Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications
The study focused on assessing selected organic fillers’ impact (periwinkle and clam shells) on the physicochemical and mechanical properties of polyester composites. The tensile, compressive, flexural and Brinell hardness tests were respectively carried out in accordance to ASTM standards. The meth...
Gespeichert in:
Veröffentlicht in: | SN computer science 2024-10, Vol.5 (7), p.832 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 7 |
container_start_page | 832 |
container_title | SN computer science |
container_volume | 5 |
creator | Ihueze, Christopher Chukwutoo Okafor, Christian Emeka Omeiza, Obende Ezekiel |
description | The study focused on assessing selected organic fillers’ impact (periwinkle and clam shells) on the physicochemical and mechanical properties of polyester composites. The tensile, compressive, flexural and Brinell hardness tests were respectively carried out in accordance to ASTM standards. The methods involved grinding and sieve analysis of the shells, material preparation, and Taguchi robust design aided by Plackett–Burman screening. Signal-to-noise ratio analysis guided composite fabrication. The process control variables were grouped in terms of particles sizes: 75, 150, 425 µm, weight fraction: 5%, 20%, 40% and material thickness: 5, 15, 25 mm. The Artificial Neural Network (ANN) training was carried out using MATLAB R2013a and the cascade-forward back-propagation architecture while Adaptive network-based fuzzy system (ANFIS) which is a well-known hybrid artificial intelligence model was subsequently applied. The geometrical model of 9 mm FMJ armour piercing ammunition projectile and the armour plate was modeled using a commercial finite element software package (ANSYS v14) suitable for high velocity impact. The Finite Element Analysis (FEA) further investigates the deformation, elastic strain, and stress response of clam and periwinkle reinforced composites under ballistic impact. Scanning Electron Microscopy (SEM), Fourier transform infrared (FTIR), Differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA)/Differential thermal analysis (DTA) were deployed to further study the morphology, chemical composition, phase transitions and thermal stability of the optimal material. The results revealed that the clam shell reinforced composite have mechanical responses of 11.038 MPa, 17.07 MPa, 40.2 MPa, and 69.62 N/mm for tensile, compressive, flexural, and hardness strength respectively. While the periwinkle shell reinforced composite has mechanical responses of 16.111 MPa, 17.173 MPa, 39.7 MPa, and 63.57 N/mm for tensile, compressive, flexural, and hardness strength respectively. FEA results indicate decreasing deformation, elastic strain, and stress with increasing material thickness. The investigation carried out indicated the impact of the organic fillers and showed that the new material properties depend on the reinforcement combinations of control parameters. |
doi_str_mv | 10.1007/s42979-024-03199-0 |
format | Article |
fullrecord | <record><control><sourceid>proquest_sprin</sourceid><recordid>TN_cdi_proquest_journals_3097630720</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3097630720</sourcerecordid><originalsourceid>FETCH-LOGICAL-p720-b9397a6705c8c2a08a4aacc8ebad03fb1a46f9a149724b57bc4c677ce618b7f53</originalsourceid><addsrcrecordid>eNpFkM1qwzAQhEVpoSHNC_Qk6FntSpYl65imf4GUQMmhh4KRZdk4OJIr2Ye-fZWk0MvuHIadnQ-hWwr3FEA-RM6UVAQYJ5BRldQFmjEhKCkUyMuTZkSp_PMaLWLcAwDLgXORz9DXh6-mOOInG7vWYe1qvHaj7fuutW7E774-atdi3-BtaLXrDHnU0dZ45Q-Dj91oI258wMtw8FP4wcth6Dujx867eIOuGt1Hu_jbc7R7ed6t3shm-7peLTdkkAxIpTIltZCQm8IwDYXmWhtT2ErXkDUV1Vw0SlOuJONVLivDjZDSWEGLSjZ5Nkd357ND8N-TjWO5T6-4lFhmoKTIIMUkV3Z2xSGkQjb8uyiUR5DlGWSZQJYnkGn-AoDwZuE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3097630720</pqid></control><display><type>article</type><title>Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications</title><source>SpringerLink Journals - AutoHoldings</source><creator>Ihueze, Christopher Chukwutoo ; Okafor, Christian Emeka ; Omeiza, Obende Ezekiel</creator><creatorcontrib>Ihueze, Christopher Chukwutoo ; Okafor, Christian Emeka ; Omeiza, Obende Ezekiel</creatorcontrib><description>The study focused on assessing selected organic fillers’ impact (periwinkle and clam shells) on the physicochemical and mechanical properties of polyester composites. The tensile, compressive, flexural and Brinell hardness tests were respectively carried out in accordance to ASTM standards. The methods involved grinding and sieve analysis of the shells, material preparation, and Taguchi robust design aided by Plackett–Burman screening. Signal-to-noise