Pub Date : 2021-01-01DOI: 10.29027/IJIRASE.V4.I7.2021.807-810
Ömer Seçgin
- One of the main purposes of machining is to minimize the surface roughness of the workpiece. In this study, the hole turning operation was applied to AL7075 alloy. First, the parts were drilled on a CNC lathe with an HSS drill. Then the holes were turned. The effects of turning parameters on surface roughness were determined by Signal/Noise analysis. As a result of the study, it has been determined that the most important parameter for surface roughness is the cutting speed. It has also been found that the use of a small amount of cutting depth gives a better surface roughness.
{"title":"Surface Roughness Optimization of AL 7075 Aluminum Alloy in Hole Turning Process","authors":"Ömer Seçgin","doi":"10.29027/IJIRASE.V4.I7.2021.807-810","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I7.2021.807-810","url":null,"abstract":"- One of the main purposes of machining is to minimize the surface roughness of the workpiece. In this study, the hole turning operation was applied to AL7075 alloy. First, the parts were drilled on a CNC lathe with an HSS drill. Then the holes were turned. The effects of turning parameters on surface roughness were determined by Signal/Noise analysis. As a result of the study, it has been determined that the most important parameter for surface roughness is the cutting speed. It has also been found that the use of a small amount of cutting depth gives a better surface roughness.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128607493","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 : 2020-11-01DOI: 10.29027/IJIRASE.V4.I5.2020.774-784
Seada Hussen, K. Ibrahim
- The distribution system reliability assessment deals with availability and quality of power supply at each customer service entrance. This paper focuses the assessment of power distribution reliability of Addis Ababa city which is connected from Cotebie distribution substation and the possibility of using smart reclosers and disconnectors to mitigate the urgent and pressing power interruption problems. Depending of the assessment result Cotebie distribution substation has reliability indices such as average frequency of interruption is 133.37 interruptions per year per customer and the average interruption duration is 187.31 hours per year per customer. This value shows the substation has greater reliability problems and the substation does not meet the requirements set by the regulatory body that is Ethiopian Electric Authority (EEA). In this paper, the reliability is improved in to 22.27 interruptions per year per customer average frequency of interruption and the average interruption duration is 31.274 hours per year per customer. It can also improve above this value depending of the segment and recloser number. The designed system is simulated using WindMil software that is used to analyze the reliability of the overall system. The simulation of the designed model shows that the application of smart reclosers and disconnector coordination can improve the reliability from 50% up to 83.3%.
{"title":"Assessment of Distribution System Reliability and Possible Mitigation by Using Reclosers and Disconnectors: The Case of Cotobie Distribution Station","authors":"Seada Hussen, K. Ibrahim","doi":"10.29027/IJIRASE.V4.I5.2020.774-784","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I5.2020.774-784","url":null,"abstract":"- The distribution system reliability assessment deals with availability and quality of power supply at each customer service entrance. This paper focuses the assessment of power distribution reliability of Addis Ababa city which is connected from Cotebie distribution substation and the possibility of using smart reclosers and disconnectors to mitigate the urgent and pressing power interruption problems. Depending of the assessment result Cotebie distribution substation has reliability indices such as average frequency of interruption is 133.37 interruptions per year per customer and the average interruption duration is 187.31 hours per year per customer. This value shows the substation has greater reliability problems and the substation does not meet the requirements set by the regulatory body that is Ethiopian Electric Authority (EEA). In this paper, the reliability is improved in to 22.27 interruptions per year per customer average frequency of interruption and the average interruption duration is 31.274 hours per year per customer. It can also improve above this value depending of the segment and recloser number. The designed system is simulated using WindMil software that is used to analyze the reliability of the overall system. The simulation of the designed model shows that the application of smart reclosers and disconnector coordination can improve the reliability from 50% up to 83.3%.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116812120","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 : 2020-10-01DOI: 10.29027/IJIRASE.V4.I4.2020.715-721
Anurag Sinha, Atul Kumar
In recent years the product quality has been one of the crucial parts for every single industry. The conventional methods for assessing the product quality are very time consuming and also not having the optimal result however with the resultant in dynamic Technology movement. We have the concepts of machine learning and data science through this technique it’s become more efficient to assess or to predict any kind of thing efficiently. In this paper, we have explored several machine learning techniques for evaluating wine quality based on different metrics and properties related to wine quality. In this paper, we have also used several machine learning algorithms to rank the quality of wines and investigate why people make the wine taste more interesting. We have selected the features using the most popular machine learning techniques. We used different types of datasets for this particular study. Keywords— Data science, machine learning, wine dataset, Logistic Regression, Stochastic gradient descent, Support Vector Classifier, Random Forest
