María Urrestizala de Andrés, JON AZKURRETA, NATALIA ALEGRIA GUTIERREZ, IGOR PEÑALVA BENGOA
Nuclear fusion energy emerges as one of the main alternatives in the medium and long term, capable of complementing the variable contribution of renewable energies. This paper will discuss its status and the main challenges it faces for its development, as well as the main elements and alternatives that will make up future fusion reactors. The international ITER project is critical to verify the integrity of all this technology. It sets out a series of milestones that will represent an intermediate step towards becoming a major contribution to the energy system, demonstrating the technological feasibility of each of its components. Key words: nuclear fusion, energy, reactor, ITER
{"title":"NUCLEAR FUSION. CURRENT SITUATION AND MAIN CHALLENGES IT FACES","authors":"María Urrestizala de Andrés, JON AZKURRETA, NATALIA ALEGRIA GUTIERREZ, IGOR PEÑALVA BENGOA","doi":"10.6036/10861","DOIUrl":"https://doi.org/10.6036/10861","url":null,"abstract":"Nuclear fusion energy emerges as one of the main alternatives in the medium and long term, capable of complementing the variable contribution of renewable energies. This paper will discuss its status and the main challenges it faces for its development, as well as the main elements and alternatives that will make up future fusion reactors. The international ITER project is critical to verify the integrity of all this technology. It sets out a series of milestones that will represent an intermediate step towards becoming a major contribution to the energy system, demonstrating the technological feasibility of each of its components. Key words: nuclear fusion, energy, reactor, ITER","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"81 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166655","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}
IÑIGO CAREAGA AJA, ANDREA CASAS OCAMPO, EKAITZ ZULUETA GUERRERO
The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade. However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches. This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain. Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.
{"title":"OPPORTUNITIES OFFERED BY ARTIFICIAL INTELLIGENCE IN BATTERY RECYCLING","authors":"IÑIGO CAREAGA AJA, ANDREA CASAS OCAMPO, EKAITZ ZULUETA GUERRERO","doi":"10.6036/10980","DOIUrl":"https://doi.org/10.6036/10980","url":null,"abstract":"The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade. However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches. This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain. Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"83 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166817","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}
Guar gum is commonly utilized in the pharmaceutical, cosmetic, and food industries. However, its use as a foam material for insulation purposes in construction fields has not been extensively studied, especially with regards to machine learning. This study aimed to investigate the potential use of foams produced from biopolymers for insulation and to estimate their properties using two different regression analyses. The foams were produced using a simple and quick procedure involving a mixture of guar gum, cellulose, and boric acid in different proportions, and then dried in the oven. The results of the produced foams showed promising features such as low density, low thermal conductivity, and good mechanical properties, which are highly desirable in insulation materials. A regression model was developed to analyze the effects of the components used in the foam formulation and to provide an estimated method for future research. The regression model was able to accurately predict the results, with an R2 value of up to 0.99, allowing for more quantitative data to be obtained with fewer experimental results. Furthermore, it was found that guar gum had the most significant effect on the properties of the foams. Keywords: Foam, guar gum, thermal conductivity, regression, insulation
