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Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products
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Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 28865

Special Issue Editor

Prof. Dr. Jiaqiang E

grade E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Interests: green manufacturing; sustainable management and technology; field synergy analysis; biodiesel combustion in diesel engine; after-treatment system of automotive systems; multidisciplinary design optimization; intelligent information fusion; active control and signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There are many waste emissions in the process of manufacturing and trade for mechanical and electrical products. It is well known that minimum waste emissions are wanted for normal operation of the process of manufacturing and trade for mechanical and electrical products. Many waste emissions will reduce the efficiency of the process of manufacturing and trade for mechanical and electrical products. Green manufacturing and low-carbon trade are very important to energy and to environmental and sustainable ecological development. However, green manufacturing and low-carbon trade of mechanical and electrical products are still a serious challenge to academic researchers and industrial engineers. This Special Issue is dedicated to the most recent advances in research on green manufacturing and the low-carbon trade of mechanical and electrical products. We invite scientists and investigators to contribute original research and review articles which address the topics of the Special Issue. Potential topics include but are not limited to:

  • Green manufacturing assessment based on life-cycle theory;
  • Strategy of green manufacturing based on life-cycle theory;
  • Green manufacturing operation model and its implementation methods;
  • Green manufacturing model based on synergetic implementation of benefits;
  • Green purchase, green manufacture, green marketing, and reverse logistics;
  • Pre-warning mechanism of green trade barrier;
  • Countermeasure analysis of the green trade barrier;
  • Theory of green trade-on relationship between trade and environment;
  • Carbon footprint evolution and/or reducing carbon emissions and/or low-carbon economy;
  • Development and management of the trade for mechanical and electrical products;
  • Complex systems modeling and simulation of the trade for mechanical and electrical products.

Dr. Jiaqiang E
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • green manufacturing assessment
  • green manufacturing model
  • low-carbon trade
  • mechanical and electrical product
  • carbon footprint
  • life-cycle theory

Published Papers (17 papers)

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Research

16 pages, 2758 KiB  
Article
Study on Flow and Heat Transfer in Single Rock Fractures for Geothermal Heat Extraction
by Duanru Li, Gang Liu and Shengming Liao
Processes 2024, 12(2), 363; https://doi.org/10.3390/pr12020363 - 9 Feb 2024
Viewed by 566
Abstract
A full understanding of the fluid flow and heat transfer behaviors within a single fracture is important for geothermal heat extraction. In this study, models of single fractures with varying aperture and inner surface roughness (characterized by fractal dimension) are constructed, and a [...] Read more.
A full understanding of the fluid flow and heat transfer behaviors within a single fracture is important for geothermal heat extraction. In this study, models of single fractures with varying aperture and inner surface roughness (characterized by fractal dimension) are constructed, and a compound fracture aperture (CFA) is proposed to describe the coupled effect of fracture aperture and inner surface roughness. The effect of the fluid flow Reynolds number on heat transfer was investigated as it ranged from 4.84 to 145.63. The results show that the overall heat transfer coefficient (OHTC) in a single fracture significantly increases with the rise in fluid velocity and the compound fracture aperture. Particularly, the OHTC in a single fracture with an inner surface fractal dimension of 2.09 can be up to 1.215 times that of a parallel flat fracture when the flow velocity reaches 0.18 m/s. Moreover, for a fracture with a smaller CFA, enhancing the fracture aperture plays a decisive role in increasing the OHTC. Aperture emerges as a more sensitive optimization parameter for efficient heat extraction compared to the flow velocity. Meanwhile, based on simulation results, a convective heat transfer correlation equation is derived to provide more accurate estimates of the OHTC in rock fractures with different geometries and morphological features. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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27 pages, 8741 KiB  
Article
A Time–Frequency Residual Convolution Neural Network for the Fault Diagnosis of Rolling Bearings
by Chenxi Wu, Rong Jiang, Xin Wu, Chao Zhong and Caixia Huang
Processes 2024, 12(1), 54; https://doi.org/10.3390/pr12010054 - 25 Dec 2023
Cited by 1 | Viewed by 650
Abstract
A time–frequency residual convolution neural network (TFRCNN) was proposed to identify various rolling bearing fault types more efficiently. Three novel points about TFRCNN are presented as follows: First, by constructing a double-branch convolution network in the time domain and the frequency domain, the [...] Read more.
