Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-065
{"title":"Hydrothermal Synthesis and Crystal Structure of a Novel Phosphate: CdMn4(HPO4)2(PO4)2.4H2O","authors":"","doi":"10.17756/nwj.2023-s2-065","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-065","url":null,"abstract":"","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135297528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-080
Pavement distress is the main element impacting the stability of roads and the comfort of drivers. It is crucial to identify and fix road damage promptly to prevent greater harm and decrease expenses associated with rehabilitation. Pave-ment deterioration identification has been carried out through manual means, resulting in significant time and labor requirements. Consequently, an automated method for detecting cracks is necessary to streamline this procedure. Multiple approaches exist for the automated identification of deterioration, ranging from image processing to the implementation of deep learning techniques. The process of identifying deterioration using image processing techniques often involves edge detection and threshold segmentation methods, which primarily emphasize feature extraction but remain susceptible to variations in image texture. Traditional machine learning techniques have demonstrated favorable outcomes, but they lack dependence on the features that are extracted. The application of deep learning techniques has yielded successful results in the field of distress detection, surpassing the performance of traditional methods. This research paper introduces an innovative algorithm for the identification and categorization of pavement deterioration, formulated as a multi-label classification task. In this study, images of concrete pavements were utilized as the training and test data for the models. Various types of pavement deterioration are identified and categorized, including longitudinal cracks, transversal cracks, oblique cracks, and no cracks. Moreover, in order to attain optimal performance for our algorithm, we fine-tune the hyper-parameters that compose the deep convolutional neural network model through the utilization of the grid search technique. The grid search explores every conceivable combination and selects the one that attains the greatest accuracy. Once the optimization process is finished, the effectiveness of the enhanced model is assessed using diverse evaluation metrics, including accuracy, precision, recall, and F1 score.
{"title":"Concrete Pavement Crack Detection and Classification Using Deep Convolutional Neural Network with Grid Search Optimization","authors":"","doi":"10.17756/nwj.2023-s2-080","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-080","url":null,"abstract":"Pavement distress is the main element impacting the stability of roads and the comfort of drivers. It is crucial to identify and fix road damage promptly to prevent greater harm and decrease expenses associated with rehabilitation. Pave-ment deterioration identification has been carried out through manual means, resulting in significant time and labor requirements. Consequently, an automated method for detecting cracks is necessary to streamline this procedure. Multiple approaches exist for the automated identification of deterioration, ranging from image processing to the implementation of deep learning techniques. The process of identifying deterioration using image processing techniques often involves edge detection and threshold segmentation methods, which primarily emphasize feature extraction but remain susceptible to variations in image texture. Traditional machine learning techniques have demonstrated favorable outcomes, but they lack dependence on the features that are extracted. The application of deep learning techniques has yielded successful results in the field of distress detection, surpassing the performance of traditional methods. This research paper introduces an innovative algorithm for the identification and categorization of pavement deterioration, formulated as a multi-label classification task. In this study, images of concrete pavements were utilized as the training and test data for the models. Various types of pavement deterioration are identified and categorized, including longitudinal cracks, transversal cracks, oblique cracks, and no cracks. Moreover, in order to attain optimal performance for our algorithm, we fine-tune the hyper-parameters that compose the deep convolutional neural network model through the utilization of the grid search technique. The grid search explores every conceivable combination and selects the one that attains the greatest accuracy. Once the optimization process is finished, the effectiveness of the enhanced model is assessed using diverse evaluation metrics, including accuracy, precision, recall, and F1 score.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135297676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-073
Membrane fouling is a major challenge in membrane processes. The causes are often specific and depend on the constituents of the feed water, the interaction between feed water quality, the pretreatment process, and the used chemicals. This study aims to investigate the effect of pre-treatment on membrane fouling. Various studies were carried out to identify the reasons for membrane fouling: membrane autopsy and pretreatment optimization. The results of the membrane autopsy by scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDS) revealed that the main causes of membrane fouling are: calcium carbonate (CaCO 3 ; 38.70%), aluminum oxide (Al 2 O 3 ; 17.42%), and barium sulfate (Ba(SO 4 ) 2 ; 15.23%). The results of the pretreatment optimization allowed to significantly reduce the residual aluminum concentration and the clogging index after the 5 µm cartridge filters. Likewise, it allows to decrease the clogging rate of reverse osmosis membranes.