ratio analysis guided composite fabrication. The process control variables were grouped in terms of particles sizes: 75, 150, 425 µm, weight fraction: 5%, 20%, 40% and material thickness: 5, 15, 25 mm. The Artificial Neural Network (ANN) training was carried out using MATLAB R2013a and the cascade-forward back-propagation architecture while Adaptive network-based fuzzy system (ANFIS) which is a well-known hybrid artificial intelligence model was subsequently applied. The geometrical model of 9 mm FMJ armour piercing ammunition projectile and the armour plate was modeled using a commercial finite element software package (ANSYS v14) suitable for high velocity impact. The Finite Element Analysis (FEA) further investigates the deformation, elastic strain, and stress response of clam and periwinkle reinforced composites under ballistic impact. Scanning Electron Microscopy (SEM), Fourier transform infrared (FTIR), Differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA)/Differential thermal analysis (DTA) were deployed to further study the morphology, chemical composition, phase transitions and thermal stability of the optimal material. The results revealed that the clam shell reinforced composite have mechanical responses of 11.038 MPa, 17.07 MPa, 40.2 MPa, and 69.62 N/mm for tensile, compressive, flexural, and hardness strength respectively. While the periwinkle shell reinforced composite has mechanical responses of 16.111 MPa, 17.173 MPa, 39.7 MPa, and 63.57 N/mm for tensile, compressive, flexural, and hardness strength respectively. FEA results indicate decreasing deformation, elastic strain, and stress with increasing material thickness. The investigation carried out indicated the impact of the organic fillers and showed that the new material properties depend on the reinforcement combinations of control parameters.</description><identifier>ISSN: 2662-995X</identifier><identifier>EISSN: 2661-8907</identifier><identifier>DOI: 10.1007/s42979-024-03199-0</identifier><language>eng</language><publisher>Singapore: Springer Nature Singapore</publisher><subject>Adaptive systems ; Armor penetration ; Artificial intelligence ; Artificial neural networks ; Back propagation networks ; Brinell hardness tests ; Chemical composition ; Composite fabrication ; Composite materials ; Computer Imaging ; Computer Science ; Computer Systems Organization and Communication Networks ; Data Structures and Information Theory ; Datasets ; Design of experiments ; Elastic deformation ; Elastic properties ; Fillers ; Finite element method ; Fourier transforms ; Heat resistance ; Impact analysis ; Information Systems and Communication Service ; Interfacial bonding ; Machine learning ; Manufacturing ; Mathematical models ; Mechanical properties ; Neural networks ; Noise control ; Original Research ; Particle size ; Pattern Recognition and Graphics ; Phase transitions ; Polymers ; Projectiles ; Research Advancements in Intelligent Computing ; Shell stability ; Sieve analysis ; Signal to noise ratio ; Software Engineering/Programming and Operating Systems ; Strain ; Tensile strength ; Thermal stability ; Thickness ; Vision</subject><ispartof>SN computer science, 2024-10, Vol.5 (7), p.832</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p720-b9397a6705c8c2a08a4aacc8ebad03fb1a46f9a149724b57bc4c677ce618b7f53</cites><orcidid>0000-0001-6259-0999</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s42979-024-03199-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s42979-024-03199-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Ihueze, Christopher Chukwutoo</creatorcontrib><creatorcontrib>Okafor, Christian Emeka</creatorcontrib><creatorcontrib>Omeiza, Obende Ezekiel</creatorcontrib><title>Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications</title><title>SN computer science</title><addtitle>SN COMPUT. SCI</addtitle><description>The study focused on assessing selected organic fillers’ impact (periwinkle and clam shells) on the physicochemical and mechanical properties of polyester composites. The tensile, compressive, flexural and Brinell hardness tests were respectively carried out in accordance to ASTM standards. The methods involved grinding and sieve analysis of the shells, material preparation, and Taguchi robust design aided by Plackett–Burman screening. Signal-to-noise ratio analysis guided composite fabrication. The process control variables were grouped in terms of particles sizes: 75, 150, 425 µm, weight fraction: 5%, 20%, 40% and material thickness: 5, 15, 25 mm. The Artificial Neural Network (ANN) training was carried out using MATLAB R2013a and the cascade-forward back-propagation architecture while Adaptive