A time–frequency residual convolution neural network (TFRCNN) was proposed to identify various rolling bearing fault types more efficiently. Three novel points about TFRCNN are presented as follows: First, by constructing a double-branch convolution network in the time domain and the frequency domain, the respective features in the time domain and the frequency domain were extracted to ensure the rich and complete feature representation of raw data sources. Second, specific residual structures were designed to prevent learning degradation of the deep network, and global average pooling was adopted to improve the network’s sparsity. Third, TFRCNN was better than the other models in terms of prediction accuracy, robustness, generalization ability, and convergence. The experimental results demonstrate that the prediction accuracy rate of TFRCNN, trained using mixing load data, reached 98.88 to 99.92% after optimizing the initial learning rate and choosing the optimizer and loss function. It was verified that TFRCNN can adaptively learn to extract deep fault features, accurately identify bearing fault conditions, and overcome the limitations of classical shallow feature extraction and classification methods, as well as common convolution neural networks. Hence, this investigation revealed TFRCNN’s potential for bearing fault diagnosis in practical engineering applications. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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17 pages, 11249 KiB  
Article
Research on a New Method of Track Turnout Identification Based on Improved Yolov5s
by Renxing Chen, Jintao Lv, Haotian Tian, Zhensen Li, Xuan Liu and Yongjun Xie
Processes 2023, 11(7), 2123; https://doi.org/10.3390/pr11072123 - 16 Jul 2023
Viewed by 1097
Abstract
The modern tram track automatic cleaning car is a crucial equipment in urban rail transportation systems, effectively removing trash, dust, and other debris from the slotted tracks of trams. However, due to the complex and variable structure of turnouts, the cleaning car often [...] Read more.
The modern tram track automatic cleaning car is a crucial equipment in urban rail transportation systems, effectively removing trash, dust, and other debris from the slotted tracks of trams. However, due to the complex and variable structure of turnouts, the cleaning car often requires assistance in accurately detecting their positions. Consequently, the cleaning car needs help in adequately cleaning or bypassing turnouts, which adversely affects cleaning effectiveness and track maintenance quality. This paper presents a novel method for tracking turnout identification called PBE-YOLO based on the improved yolov5s framework. The algorithm enhances yolov5s by optimizing the lightweight backbone network, improving feature fusion methods, and optimizing the regression loss function. The proposed method is trained using a dataset of track turnouts collected through field shots on modern tram lines. Comparative experiments are conducted to analyze the performance of the improved lightweight backbone network, as well as performance comparisons and ablation experiments for the new turnout identification method. Experimental results demonstrate that the proposed PBE-YOLO method achieves a 52.71% reduction in model parameters, a 4.60% increase in [email protected](%), and a 3.27% improvement in precision compared to traditional yolov5s. By improving the track turnout identification method, this paper enables the automatic cleaning car to identify turnouts’ positions accurately. This enhancement leads to several benefits, including increased automation levels, improved cleaning efficiency and quality, reduced reliance on manual intervention, and mitigation of collision risks between the cleaning car and turnouts. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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12 pages, 2946 KiB  
Article
Predicting Centrifugal Pumps’ Complete Characteristics Using Machine Learning
by Jiangping Yu, Emmanuel Akoto, Derek Kweku Degbedzui and Liren Hu
Processes 2023, 11(2), 524; https://doi.org/10.3390/pr11020524 - 9 Feb 2023
Cited by 1 | Viewed by 1948
Abstract
The complete characteristics of centrifugal pumps are crucial for the modeling of hydraulic transient phenomena occurring in pipe systems. However, due to the effort required to obtain these curves, pump manufacturers typically only provide basic information, particularly when the pump operates under normal [...] Read more.
