Urban green spaces (UGSs) are considered an important natural approach for improving urban climatic conditions, promoting sustainable urban development, and advancing the global “Carbon Peak and Carbon Neutrality” targets. Previous studies have found that different vegetation spatial morphologies significantly impact the capacity to obstruct and absorb CO2, but it is not yet well understood which morphology can retain and absorb more CO2. This study takes Nantong Central Park as an example and conducts a CFD (Computational Fluid Dynamics) carbon flow simulation for CO2 under different vegetation spatial morphologies to identify their CO2 retention and absorption effects. First, the carbon sink benefits of elements such as “vegetation, soil, and wetlands” within the park were calculated, and the elements with the highest carbon sink benefits were identified. Then, the park was divided into carbon welcoming zones, carbon flow zones, and carbon shadow zones for carbon flow simulation with the highest carbon sink benefits. The results show that in the carbon welcome area, the one-block long fan-shaped plant community with a spatial density of 40 m thickness can best meet the requirements of absorption and induction of a small amount of carbon dioxide, with the smallest air vortex and uniform distribution of carbon dioxide in the surrounding area. In the carbon flow area, combined with the visual effect, the planting pattern of 6 m spacing herringbone combined with natural structure was adopted, which has a good carbon dioxide blocking and absorption capacity. In the carbon-shaded area, a herringbone planting pattern with a total width of 40 m and a base angle of 60° was chosen, which had the strongest hindrance and absorption capacity. Urban park environment optimization can use Fluent simulation to analyze the flow of carbon dioxide between different elements affected by wind dynamics at the same time. Based on the results, the form, layout, and spatial distance are adjusted and optimized. This study can better guide the spatial layout of vegetation and contribute to the realization of the goal of “carbon peak and carbon neutrality”.
{"title":"Research on Carbon Dioxide Computational Fluid Dynamics Simulation of Urban Green Spaces under Different Vegetation Spatial Layout Morphologies","authors":"Jing Li, Lang Zhang, Haoran Yu, Yi Zhu","doi":"10.3390/pr12091931","DOIUrl":"https://doi.org/10.3390/pr12091931","url":null,"abstract":"Urban green spaces (UGSs) are considered an important natural approach for improving urban climatic conditions, promoting sustainable urban development, and advancing the global “Carbon Peak and Carbon Neutrality” targets. Previous studies have found that different vegetation spatial morphologies significantly impact the capacity to obstruct and absorb CO2, but it is not yet well understood which morphology can retain and absorb more CO2. This study takes Nantong Central Park as an example and conducts a CFD (Computational Fluid Dynamics) carbon flow simulation for CO2 under different vegetation spatial morphologies to identify their CO2 retention and absorption effects. First, the carbon sink benefits of elements such as “vegetation, soil, and wetlands” within the park were calculated, and the elements with the highest carbon sink benefits were identified. Then, the park was divided into carbon welcoming zones, carbon flow zones, and carbon shadow zones for carbon flow simulation with the highest carbon sink benefits. The results show that in the carbon welcome area, the one-block long fan-shaped plant community with a spatial density of 40 m thickness can best meet the requirements of absorption and induction of a small amount of carbon dioxide, with the smallest air vortex and uniform distribution of carbon dioxide in the surrounding area. In the carbon flow area, combined with the visual effect, the planting pattern of 6 m spacing herringbone combined with natural structure was adopted, which has a good carbon dioxide blocking and absorption capacity. In the carbon-shaded area, a herringbone planting pattern with a total width of 40 m and a base angle of 60° was chosen, which had the strongest hindrance and absorption capacity. Urban park environment optimization can use Fluent simulation to analyze the flow of carbon dioxide between different elements affected by wind dynamics at the same time. Based on the results, the form, layout, and spatial distance are adjusted and optimized. This study can better guide the spatial layout of vegetation and contribute to the realization of the goal of “carbon peak and carbon neutrality”.