{"title":"Wine Quality and Taste Classification Using Machine Learning Model","authors":"Anurag Sinha, Atul Kumar","doi":"10.29027/IJIRASE.V4.I4.2020.715-721","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I4.2020.715-721","url":null,"abstract":"In recent years the product quality has been one of the crucial parts for every single industry. The conventional methods for assessing the product quality are very time consuming and also not having the optimal result however with the resultant in dynamic Technology movement. We have the concepts of machine learning and data science through this technique it’s become more efficient to assess or to predict any kind of thing efficiently. In this paper, we have explored several machine learning techniques for evaluating wine quality based on different metrics and properties related to wine quality. In this paper, we have also used several machine learning algorithms to rank the quality of wines and investigate why people make the wine taste more interesting. We have selected the features using the most popular machine learning techniques. We used different types of datasets for this particular study. Keywords— Data science, machine learning, wine dataset, Logistic Regression, Stochastic gradient descent, Support Vector Classifier, Random Forest","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122834077","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 : 2020-09-30DOI: 10.35940/ijrte.c4354.099320
K. Kumar, G. Chandhini, B. Chithra, Kiruthikadevi P Bhagyasasi
Underground drainage monitoring system plays an important role in keeping the cities clean and healthy. Compared to other countries, India consists of highest number of sewage workers. Exposure of sewage workers to poisonous gases like hydrogen sulphide, sulphur dioxide, carbon monoxide, methane, ammonia, nitrogen oxide increases the death of the sewage workers. The main aim of this project is to design a network system which helps in monitoring poisonous gases present in sewage. Whenever the gas level crosses the threshold value, the information with different gas ppm values is displayed in the smart phone through the app. It also indicates whether it is safe for the manual scavengers to work in the environment or not.
{"title":"IoT BASED UNDERGROUND DRAINAGE MONITORING SYSTEM","authors":"K. Kumar, G. Chandhini, B. Chithra, Kiruthikadevi P Bhagyasasi","doi":"10.35940/ijrte.c4354.099320","DOIUrl":"https://doi.org/10.35940/ijrte.c4354.099320","url":null,"abstract":"Underground drainage monitoring system plays an\u0000important role in keeping the cities clean and healthy. Compared\u0000to other countries, India consists of highest number of sewage\u0000workers. Exposure of sewage workers to poisonous gases like\u0000hydrogen sulphide, sulphur dioxide, carbon monoxide, methane,\u0000ammonia, nitrogen oxide increases the death of the sewage\u0000workers. The main aim of this project is to design a network\u0000system which helps in monitoring poisonous gases present in\u0000sewage. Whenever the gas level crosses the threshold value, the\u0000information with different gas ppm values is displayed in the\u0000smart phone through the app. It also indicates whether it is safe\u0000for the manual scavengers to work in the environment or not.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120821437","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 : 2020-09-01DOI: 10.29027/IJIRASE.V4.I3.2020.669-674
A. Yadav, Ramendra Kumar Bajpa
— In the present scenario, it is vital for any organization, especially the financial organizations, to understand customers and their financial dealings better. KYC is a process to verify identity and related details of corresponding customers. The current KYC mechanism has a severe concern in financial institutions as it requires separate ledger for the separate financial organizations. Every institution has its KYC process, which sometimes may include third-party, which may cause increased maintenance cost, time and redundancy. There is considerable wastage of costs in the form of opportunity cost, maintenance cost, customer verification cost and many more of around $27 million according to an economic survey. The current KYC process is very time-consuming, and it decreases the user experience. We have proposed an enhanced KYC system using blockchain technology to improve the existing KYC system. An inherent feature of the DLT is used to remove the third-party involvement, and smart contracts are used to build our logic in the mobility of the data. Blockchain technology has various types of cryptographic security which provide a safer place to transact over an unsecured channel. Using the facility of DLT, cryptography and consensus mechanism of blockchain, the proposed model of KYC process can optimize storing, updating, sharing of data and accessing operations along with enhanced security, transparency and privacy. It also enhances customer ownership and improves customer experience. It not only reduces the time duration and document update problem but also saves opportunity cost, aggregation, cost, maintenance cost and many more costs, which can affect the performance of any organization.