{"title":"INVESTIGATING THE FEASIBILITY OF GUAR GUM-BASED FOAMS FOR INSULATION APPLICATIONS USING REGRESSION ANALYSIS","authors":"Mehmet Emin ERGÜN, Halime Ergunb","doi":"10.6036/10832","DOIUrl":"https://doi.org/10.6036/10832","url":null,"abstract":"Guar gum is commonly utilized in the pharmaceutical, cosmetic, and food industries. However, its use as a foam material for insulation purposes in construction fields has not been extensively studied, especially with regards to machine learning. This study aimed to investigate the potential use of foams produced from biopolymers for insulation and to estimate their properties using two different regression analyses. The foams were produced using a simple and quick procedure involving a mixture of guar gum, cellulose, and boric acid in different proportions, and then dried in the oven. The results of the produced foams showed promising features such as low density, low thermal conductivity, and good mechanical properties, which are highly desirable in insulation materials. A regression model was developed to analyze the effects of the components used in the foam formulation and to provide an estimated method for future research. The regression model was able to accurately predict the results, with an R2 value of up to 0.99, allowing for more quantitative data to be obtained with fewer experimental results. Furthermore, it was found that guar gum had the most significant effect on the properties of the foams. Keywords: Foam, guar gum, thermal conductivity, regression, insulation","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217215","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 pitch angle of greenhouse tractors changes when operating on rough soil pavement. As a result, the feedback signal lags behind the tractor motion attitude signal, thereby affecting the real-time control of tilling depth. In this study, a pitch angle prediction model of greenhouse electric tractor was proposed based on extended Kalman filter (EKF) and time series analysis to improve the dynamic response speed of tilling depth regulation by providing predictive information for advance control. EKF was used to track the tilling depth of greenhouse electric tractor in real time, and an auto-regressive moving average model (ARMA) was established for the obtained time series data. ARMA (2, 1) was designed as the pitch angle prediction model of greenhouse electric tractors by constructing a simulation model. Inertia measurement unit (IMU) of tractor was used to construct the extended Kalman estimation model of the pitch angle. Actual vehicle tests were carried out under different working conditions. Results show that the estimated values obtained under two operating conditions have a high correlation with the measured values, with correlation coefficients(R) of 0.9504 and 0.9734, root mean square error (RMSE) of 0.2355 and 0.2173, and maximum absolute error (MAE) of 0.1929 and 0.1703, respectively. And ,the MAE and the RMSE of the predicted and measured values of ARMA (2,1) model approximately have the same value under the two conditions, with with the R of 0.9665 and 0.9755, the RMSE of 0.2002 and 0.1812, and the MAE of 0.1578 and 0.1387, respectively. The effectiveness of ARMA (2, 1) as the pitch angle estimation and prediction model of greenhouse electric tractors is verified. This study provides theoretical reference for designing the control law of tilling depth stability in subsequent greenhouse operation. Keywords: Time series, prediction, pitch angle,electric tractor
{"title":"PREDICTION MODEL OF PITCH ANGLE OF GREENHOUSE ELECTRIC TRACTORS BASED ON TIME SERIES ANALYSIS","authors":"Hangxu Yang, Jun Zhou, Zezhong Qi","doi":"10.6036/11052","DOIUrl":"https://doi.org/10.6036/11052","url":null,"abstract":"The pitch angle of greenhouse tractors changes when operating on rough soil pavement. As a result, the feedback signal lags behind the tractor motion attitude signal, thereby affecting the real-time control of tilling depth. In this study, a pitch angle prediction model of greenhouse electric tractor was proposed based on extended Kalman filter (EKF) and time series analysis to improve the dynamic response speed of tilling depth regulation by providing predictive information for advance control. EKF was used to track the tilling depth of greenhouse electric tractor in real time, and an auto-regressive moving average model (ARMA) was established for the obtained time series data. ARMA (2, 1) was designed as the pitch angle prediction model of greenhouse electric tractors by constructing a simulation model. Inertia measurement unit (IMU) of tractor was used to construct the extended Kalman estimation model of the pitch angle. Actual vehicle tests were carried out under different working conditions. Results show that the estimated values obtained under two operating conditions have a high correlation with the measured values, with correlation coefficients(R) of 0.9504 and 0.9734, root mean square error (RMSE) of 0.2355 and 0.2173, and maximum absolute error (MAE) of 0.1929 and 0.1703, respectively. And ,the MAE and the RMSE of the predicted and measured values of ARMA (2,1) model approximately have the same value under the two conditions, with with the R of 0.9665 and 0.9755, the RMSE of 0.2002 and 0.1812, and the MAE of 0.1578 and 0.1387, respectively. The effectiveness of ARMA (2, 1) as the pitch angle estimation and prediction model of greenhouse electric tractors is verified. This study provides theoretical reference for designing the control law of tilling depth stability in subsequent greenhouse operation. Keywords: Time series, prediction, pitch angle,electric tractor","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"80 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166666","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}