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The transportation of coal-based solid waste filling slurry (CSWFS) through pipelines for underground goaf injection is essential for enhancing mine safety and promoting green, low-carbon coal mining. To address the issue of pipeline blockage caused by the suspension sensitivity of CSWFS during long-distance transportation, this study proposes the addition of the suspending agent hydroxypropyl methyl cellulose (HPMC) to transform the filling slurry into a stable suspending slurry. The mechanism by which the suspending agent modifies the rheological property of CSWFS was elucidated and verified. Firstly, an evaluation index system for the suspending state of CSWFS based on the “experimental test and theoretical calculation” was established. The values for layering degree, bleeding rate time-loss, and the corresponding average time-loss rate over 0 to 120 min of A1–A5 CSWFS were recorded as 24 mm–2 mm, 3.0–0.2%, 252.4–54.2%, and 149.6–14.6%, respectively. The concentration gradient evaluation result, C/CA = 0.91 (≥0.8), confirmed that the suspending agent maintained a stable suspending state over time for CSWFS. Secondly, it was demonstrated that the suspending agent HPMC modified the rheological property of A1–A5 CSWFS by increasing its plastic viscosity, which strengthened the viscous resistance to particle settling, thereby transforming a semi-stable slurry into a stable one. Additionally, the formation of a spatial suspending network by the suspending agent ensures that no pipeline blockage accidents occured in practical engineering applications. Furthermore, the XRD and SEM tests were utilized to verify the microstructure of the top (T) and bottom (B) samples in A4 block. It was concluded that the type of hydration products, occurrence forms, lapping compactness, and microstructural development were consistent, ultimately forming a high-strength, dense, hardened filling block. Finally, numerical simulation confirmed that the addition of suspending agent in A4 slurry formed a comprehensive spatial suspending network and a well-structured, unified system. This is one effective approach which could contribute to addressing the technical issue of pipeline blockage during long-distance pipeline transportation.
{"title":"Experimental Study on the Suspending Mechanism of Suspending Agent in Coal-Based Solid Waste Slurry for Long-Distance Pipeline Transportation","authors":"Tao Li, Tao Yang, Heng Min, Min Cao, Jingyan Hu","doi":"10.3390/pr12091937","DOIUrl":"https://doi.org/10.3390/pr12091937","url":null,"abstract":"The transportation of coal-based solid waste filling slurry (CSWFS) through pipelines for underground goaf injection is essential for enhancing mine safety and promoting green, low-carbon coal mining. To address the issue of pipeline blockage caused by the suspension sensitivity of CSWFS during long-distance transportation, this study proposes the addition of the suspending agent hydroxypropyl methyl cellulose (HPMC) to transform the filling slurry into a stable suspending slurry. The mechanism by which the suspending agent modifies the rheological property of CSWFS was elucidated and verified. Firstly, an evaluation index system for the suspending state of CSWFS based on the “experimental test and theoretical calculation” was established. The values for layering degree, bleeding rate time-loss, and the corresponding average time-loss rate over 0 to 120 min of A1–A5 CSWFS were recorded as 24 mm–2 mm, 3.0–0.2%, 252.4–54.2%, and 149.6–14.6%, respectively. The concentration gradient evaluation result, C/CA = 0.91 (≥0.8), confirmed that the suspending agent maintained a stable suspending state over time for CSWFS. Secondly, it was demonstrated that the suspending agent HPMC modified the rheological property of A1–A5 CSWFS by increasing its plastic viscosity, which strengthened the viscous resistance to particle settling, thereby transforming a semi-stable slurry into a stable one. Additionally, the formation of a spatial suspending network by the suspending agent ensures that no pipeline blockage accidents occured in practical engineering applications. Furthermore, the XRD and SEM tests were utilized to verify the microstructure of the top (T) and bottom (B) samples in A4 block. It was concluded that the type of hydration products, occurrence forms, lapping compactness, and microstructural development were consistent, ultimately forming a high-strength, dense, hardened filling block. Finally, numerical simulation confirmed that the addition of suspending agent in A4 slurry formed a comprehensive spatial suspending network and a well-structured, unified system. This is one effective approach which could contribute to addressing the technical issue of pipeline blockage during long-distance pipeline transportation.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ricardo Andrés García-León, Jorge Trigos-Caceres, Natalia Castilla-Quintero, Nelson Afanador-García, July Gómez-Camperos