{"title":"KYC Optimization using Blockchain Smart Contract Technology","authors":"A. Yadav, Ramendra Kumar Bajpa","doi":"10.29027/IJIRASE.V4.I3.2020.669-674","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I3.2020.669-674","url":null,"abstract":"— In the present scenario, it is vital for any organization, especially the financial organizations, to understand customers and their financial dealings better. KYC is a process to verify identity and related details of corresponding customers. The current KYC mechanism has a severe concern in financial institutions as it requires separate ledger for the separate financial organizations. Every institution has its KYC process, which sometimes may include third-party, which may cause increased maintenance cost, time and redundancy. There is considerable wastage of costs in the form of opportunity cost, maintenance cost, customer verification cost and many more of around $27 million according to an economic survey. The current KYC process is very time-consuming, and it decreases the user experience. We have proposed an enhanced KYC system using blockchain technology to improve the existing KYC system. An inherent feature of the DLT is used to remove the third-party involvement, and smart contracts are used to build our logic in the mobility of the data. Blockchain technology has various types of cryptographic security which provide a safer place to transact over an unsecured channel. Using the facility of DLT, cryptography and consensus mechanism of blockchain, the proposed model of KYC process can optimize storing, updating, sharing of data and accessing operations along with enhanced security, transparency and privacy. It also enhances customer ownership and improves customer experience. It not only reduces the time duration and document update problem but also saves opportunity cost, aggregation, cost, maintenance cost and many more costs, which can affect the performance of any organization.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131811715","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 : 2020-08-01DOI: 10.29027/IJIRASE.V4.I2.2020.629-632
K. Samruddhi, R. A. Kumar
: Predicting the price of used cars is one of the significant and interesting areas of analysis. As an increased demand in the second-hand car market, the business for both buyers and sellers has increased. For reliable and accurate prediction it requires expert knowledge about the field because of the price of the cars dependent on many important factors. This paper proposed a supervised machine learning model using KNN (K Nearest Neighbor) regression algorithm to analyze the price of used cars. We trained our model with data of used cars which is collected from the Kaggle website. Through this experiment, the data was examined with different trained and test ratios. As a result, the accuracy of the proposed model is around 85% and is fitted as the optimized model.