Franklin Salazar Logroño, SOFIA MARTINEZ GARCIA, ANGEL DE CASTRO MARTIN
The great development of the aviation industry in recent years has allowed to extend its field of application from the military to the civilian field. The use of UAVs to perform high-risk missions, as well as immediate action, allows the development of research in the area of UAVs. The manufacturing of a UAV for monitoring and video surveillance applications requires an adequate design and modeling of the system. One of the main characteristics for a stable flight of a UAV is its aerodynamic design, since this depends on the application for which it is built. This paper presents the aerodynamic design and modeling of the UAV, as well as its trajectory simulation and the construction of a functional UAV for strategic missions. The project was developed within a knowledge exchange agreement between the Ecuadorian Armed Forces (FAE) and the Technical University of Ambato (UTA). The analysis of the different airfoils allowed to determine that the S4083 airfoil, part of the 4-digit family of the NACA airfoil, is the most suitable for the proposed system, allowing to achieve average flight times of 3 hours, with the inclusion of a solar power source incorporated in the UAV wings.
{"title":"AERODYNAMIC DESIGN OF A LONG-RANGE UAV FOR STRATEGIC MONITORING MISSIONS","authors":"Franklin Salazar Logroño, SOFIA MARTINEZ GARCIA, ANGEL DE CASTRO MARTIN","doi":"10.6036/10813","DOIUrl":"https://doi.org/10.6036/10813","url":null,"abstract":"The great development of the aviation industry in recent years has allowed to extend its field of application from the military to the civilian field. The use of UAVs to perform high-risk missions, as well as immediate action, allows the development of research in the area of UAVs. The manufacturing of a UAV for monitoring and video surveillance applications requires an adequate design and modeling of the system. One of the main characteristics for a stable flight of a UAV is its aerodynamic design, since this depends on the application for which it is built. This paper presents the aerodynamic design and modeling of the UAV, as well as its trajectory simulation and the construction of a functional UAV for strategic missions. The project was developed within a knowledge exchange agreement between the Ecuadorian Armed Forces (FAE) and the Technical University of Ambato (UTA). The analysis of the different airfoils allowed to determine that the S4083 airfoil, part of the 4-digit family of the NACA airfoil, is the most suitable for the proposed system, allowing to achieve average flight times of 3 hours, with the inclusion of a solar power source incorporated in the UAV wings.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217813","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 building sector represents around one third of the energy related to the EU greenhouse gas (GHG) emissions, which make it a crucial sector for achieving the EU’s energy and environmental goals. Thus, to boost energy performance of buildings, the EU has established a legislative framework to foster the integration of renewable energy technologies in the buildings. In this sense, bearing in mind the needs of retrofit of the public buildings in Spain, and in particular in Catalunya, this paper proposes the optimization of a polygeneration system for the building TR5 of the Polytechnic University of Catalunya located in Terrassa. This is carried out through a Mixed Integer Linear Programing (MILP) model to optimize from the economic point of view the energy system under different energy prices scenarios. The results show the feasibility of the PV technology in all scenarios, whereas other technologies such as solar thermal collectors, energy storage, among others, were not feasible in any scenario. On the other hand, the optimal configuration changes according to the energy prices but also the environmental impact. In particular, higher natural gas prices leads to reduce the GHG emissions whereas higher electricity prices not necessarily. Keywords: Polygeneration systems; optimization; energy efficiency; buildings.