{"title":"Efficiency in Optimizing the Pre-treatment Process in Water Desalination","authors":"","doi":"10.17756/nwj.2023-s2-073","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-073","url":null,"abstract":"Membrane fouling is a major challenge in membrane processes. The causes are often specific and depend on the constituents of the feed water, the interaction between feed water quality, the pretreatment process, and the used chemicals. This study aims to investigate the effect of pre-treatment on membrane fouling. Various studies were carried out to identify the reasons for membrane fouling: membrane autopsy and pretreatment optimization. The results of the membrane autopsy by scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDS) revealed that the main causes of membrane fouling are: calcium carbonate (CaCO 3 ; 38.70%), aluminum oxide (Al 2 O 3 ; 17.42%), and barium sulfate (Ba(SO 4 ) 2 ; 15.23%). The results of the pretreatment optimization allowed to significantly reduce the residual aluminum concentration and the clogging index after the 5 µm cartridge filters. Likewise, it allows to decrease the clogging rate of reverse osmosis membranes.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135297678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-069
Water pollution is a critical global issue that poses significant threats to eco-systems and human health. The contamination of water sources by various pollutants, such as heavy metals, chemicals, and organic compounds, has adverse impacts on the environment and public well-being. To address this challenge, adsorption has emerged as a promising solution. Utilizing adsorbent materials like hydroxyapatite (HAp), contaminants can be effectively removed from water through the adsorption process. HAp, derived from sustainable sources, serves as an eco-friendly adsorbent. Porous hydroxyapatite (p-HAp) was prepared us-ing the neutralization method of calcium hydroxide (Ca(OH) 2 ) and ammonium dihydrogen phosphate (NH 4 H 2 PO 4 ). p-HAp was characterized by using different methods such as BET (Brunauer-Emmett-Teller), FTIR (Fourier transform infrared spectroscopy), and XRD (X-ray diffraction). The characterization of p-HAp by FTIR and XRD showed that the synthetic HAp has an apatite phase which is essential for the adsorption of heavy metals. The BET method is used for measuring the specific surface area of p-HAp. The adsorption process was studied using optimization by Design-Expert 11 software, with a quadratic model.
{"title":"Optimization of Copper Adsorption Process on Synthesized Porous Hydroxyapatite","authors":"","doi":"10.17756/nwj.2023-s2-069","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-069","url":null,"abstract":"Water pollution is a critical global issue that poses significant threats to eco-systems and human health. The contamination of water sources by various pollutants, such as heavy metals, chemicals, and organic compounds, has adverse impacts on the environment and public well-being. To address this challenge, adsorption has emerged as a promising solution. Utilizing adsorbent materials like hydroxyapatite (HAp), contaminants can be effectively removed from water through the adsorption process. HAp, derived from sustainable sources, serves as an eco-friendly adsorbent. Porous hydroxyapatite (p-HAp) was prepared us-ing the neutralization method of calcium hydroxide (Ca(OH) 2 ) and ammonium dihydrogen phosphate (NH 4 H 2 PO 4 ). p-HAp was characterized by using different methods such as BET (Brunauer-Emmett-Teller), FTIR (Fourier transform infrared spectroscopy), and XRD (X-ray diffraction). The characterization of p-HAp by FTIR and XRD showed that the synthetic HAp has an apatite phase which is essential for the adsorption of heavy metals. The BET method is used for measuring the specific surface area of p-HAp. The adsorption process was studied using optimization by Design-Expert 11 software, with a quadratic model.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-082
The circular economy in the civil and construction engineering sectors is gaining momentum globally. The inadequate waste management system, especially in emerging nations, is quite concerning. Various waste sources such as construction and demolition (C&D), industrial wastes as well as agricultural wastes such as cassava peel, rice husk, and coconut fibre have been utilized in developing construction products. This study adopts the UK (United Kingdom) and Nigeria as two cases with critical analyses of the status quo and recommendations for promoting circularity. The existing studies on the circular use of waste construction products were comprehensively reviewed by mapping them against the Technology Readiness Level (TRL). The study addressed three research questions: (1) the existing locally available wastes used in civil and construction industries in the two studied countries, (2) the effects of these wastes on the properties of new construction products, and (3) visions to enhance circular use of wastes on civil and construction engineering practices. It is found that both countries have abundant industrial, agricultural, and demolition wastes that are potential materials for circularity in construction. While the TRL of utilizing these wastes is at an advanced stage in the UK, there is still a need for more concerted efforts to bring those wastes in Nigeria to a higher TRL. This study contributes to the existing body of knowledge by mapping the three aforementioned questions between the two studied countries, shedding light on continuous work in enhancing circular practices across the global civil and construction sectors.