The complete characteristics of centrifugal pumps are crucial for the modeling of hydraulic transient phenomena occurring in pipe systems. However, due to the effort required to obtain these curves, pump manufacturers typically only provide basic information, particularly when the pump operates under normal conditions. To acquire the full characteristic curves based on the manufacturer’s normal performance curve, a machine learning (ML) model is proposed to predict full, complete Suter curves using a pump’s specific speed with the known parts of the Suter curve. The training data for the model are sourced from the available Suter curves from laboratory experiments. Subsequently, the proposed ML model combines several types of regression models in an attempt to find the most accurate prediction in terms of the root mean square error (RMSE). The result proved highly efficient, as the experiments attained a maximum RMSE value of 0.032 across the three categories of centrifugal pumps based on their specific speeds, hence demonstrating the potential of machine learning in the study of pump characteristic curves. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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17 pages, 21448 KiB  
Article
Effects of Different Influencing Factors on Temperature Distributions and Cooling Performance of Turbocharger Bearing Casing
by Bo Liu, Bin Zhang and Shuwan Cui
Processes 2022, 10(10), 2121; https://doi.org/10.3390/pr10102121 - 18 Oct 2022
Viewed by 1359
Abstract
In order to study temperature distributions under different influencing factors and evaluate the cooling performance of the turbocharger bearing casing, water-cooling system experiments regarding the turbocharger bearing casing are carried out, and an improved fuzzy analytic hierarchy process (FAHP) evaluation method for evaluating [...] Read more.
In order to study temperature distributions under different influencing factors and evaluate the cooling performance of the turbocharger bearing casing, water-cooling system experiments regarding the turbocharger bearing casing are carried out, and an improved fuzzy analytic hierarchy process (FAHP) evaluation method for evaluating its design performance is proposed firstly. Then, the effects of various factors such as cooling-water inlet flow velocity, cooling-water inlet temperature, cooling-water pressure and exhaust temperature on the cooling performance of the bearing casing are investigated according to the experimental results. Finally, the design performance of the water-cooling system in the turbocharger bearing casing is evaluated based on the FAHP evaluation method. The results show that the turbocharger bearing casing temperature and the temperature drop rate show a decreasing trend with the increase of inlet cooling-water velocity, but that the temperature and temperature rise rate increase with the increase of the inlet temperature of cooling-water and exhaust temperature; the temperatures under the inlet velocities of 4 m/s, 5 m/s and 6 m/s are reduced by 4.1%, 5.9% and 6.7% compared with that under 3 m/s, respectively. In addition, the bearing casing temperatures firstly reduce then increase with the increase of cooling-water pressure, where the boiling heat transfer plays an important role; points 1, 2 and 3 have relatively higher temperatures than other points under all working conditions; the bearing casing temperature of six measuring points also increases under a cooling-water pressure between 0.1 MPa and 0.25 MPa. Moreover, the performance evaluation value based on the FAHP method for the turbocharger bearing casing is 87.7620, and the performance evaluation level is good, which indicates that the water-cooling system in the turbocharger bearing casing has desirable design performance. This work provides reference for the turbocharger’s design and its cooling performance enhancement. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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18 pages, 6885 KiB  
Article
Analytical Research on the Bearing Characteristics of Oil Film Supplied with Constant Oil Flow Hydrostatic Turntables under Fixed Eccentric Load Condition
by Shaoli Wang, Jie Lu, Yilin Zhang, Kehan Ge and Chao Zhong
Processes 2022, 10(10), 2017; https://doi.org/10.3390/pr10102017 - 6 Oct 2022
Cited by 2 | Viewed by 1375
Abstract
This study was initiated in view of the phenomenon that hydrostatic turntable rails are prone to scrape damage when the liquid hydrostatic turntable is running under fixed partial load. The existing bias-load hydrostatic turntable oil film bearing characteristics are mainly calculated by using [...] Read more.