The environmental impact of traditional construction materials necessitates the development of sustainable alternatives. This study evaluates eco-cobbles as novel building materials designed to reduce environmental footprint while maintaining performance standards. The objectives were to develop an eco-friendly cobble alternative and assess its effectiveness through laboratory tests. Eco-cobbles were synthesized using recycled and bio-based materials and tested for compressive strength, flexural strength, and water absorption at 14 and 28 days. The compressive strength ranged from 11.5 MPa to 26.8 MPa, with a maximum value observed at 28 days in a mixture containing 95% concrete and 5% polyethylene terephthalate (PET). Flexural strength varied from 9.1 MPa to 28.7 MPa, with the highest value achieved in a mixture of 95% concrete and 0% fibers. Water absorption rates ranged from 2.1% to 6.6%, demonstrating an effective balance between performance and durability. Environmental assessments indicated a 30% reduction in resource consumption and a 40% decrease in carbon footprint compared to traditional cobble production methods. The findings demonstrate that eco-cobbles not only meet performance standards but also offer significant environmental benefits with a 99% compliance from the results obtained by response surface methodology plots, confirming that eco-cobbles offer a viable, sustainable alternative to conventional materials, with the potential for broader application in eco-friendly construction practices.
{"title":"Experimental and Statistical Analysis of Concrete Eco-Cobble Using Organic and Synthetic Fibers","authors":"Ricardo Andrés García-León, Jorge Trigos-Caceres, Natalia Castilla-Quintero, Nelson Afanador-García, July Gómez-Camperos","doi":"10.3390/pr12091936","DOIUrl":"https://doi.org/10.3390/pr12091936","url":null,"abstract":"The environmental impact of traditional construction materials necessitates the development of sustainable alternatives. This study evaluates eco-cobbles as novel building materials designed to reduce environmental footprint while maintaining performance standards. The objectives were to develop an eco-friendly cobble alternative and assess its effectiveness through laboratory tests. Eco-cobbles were synthesized using recycled and bio-based materials and tested for compressive strength, flexural strength, and water absorption at 14 and 28 days. The compressive strength ranged from 11.5 MPa to 26.8 MPa, with a maximum value observed at 28 days in a mixture containing 95% concrete and 5% polyethylene terephthalate (PET). Flexural strength varied from 9.1 MPa to 28.7 MPa, with the highest value achieved in a mixture of 95% concrete and 0% fibers. Water absorption rates ranged from 2.1% to 6.6%, demonstrating an effective balance between performance and durability. Environmental assessments indicated a 30% reduction in resource consumption and a 40% decrease in carbon footprint compared to traditional cobble production methods. The findings demonstrate that eco-cobbles not only meet performance standards but also offer significant environmental benefits with a 99% compliance from the results obtained by response surface methodology plots, confirming that eco-cobbles offer a viable, sustainable alternative to conventional materials, with the potential for broader application in eco-friendly construction practices.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fanghong Jian, Jiangfeng Li, Xiaomei Liu, Qiong Wu, Dan Zhong
Deng’s grey relational analysis (GRA) model is widely used in clustering because of its simple mathematical mechanisms. For sample data of different dimensions, people have put forward different Deng’s GRA models, including time series data, panel data, and panel time series data. The purpose of this paper is to improve the clustering accuracy of the existing Deng’s GRA model for panel data in order to overcome some of its shortcomings. Firstly, the existing Deng’s GRA model for panel data was tested based on the dataset LP1 of Robot Execution Failures. Then, according to the test results, the existing Deng’s GRA model for panel data is modified by means of Taylor’s formula, and the modified model is successfully validated by the dataset LP1 of Robot Execution Failures. Finally, as a practical application, the modified Deng’s GRA model for panel data is applied to assess the water environment of Poyang Lake over the past five years. Compared with other cluster methods, the results of the case study show that the modified Deng’s GRA model for panel data is applicable and also confirm the remarkable effectiveness of the Chinese government’s water quality regulation in Poyang Lake. Therefore, the modified Deng’s GRA model presented in this paper improves the clustering accuracy compared to the original model and can be applied well to the classification of data with a large dimension.