{"title":"Comparative Analyses of Circularity Practices in Civil and Construction Engineering Between UK and Nigeria","authors":"","doi":"10.17756/nwj.2023-s2-082","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-082","url":null,"abstract":"The circular economy in the civil and construction engineering sectors is gaining momentum globally. The inadequate waste management system, especially in emerging nations, is quite concerning. Various waste sources such as construction and demolition (C&D), industrial wastes as well as agricultural wastes such as cassava peel, rice husk, and coconut fibre have been utilized in developing construction products. This study adopts the UK (United Kingdom) and Nigeria as two cases with critical analyses of the status quo and recommendations for promoting circularity. The existing studies on the circular use of waste construction products were comprehensively reviewed by mapping them against the Technology Readiness Level (TRL). The study addressed three research questions: (1) the existing locally available wastes used in civil and construction industries in the two studied countries, (2) the effects of these wastes on the properties of new construction products, and (3) visions to enhance circular use of wastes on civil and construction engineering practices. It is found that both countries have abundant industrial, agricultural, and demolition wastes that are potential materials for circularity in construction. While the TRL of utilizing these wastes is at an advanced stage in the UK, there is still a need for more concerted efforts to bring those wastes in Nigeria to a higher TRL. This study contributes to the existing body of knowledge by mapping the three aforementioned questions between the two studied countries, shedding light on continuous work in enhancing circular practices across the global civil and construction sectors.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135297706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.17756/nwj.2023-s2-078
The aim of this work is to develop models that reproduce highly precise I-V (Current-voltage) curves of photovoltaic (PV) panels, regardless of the temperature and sunlight conditions, using an experimental database installed at the PV PARK of Benguerir city, that allow the record an up to date current-voltage characteristics (I-V) of the PV. This paper presents three modeling approaches that simulate the PV arrays, two are classic models determined by the electrical behavior of the PV cell, while the last is based on experimental modeling us-ing the LUT (Look up tables) arrays and shows the performances results of the current-voltage characteristic obtained by the modeling approaches. To estimate the experimental parameters, we used the robust optimization algorithm Lev-enberg-Marquardt system, and a model based on the adaptive inference system ANFIS (Neuro-fuzzy adaptive inference systems) is developed to solve the problem of estimating of the experimental voltages V oc and V mp . We used MATLAB/ SIMULINK to build the mathematical model, and the experimental database is used to validate these models under Moroccan meteorological conditions.
{"title":"Extraction of Monocrystalline Silicon Photovoltaic Panel Parameters Based on Experimental Data","authors":"","doi":"10.17756/nwj.2023-s2-078","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-078","url":null,"abstract":"The aim of this work is to develop models that reproduce highly precise I-V (Current-voltage) curves of photovoltaic (PV) panels, regardless of the temperature and sunlight conditions, using an experimental database installed at the PV PARK of Benguerir city, that allow the record an up to date current-voltage characteristics (I-V) of the PV. This paper presents three modeling approaches that simulate the PV arrays, two are classic models determined by the electrical behavior of the PV cell, while the last is based on experimental modeling us-ing the LUT (Look up tables) arrays and shows the performances results of the current-voltage characteristic obtained by the modeling approaches. To estimate the experimental parameters, we used the robust optimization algorithm Lev-enberg-Marquardt system, and a model based on the adaptive inference system ANFIS (Neuro-fuzzy adaptive inference systems) is developed to solve the problem of estimating of the experimental voltages V oc and V mp . We used MATLAB/ SIMULINK to build the mathematical model, and the experimental database is used to validate these models under Moroccan meteorological conditions.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135297711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Study of machining characteristics is an important phenomenon of any material; the confirmation of good surface finish can justify the materials application and its usage conditions. The ultimate aim of the automobile industry is providing good mileage with highest safety. In this virtue, the material selected by light weight is very strong. This can be achieved by using the aluminum alloys materials and machined by Electrical Discharge Machines (EDM). In this research work the aluminum alloy 6063 is used as base material and 9 weight percentage of nano-SiC (Silicon carbide) powder is used as a reinforcement with 3 weight percentage of graphite (Gr) is used for the improvement of the aluminum hybrid composite material which is fabricated by using stir casting method. The mechanical properties and microstructures were studied; the machinability characteristics were studied in the EDM and optimized the process parameters by using Taguchi technique with usage of L9 orthogonal array.