This study was initiated in view of the phenomenon that hydrostatic turntable rails are prone to scrape damage when the liquid hydrostatic turntable is running under fixed partial load. The existing bias-load hydrostatic turntable oil film bearing characteristics are mainly calculated by using the calculus integration method and CFD fluid simulation method. The calculating formula obtained by the calculus integration method is complex and inefficient. The CFD fluid simulation calculation method requires 3D modeling and meshing of the oil film, which is a tedious and time-consuming process and may not yield convergent calculation results due to improper meshing methods or boundary condition settings. In order to solve the shortage of the above calculation methods, this paper simplifies and equates the uneven thickness of the oil film of each sealing edge of the oil pad of the bias-loaded hydrostatic rotary table to the equivalent uniform thickness of the oil film, and based on this idea, the analytical calculation formula of the oil film bearing capacity, bending moment and stiffness under constant bias-load conditions of the constant-flow liquid hydrostatic rotary table is derived. In this paper, Fluent software was used to numerically simulate the oil film under this working condition, and a hydrostatic turntable test bench was established to conduct an experimental study on the biased load hydrostatic turntable; the experimental data and simulation results were compared with the results obtained from this simplified method of calculating the oil film loading characteristics. The results show that the error of oil film bearing capacity is less than 6% and the error of overturning moment is less than 7%, which has verified the validity of the calculation method. The simplified analytical calculation method proposed in this paper is used to study the influence of tilt displacement rate, lubricant flow rate and turntable speed on the basic performance parameters of oil film, which provides a theoretical basis for the study of oil film load-bearing characteristics under constant bias-load conditions of the constant-flow liquid hydrostatic turntable. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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22 pages, 1851 KiB  
Article
Investigation on Safety Dynamic Evolution Mechanism of a Distributed Low Carbon Manufacturing System with Large Time Delay
by Bo Liu, Yudie Chen, Hongyan Zuo, Guohai Jia and Dingqing Zhong
Processes 2022, 10(9), 1707; https://doi.org/10.3390/pr10091707 - 27 Aug 2022
Viewed by 1076
Abstract
In order to reveal the inducing factors and safety dynamic evolution mechanism of frequent personal injury accidents under a low carbon manufacturing process, a nonlinear safety dynamic evolution model of a distributed low carbon manufacturing system with large time delay is established. The [...] Read more.
In order to reveal the inducing factors and safety dynamic evolution mechanism of frequent personal injury accidents under a low carbon manufacturing process, a nonlinear safety dynamic evolution model of a distributed low carbon manufacturing system with large time delay is established. The established model is then verified by simulation results from mathematical analysis and dynamic evolution. Moreover, qualitative analysis on nonlinear safety dynamic evolution and the trend of human–machine safety under a low carbon manufacturing process is investigated. Finally, an application case of the established model is studied. The key results are as follows: (1) There are four dynamic regions, namely the safety area I, the deterioration area II, the asymptotically stable safety area III, and the enhancement area IV of the safety ability in the interaction evolution model of carelessness and safety levels; (2) There are two singularities in the dynamic evolution model of the man–machine safety system with large time delay under a low carbon manufacturing process; (3) The equilibrium points of the human–machine safety system are El = (0, 0) and E2 = (0.5333, 0.2489), while changes in the carelessness level have a serious block effect on safety development with time; (4) For the radial tire casing process, the low carbon development trend of the technological process of radial tire casing is good, but low carbon structure and management have slightly lower low carbon levels. This work provides a theoretical basis for the safety evaluation and control of the distributed low carbon manufacturing human–machine safety system with large time delay. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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14 pages, 4074 KiB  
Article
Study of Torsional Vibration Bifurcation Characteristics of Direct-Drive Wind Turbine Shaft System
by Zhonghua Huang, Rongjie Wu, Jinhao Chen, Xin Xu and Ya Xie
Processes 2022, 10(9), 1700; https://doi.org/10.3390/pr10091700 - 26 Aug 2022
Cited by 1 | Viewed by 1173
Abstract
This paper set out to establish the dynamics model of shaft torsional vibration for direct-drive wind turbine with the phenomenon of unstable shaft system torsional vibration. The stability of the equilibrium point of the dynamical model is investigated, and the Routh–Hurwitz stability criterion [...] Read more.