邓氏灰色关系分析（GRA）模型因其简单的数学机制而被广泛应用于聚类分析。针对不同维度的样本数据，人们提出了不同的邓氏 GRA 模型，包括时间序列数据、面板数据和面板时间序列数据。本文旨在改进现有 Deng's GRA 模型对面板数据的聚类精度，以克服其存在的一些不足。首先，以机器人执行故障数据集 LP1 为基础，对现有的面板数据 Deng's GRA 模型进行了测试。然后，根据测试结果，利用泰勒公式对现有的 Deng 面板数据 GRA 模型进行修正，并通过机器人执行故障数据集 LP1 成功验证了修正后的模型。最后，在实际应用中，将改进后的面板数据邓氏 GRA 模型用于评估鄱阳湖近五年的水环境状况。与其他聚类方法相比，案例研究结果表明，修正的邓氏面板数据 GRA 模型是适用的，同时也证实了中国政府对鄱阳湖水质监管的显著成效。因此，本文提出的改进型邓氏 GRA 模型与原始模型相比提高了聚类精度，可以很好地应用于大维度数据的分类。
{"title":"Modified Deng’s Grey Relational Analysis Model for Panel Data and Its Applications in Assessing the Water Environment of Poyang Lake","authors":"Fanghong Jian, Jiangfeng Li, Xiaomei Liu, Qiong Wu, Dan Zhong","doi":"10.3390/pr12091935","DOIUrl":"https://doi.org/10.3390/pr12091935","url":null,"abstract":"Deng’s grey relational analysis (GRA) model is widely used in clustering because of its simple mathematical mechanisms. For sample data of different dimensions, people have put forward different Deng’s GRA models, including time series data, panel data, and panel time series data. The purpose of this paper is to improve the clustering accuracy of the existing Deng’s GRA model for panel data in order to overcome some of its shortcomings. Firstly, the existing Deng’s GRA model for panel data was tested based on the dataset LP1 of Robot Execution Failures. Then, according to the test results, the existing Deng’s GRA model for panel data is modified by means of Taylor’s formula, and the modified model is successfully validated by the dataset LP1 of Robot Execution Failures. Finally, as a practical application, the modified Deng’s GRA model for panel data is applied to assess the water environment of Poyang Lake over the past five years. Compared with other cluster methods, the results of the case study show that the modified Deng’s GRA model for panel data is applicable and also confirm the remarkable effectiveness of the Chinese government’s water quality regulation in Poyang Lake. Therefore, the modified Deng’s GRA model presented in this paper improves the clustering accuracy compared to the original model and can be applied well to the classification of data with a large dimension.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Augustin Varga, Jan Kizek, Miroslav Rimar, Marcel Fedak, Gustáv Jablonský, Peter Oravec, Wojciech Bialik
The authors of this study focused on the energy and material assessment of processes for processing pellets from metal-bearing waste, specifically Fe concentrate. A mathematical model was created for process evaluation, with which thermotechnical calculations of parameters in the processing of metallized pellets were carried out. Thermodynamic calculations were performed to determine the enthalpy of the charge in individual devices (drying chamber, rotary kiln, cooler). For the reduction of Fe oxides, carbon from coke (with Fe oxide reductions of 50%, 61%, and 92%) and lignite (with Fe oxide reductions of 69% and 92%) were considered as part of the pellets. The degree of reduction of iron oxides was a determining parameter, and the consumption of the reducing agent corresponded to the direct reduction of Fe oxides by carbon with a coefficient of 1.5. Another determining parameter was the input and output temperature in individual devices. For a more precise description of the processes in individual devices, calculations were carried out zonally. The results of the calculations are analyses and recommendations for feasible alternatives for the reducing agent and associated processes.