{"title":"Used Car Price Prediction using K-Nearest Neighbor Based Model","authors":"K. Samruddhi, R. A. Kumar","doi":"10.29027/IJIRASE.V4.I2.2020.629-632","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I2.2020.629-632","url":null,"abstract":": Predicting the price of used cars is one of the significant and interesting areas of analysis. As an increased demand in the second-hand car market, the business for both buyers and sellers has increased. For reliable and accurate prediction it requires expert knowledge about the field because of the price of the cars dependent on many important factors. This paper proposed a supervised machine learning model using KNN (K Nearest Neighbor) regression algorithm to analyze the price of used cars. We trained our model with data of used cars which is collected from the Kaggle website. Through this experiment, the data was examined with different trained and test ratios. As a result, the accuracy of the proposed model is around 85% and is fitted as the optimized model.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130321301","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 : 2020-08-01DOI: 10.29027/IJIRASE.V4.I2.2020.622-628
V. B, K. Arumugam, M. Vijayakumar, Akila R
: Concrete is the most widely used building material. In worldwide the high rise buildings are constructed by using high strength concrete mode only. Growing demand for construction materials necessitated the usage of alternative materials in the production of conventional concrete. Now a day’s fine aggregate source is reduced due to high consumption, so some material is needed to replacing of sand. The objective of this work is to study the strength and durability properties of concrete. Here M 70 grade concrete used and concrete containing copper slag as partial replacement of fine aggregate and mineral admixture as partial replacement of cement in the concrete mix design. Copper slag content has been 40% as a replacement of fine aggregate and silica fume 5%,10%,15% & 20% and GGBS 5%,10%,15% & 20% as a replacement of cement respectively .This research paper study on strength test& Durability test. The test results show 40% replacement of fine aggregate as copper slag gives them more strength. And Silica fume & GGBS as partial replacement of cement (up to 15%). From the results, it was observed that the use of copper slag and mineral admixture in concrete has shown a considerable increase in strength and reduction of the cost when compared with normal concrete.
{"title":"Experimental Study on Strength and Durability Properties of High Strength Concrete Using Mineral Admixtures and Copper Slag","authors":"V. B, K. Arumugam, M. Vijayakumar, Akila R","doi":"10.29027/IJIRASE.V4.I2.2020.622-628","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I2.2020.622-628","url":null,"abstract":": Concrete is the most widely used building material. In worldwide the high rise buildings are constructed by using high strength concrete mode only. Growing demand for construction materials necessitated the usage of alternative materials in the production of conventional concrete. Now a day’s fine aggregate source is reduced due to high consumption, so some material is needed to replacing of sand. The objective of this work is to study the strength and durability properties of concrete. Here M 70 grade concrete used and concrete containing copper slag as partial replacement of fine aggregate and mineral admixture as partial replacement of cement in the concrete mix design. Copper slag content has been 40% as a replacement of fine aggregate and silica fume 5%,10%,15% & 20% and GGBS 5%,10%,15% & 20% as a replacement of cement respectively .This research paper study on strength test& Durability test. The test results show 40% replacement of fine aggregate as copper slag gives them more strength. And Silica fume & GGBS as partial replacement of cement (up to 15%). From the results, it was observed that the use of copper slag and mineral admixture in concrete has shown a considerable increase in strength and reduction of the cost when compared with normal concrete.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133958247","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 : 2020-08-01DOI: 10.29027/IJIRASE.V4.I2.2020.612-616
B. Vivekananthan, R. Nithya, B. Divya
— Brain Computer Interface ( BCI) is a computerized system that acquires brain signals, extracts and classifies features during different mental activities, and converts them into correct control signals, and transfers them to external devices. BCI helps people with motor disabilities. Real-time application of a BCI system needs an efficient classification of motor tasks. Motor Imagery task identification based on EEG signals is still challenging for researchers. Extraction of robust, mutual information and discriminative features which can be converted into device commands is the biggest challenge in Motor Imagery BCI system. This study aims to analyse the effectiveness of motor and motor imagery classification for left hand and right-hand movements. The motor and motor imagery of left and right-hand movements is defined using statistical features of a higher order that are fed to classifier SVM and Random Forest Classifier. Using SVM classifier, for motor action the classification accuracy of 62.5% was reached and for motor imagery classification accuracy of 45.83% was reached. Using random forest classifier, for motor action the classification accuracy of 80.2% was reached and for motor imagery classification accuracy of 64.58% was reached.