{"title":"Parameter Optimization for Electrical Discharge Machining of Stir Casted AA6063/Nano-SiC with Graphite Hybrid Composite Materials by Using Response Surface Methodology","authors":"Baradeswaran Annasamy, Pugazhenthi Rajagopal, Vamsi Krishna, Mamidi, Baskar Sanjeevi, Ajith Arul, Daniel Sel-sam Chandradoss","doi":"10.17756/nwj.2023-s3-012","DOIUrl":"https://doi.org/10.17756/nwj.2023-s3-012","url":null,"abstract":"Study of machining characteristics is an important phenomenon of any material; the confirmation of good surface finish can justify the materials application and its usage conditions. The ultimate aim of the automobile industry is providing good mileage with highest safety. In this virtue, the material selected by light weight is very strong. This can be achieved by using the aluminum alloys materials and machined by Electrical Discharge Machines (EDM). In this research work the aluminum alloy 6063 is used as base material and 9 weight percentage of nano-SiC (Silicon carbide) powder is used as a reinforcement with 3 weight percentage of graphite (Gr) is used for the improvement of the aluminum hybrid composite material which is fabricated by using stir casting method. The mechanical properties and microstructures were studied; the machinability characteristics were studied in the EDM and optimized the process parameters by using Taguchi technique with usage of L9 orthogonal array.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139334272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.17756/nwj.2023-s2-040
The increasing urbanization of cities requires the implementation of various subterranean infrastructures, such as tunnels, metro stations, and deep excava-tions. The construction of retaining structures to support these works can potentially cause structural disturbances to adjacent buildings and structures. Therefore, predicting and controlling ground displacements is crucial. However, estimating these displacements accurately remains a challenging task. This study focuses on a 2D finite element analysis to assess the impact of deep excavations on adjacent structures using two elastoplastic behavior models, the Hardening Soil (HS) model and the Hardening Soil Small (HSS) model. The comparison of the two models and measured values shows that the HSS models provide more accurate predictions of ground surface movements induced by deep excavations. The advanced constitutive model that accounts for small strain characteristics (HSS) outperforms the basic soil constitutive model (HS) in predicting the settlement and displacement of the excavation screen. The use of HSS model can lead to better design and construction practices in deep excavation projects, reducing the risk of damage to surrounding structures and improving the security of the site.
{"title":"Comparative Analysis of Hardening Soil Models and Field Measurements for Deep Excavation: A Numerical Study","authors":"","doi":"10.17756/nwj.2023-s2-040","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-040","url":null,"abstract":"The increasing urbanization of cities requires the implementation of various subterranean infrastructures, such as tunnels, metro stations, and deep excava-tions. The construction of retaining structures to support these works can potentially cause structural disturbances to adjacent buildings and structures. Therefore, predicting and controlling ground displacements is crucial. However, estimating these displacements accurately remains a challenging task. This study focuses on a 2D finite element analysis to assess the impact of deep excavations on adjacent structures using two elastoplastic behavior models, the Hardening Soil (HS) model and the Hardening Soil Small (HSS) model. The comparison of the two models and measured values shows that the HSS models provide more accurate predictions of ground surface movements induced by deep excavations. The advanced constitutive model that accounts for small strain characteristics (HSS) outperforms the basic soil constitutive model (HS) in predicting the settlement and displacement of the excavation screen. The use of HSS model can lead to better design and construction practices in deep excavation projects, reducing the risk of damage to surrounding structures and improving the security of the site.","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135470915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.17756/nwj.2023-s2-038
{"title":"Experimental Evaluation of the Compressive and Shear Behavior of Unstabilized Rammed Earth","authors":"","doi":"10.17756/nwj.2023-s2-038","DOIUrl":"https://doi.org/10.17756/nwj.2023-s2-038","url":null,"abstract":"","PeriodicalId":36802,"journal":{"name":"NanoWorld Journal","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135470922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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