{"title":"Energy Evaluation and Mathematical Modeling of Pellet Production from Metal-Bearing Waste with a Focus on Alternative Applications of Reducing Agents","authors":"Augustin Varga, Jan Kizek, Miroslav Rimar, Marcel Fedak, Gustáv Jablonský, Peter Oravec, Wojciech Bialik","doi":"10.3390/pr12091938","DOIUrl":"https://doi.org/10.3390/pr12091938","url":null,"abstract":"The authors of this study focused on the energy and material assessment of processes for processing pellets from metal-bearing waste, specifically Fe concentrate. A mathematical model was created for process evaluation, with which thermotechnical calculations of parameters in the processing of metallized pellets were carried out. Thermodynamic calculations were performed to determine the enthalpy of the charge in individual devices (drying chamber, rotary kiln, cooler). For the reduction of Fe oxides, carbon from coke (with Fe oxide reductions of 50%, 61%, and 92%) and lignite (with Fe oxide reductions of 69% and 92%) were considered as part of the pellets. The degree of reduction of iron oxides was a determining parameter, and the consumption of the reducing agent corresponded to the direct reduction of Fe oxides by carbon with a coefficient of 1.5. Another determining parameter was the input and output temperature in individual devices. For a more precise description of the processes in individual devices, calculations were carried out zonally. The results of the calculations are analyses and recommendations for feasible alternatives for the reducing agent and associated processes.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under the condition of multiple wells, the inverse problem of two-phase flow typically requires hundreds of forward runs of the simulator to achieve meaningful coverage, leading to a substantial computational workload in reservoir numerical simulations. To tackle this challenge, we propose an innovative approach leveraging a surrogate model named TgCNN (Theory-guided Convolutional Neural Network). This method integrates deep learning with computational fluid dynamics simulations to predict the behavior of two-phase flow. The model is not solely data-driven but also incorporates scientific theory. It comprises a coupled permeability module, a pressure module, and a water saturation module. The accuracy of the surrogate model was comprehensively tested from multiple perspectives in this study. Subsequently, efforts were made to address the permeability-field inverse problem under multi-well conditions by combining the surrogate model with the Ensemble Random Maximum Likelihood (EnRML) algorithm. The research findings indicate that modifying the network structure allows for improved integration of the outputs, resulting in prediction accuracy and computational efficiency. The TgCNN surrogate model demonstrated outstanding predictive performance and computational efficiency in two-phase flow. By combining the surrogate model with the EnRML algorithm, the inversion results closely aligned with those from the commercial simulation software, significantly improving the computational efficiency.
{"title":"Inverse Problem of Permeability Field under Multi-Well Conditions Using TgCNN-Based Surrogate Model","authors":"Jian Li, Ran Zhang, Haochen Wang, Zhengxiao Xu","doi":"10.3390/pr12091934","DOIUrl":"https://doi.org/10.3390/pr12091934","url":null,"abstract":"Under the condition of multiple wells, the inverse problem of two-phase flow typically requires hundreds of forward runs of the simulator to achieve meaningful coverage, leading to a substantial computational workload in reservoir numerical simulations. To tackle this challenge, we propose an innovative approach leveraging a surrogate model named TgCNN (Theory-guided Convolutional Neural Network). This method integrates deep learning with computational fluid dynamics simulations to predict the behavior of two-phase flow. The model is not solely data-driven but also incorporates scientific theory. It comprises a coupled permeability module, a pressure module, and a water saturation module. The accuracy of the surrogate model was comprehensively tested from multiple perspectives in this study. Subsequently, efforts were made to address the permeability-field inverse problem under multi-well conditions by combining the surrogate model with the Ensemble Random Maximum Likelihood (EnRML) algorithm. The research findings indicate that modifying the network structure allows for improved integration of the outputs, resulting in prediction accuracy and computational efficiency. The TgCNN surrogate model demonstrated outstanding predictive performance and computational efficiency in two-phase flow. By combining the surrogate model with the EnRML algorithm, the inversion results closely aligned with those from the commercial simulation software, significantly improving the computational efficiency.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evangelos E. Pompodakis, Arif Ahmed, Georgios I. Orfanoudakis, Emmanuel S. Karapidakis
The European Union has established ambitious targets for lowering carbon dioxide emissions in the residential sector, aiming for all new buildings to be “zero-emission” by 2030. Integrating solar generators with hydrogen storage systems is emerging as a viable solution for achieving these goals in homes. This paper introduces a linear programming optimization algorithm aimed at improving the installation capacity of residential solar–hydrogen systems, which also utilize waste heat recovery from electrolyzers and fuel cells to increase the overall efficiency of the system. Analyzing six European cities with diverse climate conditions, our techno-economic assessments show that optimized configurations of these systems can lead to significant net present cost savings for electricity and heat over a 20-year period, with potential savings up to EUR 63,000, which amounts to a 26% cost reduction, especially in Southern Europe due to its abundant solar resources. Furthermore, these systems enhance sustainability and viability in the residential sector by significantly reducing carbon emissions. Our study does not account for the potential economic benefits from EU subsidies. Instead, we propose a novel incentive policy that allows owners of solar–hydrogen systems to inject up to 20% of their total solar power output directly into the grid, bypassing hydrogen storage. This strategy provides two key advantages: first, it enables owners to profit by selling the excess photovoltaic power during peak midday hours, rather than curtailing production; second, it facilitates a reduction in the size—and therefore cost—of the electrolyzer.