{"title":"Analysis of Motor Action and Motor Imagery Signals for BCI Applications","authors":"B. Vivekananthan, R. Nithya, B. Divya","doi":"10.29027/IJIRASE.V4.I2.2020.612-616","DOIUrl":"https://doi.org/10.29027/IJIRASE.V4.I2.2020.612-616","url":null,"abstract":"— Brain Computer Interface ( BCI) is a computerized system that acquires brain signals, extracts and classifies features during different mental activities, and converts them into correct control signals, and transfers them to external devices. BCI helps people with motor disabilities. Real-time application of a BCI system needs an efficient classification of motor tasks. Motor Imagery task identification based on EEG signals is still challenging for researchers. Extraction of robust, mutual information and discriminative features which can be converted into device commands is the biggest challenge in Motor Imagery BCI system. This study aims to analyse the effectiveness of motor and motor imagery classification for left hand and right-hand movements. The motor and motor imagery of left and right-hand movements is defined using statistical features of a higher order that are fed to classifier SVM and Random Forest Classifier. Using SVM classifier, for motor action the classification accuracy of 62.5% was reached and for motor imagery classification accuracy of 45.83% was reached. Using random forest classifier, for motor action the classification accuracy of 80.2% was reached and for motor imagery classification accuracy of 64.58% was reached.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127855315","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 : 2020-06-01DOI: 10.29027/ijirase.v3.i12.2020.587-592
Preeti Pandey, D. J. Arvindhar
{"title":"Smart System for Attendance","authors":"Preeti Pandey, D. J. Arvindhar","doi":"10.29027/ijirase.v3.i12.2020.587-592","DOIUrl":"https://doi.org/10.29027/ijirase.v3.i12.2020.587-592","url":null,"abstract":"","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108430","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 : 2020-05-01DOI: 10.29027/ijirase.v3.i11.2020.548-559
A. Nawaz, S. Rani
Metal foams are manufactured by various methods which include foaming of molten metal alloy and powder metallurgical processing. Some non conventional methods have also been developed for the manufacturing of metal foams. Metal foams have many interesting characteristics such as high resistance to deformation (stiffness), low specific gravity (specific weight), high resistance to compression and high energy absorption etc. Because of these characteristics metal foams find wide applications mainly in the field of construction where light weight is required, crash and impact energy absorption and in the field of thermal and sound insulation. Metal foams are cellular structure which consists of solid metal mainly (Aluminium, steels, iron etc) with micro pores filled with gas (hydrogen, carbon di oxide, nitrogen, argon etc). The metal foams are open cell or closed cell in nature. The gas comprises a large part of the volume of metal foam. In this review paper different methods for producing metal foam and their mechanical properties analysis are discussed especially for aluminium foam.
{"title":"A review on Fabrication Methods and Analysis of Mechanical Properties of Metal Foams","authors":"A. Nawaz, S. Rani","doi":"10.29027/ijirase.v3.i11.2020.548-559","DOIUrl":"https://doi.org/10.29027/ijirase.v3.i11.2020.548-559","url":null,"abstract":"Metal foams are manufactured by various methods which include foaming of molten metal alloy and powder metallurgical processing. Some non conventional methods have also been developed for the manufacturing of metal foams. Metal foams have many interesting characteristics such as high resistance to deformation (stiffness), low specific gravity (specific weight), high resistance to compression and high energy absorption etc. Because of these characteristics metal foams find wide applications mainly in the field of construction where light weight is required, crash and impact energy absorption and in the field of thermal and sound insulation. Metal foams are cellular structure which consists of solid metal mainly (Aluminium, steels, iron etc) with micro pores filled with gas (hydrogen, carbon di oxide, nitrogen, argon etc). The metal foams are open cell or closed cell in nature. The gas comprises a large part of the volume of metal foam. In this review paper different methods for producing metal foam and their mechanical properties analysis are discussed especially for aluminium foam.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126235633","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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