This paper set out to establish the dynamics model of shaft torsional vibration for direct-drive wind turbine with the phenomenon of unstable shaft system torsional vibration. The stability of the equilibrium point of the dynamical model is investigated, and the Routh–Hurwitz stability criterion is used to obtain a range of values for the bifurcation control parameters. For the stable equilibrium point, the stability domain of the system is calculated by constructing the Lyapunov function. The sensitivity analysis of system parameters is carried out to obtain the law of the effect of system parameters on system stability of the torsional vibration system. The results are substituted for example calculations, and the results verify the correctness of the theoretical analysis conclusions. It is proved that it is feasible to analyze the torsional vibration characteristics of the direct-drive wind turbine shaft system by using the principle of Routh–Hurwitz stability, etc., which provides a reference for the structural design of direct-drive wind turbine. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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22 pages, 8548 KiB  
Article
An Optimization of a Turbocharger Blade Based on Fluid–Structure Interaction
by Minghai Li, Yuanzhe Li, Feng Jiang and Jie Hu
Processes 2022, 10(8), 1569; https://doi.org/10.3390/pr10081569 - 10 Aug 2022
Cited by 3 | Viewed by 2297
Abstract
The structural fracture of the compressor blade is the main cause of fatigue failure. The novelty of this paper is the creative application of bent swept-back modeling to the blade of the turbocharger impeller. This paper is based on a compressor impeller satisfying [...] Read more.
The structural fracture of the compressor blade is the main cause of fatigue failure. The novelty of this paper is the creative application of bent swept-back modeling to the blade of the turbocharger impeller. This paper is based on a compressor impeller satisfying the k-ε turbulence model. A simulation model was established in ANSYS software, the fluid–structure interaction was calculated in the three models before and after improvement, and the results were compared and analyzed. The optimized blade could improve the blade structure, reduce stress and deformation, and improve the pressurization ratio. In this paper, the optimization scheme of different parameters was discussed in line with the optimal solution. Based on the combination of fuzzy and grey correlation theory, it was concluded that the correlation between pressure and total deformation was higher than that of equivalent stress, and these two values reached 0.8596 and 0.8001, respectively. The results showed that the pressure and total deformation were significantly related to the flow rate. It provides a feasible scheme for further improvement of the supercharger compressor. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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14 pages, 8497 KiB  
Article
Research on an Improved Sliding Mode Observer for Speed Estimation in Permanent Magnet Synchronous Motor
by Zhiqiang Liu and Wenkai Chen
Processes 2022, 10(6), 1182; https://doi.org/10.3390/pr10061182 - 13 Jun 2022
Cited by 9 | Viewed by 1990
Abstract
Aimed at the problems of system chattering and large observation errors in the sensorless control of a permanent magnet synchronous motor (PMSM) based on a traditional sliding mode observer (SMO), a combined reaching law algorithm based on the exponential reaching law and arcsine [...] Read more.