{"title":"OPTIMIZATION OF AN ENERGY POLYGENERATION SYSTEM FOR THE TR5 BUILDING AT THE POLYTECHNIC UNIVERSITY OF CATALONIA (UPC)-TERRASSA CAMPUS","authors":"EDWIN SAMIR PINTO, BEATRIZ AMANTE GARCIA","doi":"10.6036/10820","DOIUrl":"https://doi.org/10.6036/10820","url":null,"abstract":"The building sector represents around one third of the energy related to the EU greenhouse gas (GHG) emissions, which make it a crucial sector for achieving the EU’s energy and environmental goals. Thus, to boost energy performance of buildings, the EU has established a legislative framework to foster the integration of renewable energy technologies in the buildings. In this sense, bearing in mind the needs of retrofit of the public buildings in Spain, and in particular in Catalunya, this paper proposes the optimization of a polygeneration system for the building TR5 of the Polytechnic University of Catalunya located in Terrassa. This is carried out through a Mixed Integer Linear Programing (MILP) model to optimize from the economic point of view the energy system under different energy prices scenarios. The results show the feasibility of the PV technology in all scenarios, whereas other technologies such as solar thermal collectors, energy storage, among others, were not feasible in any scenario. On the other hand, the optimal configuration changes according to the energy prices but also the environmental impact. In particular, higher natural gas prices leads to reduce the GHG emissions whereas higher electricity prices not necessarily. Keywords: Polygeneration systems; optimization; energy efficiency; buildings.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"12 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166517","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}
JUAN ULLOA ROJAS, JOSE IGNACIO COLOMBO, JOSE WILCHES
In the last decades, numerous liquid storage tanks have been affected by strong earthquakes, the damage observed ranges from the partial collapse to the total collapse of the storage tanks. Elephant-foot buckling is one of the most common failures observed in these structures, which can provoke their collapse and complete loss of contents. While hydrostatic and hydrodynamic loads typically impact the seismic response of tanks, the soil type on which they are built plays an important role in influencing their performance during earthquakes. However, the soil-tank interaction has not been considered in the seismic fragility analyses of continuously supported tanks. This research aims to evaluate the seismic fragility of a continuously supported wine storage tank with a particular focus on elephant-foot buckling considering the soil-tank interaction. A specific soil condition and a typical wine storage tank are evaluated utilizing pushover-based seismic analysis and the Capacity Spectrum Method (CSM). 3D nonlinear Finite Element (FE) models are developed considering the tank, foundation, and soil. Seven ground motion records compatible with the soil type are considered. The seismic fragility is estimated using the FE models and the ground motion records. Both unanchored and anchored conditions are evaluated. The obtained results show that for the considered case study, the anchored condition shows better seismic performance when compared to the unanchored condition. Keywords: liquid storage tanks, wine storage tanks, buckling, finite element models
{"title":"INFLUENCE OF ANCHORING ON THE SEISMIC FRAGILITY OF BUCKLING IN LIQUID STORAGE TANKS CONSIDERING SOIL-TANK INTERACTION: A CASE STUDY FOR WINE STORAGE TANKS","authors":"JUAN ULLOA ROJAS, JOSE IGNACIO COLOMBO, JOSE WILCHES","doi":"10.6036/10978","DOIUrl":"https://doi.org/10.6036/10978","url":null,"abstract":"In the last decades, numerous liquid storage tanks have been affected by strong earthquakes, the damage observed ranges from the partial collapse to the total collapse of the storage tanks. Elephant-foot buckling is one of the most common failures observed in these structures, which can provoke their collapse and complete loss of contents. While hydrostatic and hydrodynamic loads typically impact the seismic response of tanks, the soil type on which they are built plays an important role in influencing their performance during earthquakes. However, the soil-tank interaction has not been considered in the seismic fragility analyses of continuously supported tanks. This research aims to evaluate the seismic fragility of a continuously supported wine storage tank with a particular focus on elephant-foot buckling considering the soil-tank interaction. A specific soil condition and a typical wine storage tank are evaluated utilizing pushover-based seismic analysis and the Capacity Spectrum Method (CSM). 