network-based fuzzy system (ANFIS) which is a well-known hybrid artificial intelligence model was subsequently applied. The geometrical model of 9 mm FMJ armour piercing ammunition projectile and the armour plate was modeled using a commercial finite element software package (ANSYS v14) suitable for high velocity impact. The Finite Element Analysis (FEA) further investigates the deformation, elastic strain, and stress response of clam and periwinkle reinforced composites under ballistic impact. Scanning Electron Microscopy (SEM), Fourier transform infrared (FTIR), Differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA)/Differential thermal analysis (DTA) were deployed to further study the morphology, chemical composition, phase transitions and thermal stability of the optimal material. The results revealed that the clam shell reinforced composite have mechanical responses of 11.038 MPa, 17.07 MPa, 40.2 MPa, and 69.62 N/mm for tensile, compressive, flexural, and hardness strength respectively. While the periwinkle shell reinforced composite has mechanical responses of 16.111 MPa, 17.173 MPa, 39.7 MPa, and 63.57 N/mm for tensile, compressive, flexural, and hardness strength respectively. FEA results indicate decreasing deformation, elastic strain, and stress with increasing material thickness. The investigation carried out indicated the impact of the organic fillers and showed that the new material properties depend on the reinforcement combinations of control parameters.</description><subject>Adaptive systems</subject><subject>Armor penetration</subject><subject>Artificial intelligence</subject><subject>Artificial neural networks</subject><subject>Back propagation networks</subject><subject>Brinell hardness tests</subject><subject>Chemical composition</subject><subject>Composite fabrication</subject><subject>Composite materials</subject><subject>Computer Imaging</subject><subject>Computer Science</subject><subject>Computer Systems Organization and Communication Networks</subject><subject>Data Structures and Information Theory</subject><subject>Datasets</subject><subject>Design of experiments</subject><subject>Elastic deformation</subject><subject>Elastic properties</subject><subject>Fillers</subject><subject>Finite element method</subject><subject>Fourier transforms</subject><subject>Heat resistance</subject><subject>Impact analysis</subject><subject>Information Systems and Communication Service</subject><subject>Interfacial bonding</subject><subject>Machine learning</subject><subject>Manufacturing</subject><subject>Mathematical models</subject><subject>Mechanical properties</subject><subject>Neural networks</subject><subject>Noise control</subject><subject>Original Research</subject><subject>Particle size</subject><subject>Pattern Recognition and Graphics</subject><subject>Phase transitions</subject><subject>Polymers</subject><subject>Projectiles</subject><subject>Research Advancements in Intelligent Computing</subject><subject>Shell stability</subject><subject>Sieve analysis</subject><subject>Signal to noise ratio</subject><subject>Software Engineering/Programming and Operating Systems</subject><subject>Strain</subject><subject>Tensile strength</subject><subject>Thermal stability</subject><subject>Thickness</subject><subject>Vision</subject><issn>2662-995X</issn><issn>2661-8907</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpFkM1qwzAQhEVpoSHNC_Qk6FntSpYl65imf4GUQMmhh4KRZdk4OJIr2Ye-fZWk0MvuHIadnQ-hWwr3FEA-RM6UVAQYJ5BRldQFmjEhKCkUyMuTZkSp_PMaLWLcAwDLgXORz9DXh6-mOOInG7vWYe1qvHaj7fuutW7E774-atdi3-BtaLXrDHnU0dZ45Q-Dj91oI258wMtw8FP4wcth6Dujx867eIOuGt1Hu_jbc7R7ed6t3shm-7peLTdkkAxIpTIltZCQm8IwDYXmWhtT2ErXkDUV1Vw0SlOuJONVLivDjZDSWEGLSjZ5Nkd357ND8N-TjWO5T6-4lFhmoKTIIMUkV3Z2xSGkQjb8uyiUR5DlGWSZQJYnkGn-AoDwZuE</recordid><startdate>20241001</startdate><enddate>20241001</enddate><creator>Ihueze, Christopher Chukwutoo</creator><creator>Okafor, Christian Emeka</creator><creator>Omeiza, Obende Ezekiel</creator><general>Springer Nature Singapore</general><general>Springer Nature B.V</general><scope>JQ2</scope><orcidid>https://orcid.org/0000-0001-6259-0999</orcidid></search><sort><creationdate>20241001</creationdate><title>Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications</title><author>Ihueze, Christopher Chukwutoo ; Okafor, Christian Emeka ; Omeiza, Obende Ezekiel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p720-b9397a6705c8c2a08a4aacc8ebad03fb1a46f9a149724b57bc4c677ce618b7f53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adaptive systems</topic><topic>Armor penetration</topic><topic>Artificial intelligence</topic><topic>Artificial neural networks</topic><topic>Back propagation networks</topic><topic>Brinell