Aimed at the problems of system chattering and large observation errors in the sensorless control of a permanent magnet synchronous motor (PMSM) based on a traditional sliding mode observer (SMO), a combined reaching law algorithm based on the exponential reaching law and arcsine saturation function reaching law is proposed to improve the sliding mode observer. An appropriate positive real number is taken and compared with the product of controller gain and stator current observation error to judge the system position in sliding mode motion. In the early stage of sliding mode motion, the exponential reaching law is utilized, and then, in the latter and stable stages of sliding mode motion, the arcsine saturation function reaching law is used. The stability of the observer is proved by Lyapunov theory. The simulation and experimental data show that the speed error of the sliding mode observer based on the combined reaching law is reduced by 80% compared with the traditional sliding mode observer, and the chattering problem is also improved. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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14 pages, 2277 KiB  
Article
Lightweight Design and Experimental Study of Ceramic Composite Armor
by Jianmei Chen, Yihui Zeng, Xiaopeng Liang, Yanbin Hou, Yunliang Wang, Zhenqi Sun and Shuwan Cui
Processes 2022, 10(6), 1056; https://doi.org/10.3390/pr10061056 - 25 May 2022
Cited by 4 | Viewed by 2721
Abstract
Ceramic/fiber composite armor is a hot research topic of bulletproof equipment. The lightweight design of ceramic materials and structures has attracted much attention. In this work, in the light of the remarkable performance of ceramic against elastic and oblique penetration, a novel honeycomb [...] Read more.
Ceramic/fiber composite armor is a hot research topic of bulletproof equipment. The lightweight design of ceramic materials and structures has attracted much attention. In this work, in the light of the remarkable performance of ceramic against elastic and oblique penetration, a novel honeycomb ceramic panel with a hexagonal prism and spherical body was designed. The splicing ceramic/fiber composite plate was bonded with a PE plate. The splicing ceramic/fiber composite was prepared, and the target test of the composite was conducted. The results show that the bulletproof performance of the hexagonal prism spherical crown ceramic/fiber composite plate is better than that of the conventional ceramic/fiber composite plate of the same thickness. The honeycomb spherical crown structure of the ceramic surface can convert the nominal forward penetration into the actual oblique penetration. This surface structure provides an effective lightweight design of ceramic/fiber composite armor. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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27 pages, 4541 KiB  
Article
A GAPN Approach for the Flexible Job-Shop Scheduling Problem with Indirect Energy and Time-of-Use Electricity Pricing
by Jianhua Guo, Qiuyun Luo, Peng Liang and Jia Ouyang
Processes 2022, 10(5), 832; https://doi.org/10.3390/pr10050832 - 22 Apr 2022
Cited by 2 | Viewed by 1446
Abstract
The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes the indirect energy cost, direct energy cost and time cost, the cost evaluation model under ToU pricing is built. To minimize [...] Read more.
The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes the indirect energy cost, direct energy cost and time cost, the cost evaluation model under ToU pricing is built. To minimize the total production cost of the FJSP-IT, an approach based on a genetic algorithm and Petri nets (GAPN) is presented. Under this approach, indirect energy and direct energy are modeled with Petri net (PN) nodes, the operation time is evaluated through PN simulation, and resource allocation is fine-tuned through genetic operations. A group of heuristic operation time policies, especially the exhausting subsection policy and two mixed policies, are presented to adapt to the FJSP-IT with vague cost components. Experiments were performed on a data set generated from the banburying shop of a rubber tire plant, and the results show that the proposed GAPN approach has good convergence. Using the proposed operation time policies makes it possible to save 10.81% on the production cost compared to using the single off-peak first or passive delay policy, and considering indirect energy makes it possible to save at least 2.09% on the production cost compared to ignoring indirect energy. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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13 pages, 4593 KiB  
Article
Evaluation Residual Compressive Strength of Tunnel Lining Concrete Structure after Fire Damage Based on Ultrasonic Pulse Velocity and Shear-Wave Tomography
by Qiang Wang, Daqing Chen, Kai Zhu, Zitai Zhai, Juntao Xu, Linlin Wu, Dong Hu, Weirong Xu and Huandong Huang
Processes 2022, 10(3), 560; https://doi.org/10.3390/pr10030560 - 13 Mar 2022
Cited by 4 | Viewed by 1990
Abstract
In this study, ultrasonic pulse velocity (UPV) and ultrasonic shear-wave tomography are combined to measure the residual compressive strength (RCS) of small-scale lining concrete blocks and to detect inner defects in the lining structure. The characteristics of and variations in the RCS of [...] Read more.