3D nonlinear Finite Element (FE) models are developed considering the tank, foundation, and soil. Seven ground motion records compatible with the soil type are considered. The seismic fragility is estimated using the FE models and the ground motion records. Both unanchored and anchored conditions are evaluated. The obtained results show that for the considered case study, the anchored condition shows better seismic performance when compared to the unanchored condition. Keywords: liquid storage tanks, wine storage tanks, buckling, finite element models","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136103947","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}
DANIEL CAMPOS OLIVARES, Alejandro Carrasco Muñoz, MIRKO MAZZOLENI, ANTONIO FERRAMOSCA, AMALIA LUQUE SENDRA
Predictive maintenance (PdM) is a set of actions and techniques to early detect failures and defects on machines before they occur, and the usage of machine learning and deep learning techniques in predictive maintenance has increased during the last years. Even with this increase of the literature, there is still a gap concerning the application of such techniques for PdM in the industry, as there are no clear guidelines about which information to use for a PdM system, how to process the information, and what machine learning techniques should be used in order to obtain acceptable results. This scoping review is performed in order to observe the current status on the use of Machine Learning and Deep Learning in predictive maintenance in academia and provide answer to the questions related to these guidelines. For this purpose, a literature review of the last five years is carried out, using those articles that cover information about sources of information used for PdM, the treatment given to such data and the machine learning (ML) methods or techniques used. The Web of Science: Core Collection database is used as a source of information, specifically the Science Citation Index Expanded (SCIE). The review shows that there are different information sources used for machine learning and deep learning in PdM, depending on the origin of the data and the availability of it, and as well whether the data sets are private or public. Also, we can observe that data used for both training and making predictions does not only use traditional pre-processing techniques, but that about one fifth of the articles even propose new techniques in this field. Additionally, we compare a wide range of techniques and algorithms which are used in Deep Learning -being ANN the most used- and in Machine Learning, being SVM the most used algorithm, closely followed by Random Forest. Based on the results, we provide indications about how to apply ML for PdM in industry. Keywords: machine learning, predictive maintenance, artificial intelligence, deep learning, data processing, data collection
预测性维护(PdM)是一组用于在机器发生故障和缺陷之前早期检测故障和缺陷的操作和技术，机器学习和深度学习技术在预测性维护中的使用在过去几年中有所增加。即使有了文献的增加，关于这些技术在PdM行业中的应用仍然存在差距，因为对于PdM系统使用哪些信息，如何处理信息以及应该使用哪些机器学习技术以获得可接受的结果，没有明确的指导方针。进行范围审查是为了观察学术界在预测性维护中使用机器学习和深度学习的现状，并提供与这些指南相关的问题的答案。为此，对过去五年的文献进行综述，使用那些涵盖PdM使用的信息源信息的文章，对这些数据的处理以及所使用的机器学习(ML)方法或技术。Web of Science: Core Collection数据库被用作信息来源，特别是科学引文索引扩展(SCIE)。回顾表明，PdM中的机器学习和深度学习有不同的信息源，这取决于数据的来源和可用性，以及数据集是私有的还是公共的。此外，我们可以观察到用于训练和预测的数据不仅使用传统的预处理技术，而且大约五分之一的文章甚至提出了该领域的新技术。此外，我们比较了深度学习中使用的各种技术和算法——最常用的人工神经网络——和机器学习中使用最多的支持向量机算法，紧随其后的是随机森林。在此基础上，提出了机器学习在PdM工业中的应用。关键词:机器学习，预测性维护，人工智能，深度学习，数据处理，数据采集
{"title":"Screening of Machine Learning Techniques on Predictive Maintenance: a Scoping Review","authors":"DANIEL CAMPOS OLIVARES, Alejandro Carrasco Muñoz, MIRKO MAZZOLENI, ANTONIO FERRAMOSCA, AMALIA LUQUE SENDRA","doi":"10.6036/10950","DOIUrl":"https://doi.org/10.6036/10950","url":null,"abstract":"Predictive maintenance (PdM) is a set of actions and techniques to early detect failures and defects on machines before they occur, and the usage of machine learning and deep learning techniques in predictive maintenance has increased during the last years. Even with this increase of the literature, there is still a gap concerning the application of such techniques for PdM in the industry, as there are no