{"title":"Optimization of Residential Hydrogen Facilities with Waste Heat Recovery: Economic Feasibility across Various European Cities","authors":"Evangelos E. Pompodakis, Arif Ahmed, Georgios I. Orfanoudakis, Emmanuel S. Karapidakis","doi":"10.3390/pr12091933","DOIUrl":"https://doi.org/10.3390/pr12091933","url":null,"abstract":"The European Union has established ambitious targets for lowering carbon dioxide emissions in the residential sector, aiming for all new buildings to be “zero-emission” by 2030. Integrating solar generators with hydrogen storage systems is emerging as a viable solution for achieving these goals in homes. This paper introduces a linear programming optimization algorithm aimed at improving the installation capacity of residential solar–hydrogen systems, which also utilize waste heat recovery from electrolyzers and fuel cells to increase the overall efficiency of the system. Analyzing six European cities with diverse climate conditions, our techno-economic assessments show that optimized configurations of these systems can lead to significant net present cost savings for electricity and heat over a 20-year period, with potential savings up to EUR 63,000, which amounts to a 26% cost reduction, especially in Southern Europe due to its abundant solar resources. Furthermore, these systems enhance sustainability and viability in the residential sector by significantly reducing carbon emissions. Our study does not account for the potential economic benefits from EU subsidies. Instead, we propose a novel incentive policy that allows owners of solar–hydrogen systems to inject up to 20% of their total solar power output directly into the grid, bypassing hydrogen storage. This strategy provides two key advantages: first, it enables owners to profit by selling the excess photovoltaic power during peak midday hours, rather than curtailing production; second, it facilitates a reduction in the size—and therefore cost—of the electrolyzer.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to investigate the effect of the application of different freeze-drying conditions on the process’s kinetics and the sorption properties of dried apples. Slices of apples were frozen and subjected to a freezing-drying process with different combinations of shelf temperature (−20, 10, 20, and 30 °C) and pressure (37, 63, 103, and 165 Pa). During the freeze-drying, the temperature in the centre of the material was recorded. The moisture content in the dried material and changes in the water content in dried apples stored at a humidity of 75.3% were obtained. The Midilli et al. model was used to describe the drying kinetics of the freeze-drying with a good fit. Drying time increased from 660 (variant with a constant shelf temperature of 30 °C, pressure 63 Pa) to 1305 min (variants with temperatures −20:10:20:30 °C, pressure 63 Pa). For this reason, the most favourable experimental parameters were a temperature of 30 °C and a pressure of 63 Pa. However, applying these parameters caused higher absorption of water vapour during storage. Therefore, the selection of freeze-drying parameters should also be related to the expected properties of the final product.