In this study, ultrasonic pulse velocity (UPV) and ultrasonic shear-wave tomography are combined to measure the residual compressive strength (RCS) of small-scale lining concrete blocks and to detect inner defects in the lining structure. The characteristics of and variations in the RCS of test blocks after being exposed to elevated temperatures (200–800 °C) and constant heating times (2 h, 3 h, and 4 h) were studied. At 800 °C, the RCS values reduced by 64.4%, 69.2%, and 74.6% at heating times of 2 h, 3 h, and 4 h. Scanning electron microscopy (SEM) was used for the micro-phase analysis of the samples that had been exposed to high temperatures. The heating time and RCS as well as the SEM micro-structure relationship were compared. Finally, a tunnel lining slab sample was designed to simulate the post-fire damage inside the blocks. Additionally, shear-wave tomography with 32 probes was able to detect the ϕ10 mm void defects at a depth of 200 mm. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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20 pages, 3067 KiB  
Article
Investigation on Energy-Effectiveness Enhancement of Medium-Frequency Induction Furnace Based on an Adaptive Chaos Immune Optimization Algorithm with Mutative Scale
by Hongyan Zuo, Yun Zhu, Dongli Tan, Shuwan Cui, Jiqiu Tan and Dingqing Zhong
Processes 2022, 10(3), 491; https://doi.org/10.3390/pr10030491 - 28 Feb 2022
Cited by 1 | Viewed by 2213
Abstract
Based on the chaos algorithm and immune algorithm theory, an adaptive chaotic immune optimization algorithm (ACIOA) with a mutative scale was proposed and subsequently validated by the experiment result in this paper, and then the adaptive chaotic immune optimization algorithm with mutative scale [...] Read more.
Based on the chaos algorithm and immune algorithm theory, an adaptive chaotic immune optimization algorithm (ACIOA) with a mutative scale was proposed and subsequently validated by the experiment result in this paper, and then the adaptive chaotic immune optimization algorithm with mutative scale was applied to investigate the performance characteristics of the medium-frequency induction furnace. The obtained results include the effects on the performance characteristics of a medium-frequency induction furnace of the diameter of the heated cylindrical material, the thickness of the crucible wall, the fullness degree of the induction coil, the ratio of diameter to current penetration depth, and the power frequency. The results showed that the optimization algorithm could continuously modify the variable search space and take the optimal number of cycles as the control index to carry out the search. In addition, the suitable ratio of diameter to current penetration depth was between 3.5 and 6.0, and was beneficial to the improvements of in power factor and thermal efficiency. This method had the characteristics of small calculation delay, high anti-noise ability, and high detection rate. Moreover, the maximum errors of KFF, Random, and PSO were 6.4%, 6.2%, and 5.4%, respectively. The improved method had good estimation accuracy and an excellent global optimization. Meanwhile, the suitable ratio of diameter to current penetration depth, the thickness of crucible wall, and power frequency were beneficial to the improvements in power factor and thermal efficiency. Thus, the finding is helpful as a guide to determining the design of a medium-frequency induction furnace, which may be of interest for improvements in performance under different operating conditions. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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19 pages, 4134 KiB  
Article
A Spatio-Temporal Deep Learning Network for the Short-Term Energy Consumption Prediction of Multiple Nodes in Manufacturing Systems
by Jianhua Guo, Mingdong Han, Guozhi Zhan and Shaopeng Liu
Processes 2022, 10(3), 476; https://doi.org/10.3390/pr10030476 - 26 Feb 2022
Cited by 4 | Viewed by 2182
Abstract
Short-term energy prediction plays an important role in green manufacturing in the industrial internet environment and has become the basis of energy wastage identification, energy-saving plans and energy-saving control. However, the short-term energy prediction of multiple nodes in manufacturing systems is still a [...] Read more.