clear guidelines about which information to use for a PdM system, how to process the information, and what machine learning techniques should be used in order to obtain acceptable results. This scoping review is performed in order to observe the current status on the use of Machine Learning and Deep Learning in predictive maintenance in academia and provide answer to the questions related to these guidelines. For this purpose, a literature review of the last five years is carried out, using those articles that cover information about sources of information used for PdM, the treatment given to such data and the machine learning (ML) methods or techniques used. The Web of Science: Core Collection database is used as a source of information, specifically the Science Citation Index Expanded (SCIE). The review shows that there are different information sources used for machine learning and deep learning in PdM, depending on the origin of the data and the availability of it, and as well whether the data sets are private or public. Also, we can observe that data used for both training and making predictions does not only use traditional pre-processing techniques, but that about one fifth of the articles even propose new techniques in this field. Additionally, we compare a wide range of techniques and algorithms which are used in Deep Learning -being ANN the most used- and in Machine Learning, being SVM the most used algorithm, closely followed by Random Forest. Based on the results, we provide indications about how to apply ML for PdM in industry. Keywords: machine learning, predictive maintenance, artificial intelligence, deep learning, data processing, data collection","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"8 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908100","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}
LEONARDO AGUIAR TRUJILLO, FRANCISCO MARQUEZ MONTESINO, BORIS ABEL RAMOS ROBAINA, YANET GUERRA REYES, JESUS ARAUZO PEREZ, ALBERTO GONZALO CALLEJO, JOSE LUIS SANCHEZ CEBRIAN, ADRIAN BLANCO MACHIN, DANIEL TRAVIESO PEDROSO, EINARA BLANCO MACHIN
ABSTRACT: The industry processing of the orange generates high volumes of solid waste. This waste has been used to complement animal feeding and biochemical processes, but the gasification process has not valued its energy use. Gasification studies were carried out with air in a catalytic fluidized bed (using dolomite and olivine as catalysts in a secondary reactor, also varying the temperature of the secondary reactor and the catalyst mass) of the solid waste of orange, and the results are compared with those obtained in the gasification with non-catalytic air. In the processes, we use a design of a complete factorial experiment of 2k, valuing the influence of the independent variables and their interactions in the answers, using the software Design-Expert® and a grade of the significance of 95 %. The results demonstrate the qualities of the solid waste of orange in the energy use through the gasification process for the treatment of these residuals, obtaining a gas of low heating value. The use of catalysts also diminishes the yield of tars obtained in the gasification process, making dolomite more active than olivine. The better results of fluidized bed catalytic gasification of RSNs, in terms of gas heating value, gas yield, and low tar yield, are obtained when the secondary reactor operates at a temperature of 800 ºC and using 60 g of dolomite as a catalyst. Keywords: Orange waste, catalytic gasification, fluidized bed, dolomite, olivine
{"title":"CATALYTIC GASIFICATION WITH DOLOMITE AND OLIVINE IN FLUIDIZED BED, OF SOLID ORANGE WASTE. COMPARISON WITH NON-CATALYTIC GASIFICATION","authors":"LEONARDO AGUIAR TRUJILLO, FRANCISCO MARQUEZ MONTESINO, BORIS ABEL RAMOS ROBAINA, YANET GUERRA REYES, JESUS ARAUZO PEREZ, ALBERTO GONZALO CALLEJO, JOSE LUIS SANCHEZ CEBRIAN, ADRIAN BLANCO MACHIN, DANIEL TRAVIESO PEDROSO, EINARA BLANCO MACHIN","doi":"10.6036/es10941","DOIUrl":"https://doi.org/10.6036/es10941","url":null,"abstract":"ABSTRACT: The industry processing of the orange generates high volumes of solid waste. This waste has been used to complement animal feeding and biochemical processes, but the gasification process has not valued its energy use. Gasification studies were carried out with air in a catalytic fluidized bed (using dolomite and olivine as catalysts in a secondary reactor, also varying the temperature of the