本研究旨在探讨不同冷冻干燥条件的应用对该过程的动力学和苹果干的吸附特性的影响。对苹果切片进行冷冻，并在不同的保存温度（-20、10、20 和 30 °C）和压力（37、63、103 和 165 Pa）组合下进行冷冻干燥。在冷冻干燥过程中，记录材料中心的温度。得出了干燥材料中的含水量以及在湿度为 75.3% 的条件下储存的干苹果中含水量的变化。Midilli 等人的模型被用来描述冷冻干燥的干燥动力学，拟合效果良好。干燥时间从 660 分钟（货架温度恒定为 30 °C，压力为 63 Pa 的变量）增加到 1305 分钟（温度为 -20:10:20:30 °C，压力为 63 Pa 的变量）。因此，最有利的实验参数是温度 30 °C 和压力 63 Pa。因此，冷冻干燥参数的选择也应与最终产品的预期特性有关。
{"title":"Process Parameters as Tools to Intensify the Freeze-Drying Process and Modify the Sorption Properties of the Obtained Freeze-Dried Products","authors":"Ewa Jakubczyk, Dorota Nowak","doi":"10.3390/pr12091932","DOIUrl":"https://doi.org/10.3390/pr12091932","url":null,"abstract":"This study aimed to investigate the effect of the application of different freeze-drying conditions on the process’s kinetics and the sorption properties of dried apples. Slices of apples were frozen and subjected to a freezing-drying process with different combinations of shelf temperature (−20, 10, 20, and 30 °C) and pressure (37, 63, 103, and 165 Pa). During the freeze-drying, the temperature in the centre of the material was recorded. The moisture content in the dried material and changes in the water content in dried apples stored at a humidity of 75.3% were obtained. The Midilli et al. model was used to describe the drying kinetics of the freeze-drying with a good fit. Drying time increased from 660 (variant with a constant shelf temperature of 30 °C, pressure 63 Pa) to 1305 min (variants with temperatures −20:10:20:30 °C, pressure 63 Pa). For this reason, the most favourable experimental parameters were a temperature of 30 °C and a pressure of 63 Pa. However, applying these parameters caused higher absorption of water vapour during storage. Therefore, the selection of freeze-drying parameters should also be related to the expected properties of the final product.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Operating in harsh environments, drilling pumps are highly susceptible to failure and challenging to diagnose. To enhance the fault diagnosis accuracy of the drilling pump fluid end and ensure the safety and stability of drilling operations, this paper proposes a fault diagnosis method based on time-frequency analysis and convolutional neural networks. Firstly, continuous wavelet transform (CWT) is used to convert the collected vibration signals into time-frequency diagrams, providing a comprehensive database for fault diagnosis. Next, a SqueezeNet-based fault diagnosis model is developed to identify faults. To validate the effectiveness of the proposed method, fault signals from the fluid end were collected, and fault diagnosis experiments were conducted. The experimental results demonstrated that the proposed method achieved an accuracy of 97.77% in diagnosing nine types of faults at the fluid end, effectively enabling precise fault diagnosis, which is higher than the accuracy of a 1D convolutional neural network by 14.55%. This study offers valuable insights into the fault diagnosis of drilling pumps and other complex equipment.
{"title":"Research on Fault Diagnosis of Drilling Pump Fluid End Based on Time-Frequency Analysis and Convolutional Neural Network","authors":"Maolin Dai, Zhiqiang Huang","doi":"10.3390/pr12091929","DOIUrl":"https://doi.org/10.3390/pr12091929","url":null,"abstract":"Operating in harsh environments, drilling pumps are highly susceptible to failure and challenging to diagnose. To enhance the fault diagnosis accuracy of the drilling pump fluid end and ensure the safety and stability of drilling operations, this paper proposes a fault diagnosis method based on time-frequency analysis and convolutional neural networks. Firstly, continuous wavelet transform (CWT) is used to convert the collected vibration signals into time-frequency diagrams, providing a comprehensive database for fault diagnosis. Next, a SqueezeNet-based fault diagnosis model is developed to identify faults. To validate the effectiveness of the proposed method, fault signals from the fluid end were collected, and fault diagnosis experiments were conducted. The experimental results demonstrated that the proposed method achieved an accuracy of 97.77% in diagnosing nine types of faults at the fluid end, effectively enabling precise fault diagnosis, which is higher than the accuracy of a 1D convolutional neural network by 14.55%. This study offers valuable insights into the fault diagnosis of drilling pumps and other complex equipment.