assist production managers in better planning a scheduling scheme for remanufacturing systems., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

One of the major challenges of the supply chain managers is to select the best suppliers among all possible ones for their business. Although the research on the supplier selection with regards to green, sustainability or resiliency criteria has been contributed by many papers, simultaneous consideration of these criteria in a fuzzy environment is rarely studied. Hence, this study proposes a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem for a real case study of palm oil industry in Malaysia. Firstly, the resilient-based sustainable criteria are localized for the suppliers' performance evaluation in palm oil industry of Malaysia. Accordingly, 30 criteria in three different aspects (i.e. general, sustainable and resilient) are determined by statistical tests. Moreover, a hyper-hybrid model with the use of FDEMATEL (fuzzy decision-making trial and evaluation laboratory), FBWM (fuzzy best worst method), FANP (fuzzy analytical network process) and FIS (fuzzy inference system), simultaneously is developed to employ their merits in an efficient way. In this framework, regarding the outset, the relationships among the criteria/sub-criteria are obtained by FDEMATEL method. Then, initial weights of the criteria/sub-criteria are measured by FBWM method. Next, the final weights of criteria/sub-criteria considering the interrelationships are calculated by FANP. Finally, the performance of the suppliers is evaluated by FIS method. To show the applicability of this hybrid decision-making framework, an industrial case of palm oil in Malaysia is presented. The findings indicate the high performance of the proposed framework in this concept and identify the most important criteria including the cost in general aspects, resource consumption as the most crucial sustainable criterion and agility as the most important resilient criterion.

In this paper, folic acid-coated graphene oxide nanocomposite (FA-GO) is used as an adsorbent for the treatment of heavy metals including cadmium (Cd 2+ ) and copper (Cu 2+ ) ions. As such, graphene oxide (GO) is modified by folic acid (FA) to synthesize FA-GO nanocomposite and characterized by the atomic force microscopy (AFM), Fourier transform-infrared (FT-IR) spectrophotometry, scanning electron microscopy (SEM), and C/H/N elemental analyses. Also, computational intelligence tests are used to study the mechanism of the interaction of FA molecules with GO. Based on the results, FA molecules formed a strong π-π stacking, chemical, and hydrogen bond interactions with functional groups of GO. Main parameters including pH of the sample solution, amounts of adsorbent, and contact time are studied and optimized by the Response Surface Methodology Based on Central Composite Design (RSM-CCD). In this study, the equilibrium of adsorption is appraised by two (Langmuir and Freundlich and Temkin and D-R models) and three parameter (Sips, Toth, and Khan models) isotherms. Based on the two parameter evaluations, Langmuir and Freundlich models have high accuracy according to the R 2 coefficient (more than 0.9) in experimental curve fittings of each pollutant adsorption. But, multilayer adsorption of each contaminant onto the FA-GO adsorbent (Freundlich equation) is demonstrated by three parameter isotherm analysis. Also, isotherm calculations express maximum computational adsorption capacities of 103.1 and 116.3 mg g -1 for Cd 2+ and Cu 2+ ions, correspondingly. Kinetic models are scrutinized and the outcomes depict the adsorption of both Cd 2+ and Cu 2+ followed by the pseudo-second-order equation. Meanwhile, the results of the geometric model illustrate that the variation of adsorption and desorption rates do not have any interfering during the adsorption process. Finally, thermodynamic studies show that the adsorption of Cu 2+ and Cd 2+ onto the FA-GO nanocomposite is an endothermic and spontaneous process.