secondary reactor and the catalyst mass) of the solid waste of orange, and the results are compared with those obtained in the gasification with non-catalytic air. In the processes, we use a design of a complete factorial experiment of 2k, valuing the influence of the independent variables and their interactions in the answers, using the software Design-Expert® and a grade of the significance of 95 %. The results demonstrate the qualities of the solid waste of orange in the energy use through the gasification process for the treatment of these residuals, obtaining a gas of low heating value. The use of catalysts also diminishes the yield of tars obtained in the gasification process, making dolomite more active than olivine. The better results of fluidized bed catalytic gasification of RSNs, in terms of gas heating value, gas yield, and low tar yield, are obtained when the secondary reactor operates at a temperature of 800 ºC and using 60 g of dolomite as a catalyst. Keywords: Orange waste, catalytic gasification, fluidized bed, dolomite, olivine","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135043940","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}
In this work the experimental results of the dynamics of the two-phase oil-water flow patterns and the pressure gradients due to friction that they produce when conducting them in a vertical ascending pipe are shown. For the study, an experimental facility and two types of injection nozzles were built, constructed and characterized. The selected fluids were oil (viscosity 90 cP, density 885 kg/m3 with 28.3 API) and water. The measurements were made in a range of superficial speeds from 0 to 0.257 m/s for oil and from 0 to 0.684 for water. The experimentation was carried out using the two nozzles and in accordance with a test matrix that has as parameters the superficial speed of the oil (USO) and the superficial speed of the water (USW) for which a fixed value of the USW was taken and it varied the USO, although it was also worked in reverse. From the experimental results, the effect of the nozzles to induce the group of flow patterns and their respective pressure gradient is shown, which reaches its lowest value when conducting the oil in the annular flow scheme. The numerical results showed that there is a notable energy saving, since the pressure loss due to friction is up to 5 times lower when conducting the same amount of oil in the annular flow pattern. Key Words: Experimental installation, oil-water mixture, injection nozzle, flow patterns, annular flow, pressure gradient.
{"title":"EXPERIMENTAL STUDY OF FLOW PATTERNS AND PRESSURE LOSSES IN VERTICAL FLOWS OF OIL-WATER MIXTURES","authors":"Irving Néstor Sierra Sánchez, FLORENCIO SANCHEZ SILVA, IGNACIO CARVAJAL MARISCAL, MONICA TOLEDO GARCIA","doi":"10.6036/10839","DOIUrl":"https://doi.org/10.6036/10839","url":null,"abstract":"In this work the experimental results of the dynamics of the two-phase oil-water flow patterns and the pressure gradients due to friction that they produce when conducting them in a vertical ascending pipe are shown. For the study, an experimental facility and two types of injection nozzles were built, constructed and characterized. The selected fluids were oil (viscosity 90 cP, density 885 kg/m3 with 28.3 API) and water. The measurements were made in a range of superficial speeds from 0 to 0.257 m/s for oil and from 0 to 0.684 for water. The experimentation was carried out using the two nozzles and in accordance with a test matrix that has as parameters the superficial speed of the oil (USO) and the superficial speed of the water (USW) for which a fixed value of the USW was taken and it varied the USO, although it was also worked in reverse. From the experimental results, the effect of the nozzles to induce the group of flow patterns and their respective pressure gradient is shown, which reaches its lowest value when conducting the oil in the annular flow scheme. The numerical results showed that there is a notable energy saving, since the pressure loss due to friction is up to 5 times lower when conducting the same amount of oil in the annular flow pattern. Key Words: Experimental installation, oil-water mixture, injection nozzle, flow patterns, annular flow, pressure gradient.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135878085","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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