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate measurement of the pore size distribution (PSD) in coals is crucial for guiding subsequent coalbed methane (CBM) engineering practice. Currently, mercury intrusion porosimetry (MIP) measurement has been widely used as a PSD testing method due to its effectiveness and convenience. Nevertheless, it is worth noting that the elevated pressure during the MIP experiments can lead to matrix compressibility, potentially causing inaccurate estimations of PSD in coals. Therefore, correction methods are used to modify the PSD in the high-pressure segment to improve the accuracy of MIP data. This study proposed a novel method with higher accuracy and convenience for calculating the matrix compressibility coefficient compared to the traditional calculation methods. Firstly, the matrix compressibility coefficients of six coal samples were calculated by using low-temperature nitrogen adsorption (LTNA) data. Subsequently, by utilizing the mathematical correlation between Kc (the compressibility coefficient of the coal matrix) and Ro,max (the maximum vitrinite reflectance) from prior research, a novel statistical method was designed to determine the matrix compressibility coefficient of the samples. Finally, the statistical matrix compressibility coefficient determination method was used to examine the fractal characteristics of the actual PSD. The results indicate that when the pressure exceeds 24 MPa, the volume obtained from mercury intrusion exceeds the pore volume measurement. The Kc calculated using the traditional correction method is in the range of 0.876–1.184 × 10−10 m2/N, while the Kc values of our proposed statistical correction method range from 0.898 × 10−10 to 1.233 × 10−10 m2/N, with a comparison error rate of ~0.11–5.25%. The MIP data greater than 24 MPa were effectively corrected using the statistical correction method, thus reducing the mercury intrusion volume error by 91.75–96.40%. Additionally, the corrected pore fractal dimension (D2) values fall within the range of 2.792 to 2.975, which are closer to the actual values than the pore fractal dimension range of 3.186 to 3.339.
{"title":"Re-Calibrating the Mercury-Intrusion-Porosimetry-Measured Pore Size Distribution of Coals: A Novel Method for Calculating the Matrix Compression Coefficient","authors":"Bin Ren, Sijian Zheng, Lihua Ping, Meng Wang, Xuguang Dai, Yanzhi Liu, Shen Xu, Xiuping Wu","doi":"10.3390/pr12091928","DOIUrl":"https://doi.org/10.3390/pr12091928","url":null,"abstract":"Accurate measurement of the pore size distribution (PSD) in coals is crucial for guiding subsequent coalbed methane (CBM) engineering practice. Currently, mercury intrusion porosimetry (MIP) measurement has been widely used as a PSD testing method due to its effectiveness and convenience. Nevertheless, it is worth noting that the elevated pressure during the MIP experiments can lead to matrix compressibility, potentially causing inaccurate estimations of PSD in coals. Therefore, correction methods are used to modify the PSD in the high-pressure segment to improve the accuracy of MIP data. This study proposed a novel method with higher accuracy and convenience for calculating the matrix compressibility coefficient compared to the traditional calculation methods. Firstly, the matrix compressibility coefficients of six coal samples were calculated by using low-temperature nitrogen adsorption (LTNA) data. Subsequently, by utilizing the mathematical correlation between Kc (the compressibility coefficient of the coal matrix) and Ro,max (the maximum vitrinite reflectance) from prior research, a novel statistical method was designed to determine the matrix compressibility coefficient of the samples. Finally, the statistical matrix compressibility coefficient determination method was used to examine the fractal characteristics of the actual PSD. The results indicate that when the pressure exceeds 24 MPa, the volume obtained from mercury intrusion exceeds the pore volume measurement. The Kc calculated using the traditional correction method is in the range of 0.876–1.184 × 10−10 m2/N, while the Kc values of our proposed statistical correction method range from 0.898 × 10−10 to 1.233 × 10−10 m2/N, with a comparison error rate of ~0.11–5.25%. The MIP data greater than 24 MPa were effectively corrected using the statistical correction method, thus reducing the mercury intrusion volume error by 91.75–96.40%. Additionally, the corrected pore fractal dimension (D2) values fall within the range of 2.792 to 2.975, which are closer to the actual values than the pore fractal dimension range of 3.186 to 3.339.","PeriodicalId":20597,"journal":{"name":"Processes","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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