Short-term energy prediction plays an important role in green manufacturing in the industrial internet environment and has become the basis of energy wastage identification, energy-saving plans and energy-saving control. However, the short-term energy prediction of multiple nodes in manufacturing systems is still a challenging issue owing to the fuzzy material flow (spatial relationship) and the dynamic production rhythm (temporal relationship). To obtain the complex spatial and temporal relationships, a spatio-temporal deep learning network (STDLN) method is presented for the short-term energy consumption prediction of multiple nodes in manufacturing systems. The method combines a graph convolutional network (GCN) and a gated recurrent unit (GRU) and predicts the future energy consumption of multiple nodes based on prior knowledge of material flow and the historical energy consumption time series. The GCN is aimed at capturing spatial relationships, with the material flow represented by a topology model, and the GRU is aimed at capturing dynamic rhythm from the energy consumption time series. To evaluate the method presented, several experiments were performed on the power consumption dataset of an aluminum profile plant. The results show that the method presented can predict the energy consumption of multiple nodes simultaneously and achieve a higher performance than methods based on the GRU, GCN, support vector regression (SVR), etc. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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17 pages, 4232 KiB  
Article
Splitting Physical Exergy by Its Feasible Working Ways
by Dongbo Gao, Xiaoqi Peng, Yanpo Song and Ping Zhou
Processes 2021, 9(11), 2091; https://doi.org/10.3390/pr9112091 - 22 Nov 2021
Cited by 1 | Viewed by 1389
Abstract
This paper analyzed the problems associated with physical exergy splitting, and based on this, presented a new splitting method. This new method splits the physical exergy into three parts according to the feasible working ways, i.e.,: the direct, indirect, and adaptive exergy. The [...] Read more.
This paper analyzed the problems associated with physical exergy splitting, and based on this, presented a new splitting method. This new method splits the physical exergy into three parts according to the feasible working ways, i.e.,: the direct, indirect, and adaptive exergy. The computational method and the physical meaning of the three exergy parts were presented in detail in terms of graphic representation and mathematical derivation. Then, it was applied to the exergy analysis of a thermal power cycle. The results show that compared with the conventional method which splits the physical exergy into thermal and mechanical parts, the current exergy splitting method can better represent the change rule of the working ability of the real working stream in the cycle and the influence of some operation parameters, such as the turbine inlet temperature, on the real working ability. The study suggests that the new method can make the exergy analysis more helpful and guidable in its applications. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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15 pages, 1895 KiB  
Article
Probabilistic Vulnerability Assessment of Transmission Lines Considering Cascading Failures
by Yanchen Liu, Minfang Peng, Xingle Gao and Haiyan Zhang
Processes 2021, 9(11), 1994; https://doi.org/10.3390/pr9111994 - 8 Nov 2021
Cited by 2 | Viewed by 1374
Abstract
The prevention of cascading failures and large-scale power outages of power grids by identifying weak links has become one of the key topics in power systems research. In this paper, a vulnerability radius index is proposed to identify the initial fault, and a [...] Read more.
The prevention of cascading failures and large-scale power outages of power grids by identifying weak links has become one of the key topics in power systems research. In this paper, a vulnerability radius index is proposed to identify the initial fault, and a fault chain model of cascading failure is developed with probabilistic attributes to identify the set of fault chains that have a significant impact on the safe and stable operation of power grids. On this basis, a method for evaluating the vulnerability of transmission lines based on a multi-criteria decision analysis is proposed, which can quickly identify critical transmission lines in the process of cascading failure. Finally, the proposed model and method for identifying vulnerable lines during the cascading failure process is demonstrated on the IEEE-118 bus system. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)
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