hardness tests</topic><topic>Chemical composition</topic><topic>Composite fabrication</topic><topic>Composite materials</topic><topic>Computer Imaging</topic><topic>Computer Science</topic><topic>Computer Systems Organization and Communication Networks</topic><topic>Data Structures and Information Theory</topic><topic>Datasets</topic><topic>Design of experiments</topic><topic>Elastic deformation</topic><topic>Elastic properties</topic><topic>Fillers</topic><topic>Finite element method</topic><topic>Fourier transforms</topic><topic>Heat resistance</topic><topic>Impact analysis</topic><topic>Information Systems and Communication Service</topic><topic>Interfacial bonding</topic><topic>Machine learning</topic><topic>Manufacturing</topic><topic>Mathematical models</topic><topic>Mechanical properties</topic><topic>Neural networks</topic><topic>Noise control</topic><topic>Original Research</topic><topic>Particle size</topic><topic>Pattern Recognition and Graphics</topic><topic>Phase transitions</topic><topic>Polymers</topic><topic>Projectiles</topic><topic>Research Advancements in Intelligent Computing</topic><topic>Shell stability</topic><topic>Sieve analysis</topic><topic>Signal to noise ratio</topic><topic>Software Engineering/Programming and Operating Systems</topic><topic>Strain</topic><topic>Tensile strength</topic><topic>Thermal stability</topic><topic>Thickness</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ihueze, Christopher Chukwutoo</creatorcontrib><creatorcontrib>Okafor, Christian Emeka</creatorcontrib><creatorcontrib>Omeiza, Obende Ezekiel</creatorcontrib><collection>ProQuest Computer Science Collection</collection><jtitle>SN computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ihueze, Christopher Chukwutoo</au><au>Okafor, Christian Emeka</au><au>Omeiza, Obende Ezekiel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications</atitle><jtitle>SN computer science</jtitle><stitle>SN COMPUT. SCI</stitle><date>2024-10-01</date><risdate>2024</risdate><volume>5</volume><issue>7</issue><spage>832</spage><pages>832-</pages><issn>2662-995X</issn><eissn>2661-8907</eissn><abstract>The study focused on assessing selected organic fillers’ impact (periwinkle and clam shells) on the physicochemical and mechanical properties of polyester composites. The tensile, compressive, flexural and Brinell hardness tests were respectively carried out in accordance to ASTM standards. The methods involved grinding and sieve analysis of the shells, material preparation, and Taguchi robust design aided by Plackett–Burman screening. Signal-to-noise ratio analysis guided composite fabrication. The process control variables were grouped in terms of particles sizes: 75, 150, 425 µm, weight fraction: 5%, 20%, 40% and material thickness: 5, 15, 25 mm. The Artificial Neural Network (ANN) training was carried out using MATLAB R2013a and the cascade-forward back-propagation architecture while Adaptive network-based fuzzy system (ANFIS) which is a well-known hybrid artificial intelligence model was subsequently applied. The geometrical model of 9 mm FMJ armour piercing ammunition projectile and the armour plate was modeled using a commercial finite element software package (ANSYS v14) suitable for high velocity impact. The Finite Element Analysis (FEA) further investigates the deformation, elastic strain, and stress response of clam and periwinkle reinforced composites under ballistic impact. Scanning Electron Microscopy (SEM), Fourier transform infrared (FTIR), Differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA)/Differential thermal analysis (DTA) were deployed to further study the morphology, chemical composition, phase transitions and thermal stability of the optimal material. The results revealed that the clam shell reinforced composite have mechanical responses of 11.038 MPa, 17.07 MPa, 40.2 MPa, and 69.62 N/mm for tensile, compressive, flexural, and hardness strength respectively. While the periwinkle shell reinforced composite has mechanical responses of 16.111 MPa, 17.173 MPa, 39.7 MPa, and 63.57 N/mm for tensile, compressive, flexural, and hardness strength respectively. FEA results indicate decreasing deformation, elastic strain, and stress with increasing material thickness. The investigation carried out indicated the impact of the organic fillers and showed that the new material properties depend on the reinforcement combinations of control parameters.</abstract><cop>Singapore</cop><pub>Springer Nature Singapore</pub><doi>10.1007/s42979-024-03199-0</doi><orcidid>https://orcid.org/0000-0001-6259-0999</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2662-995X |
ispartof | SN computer science, 2024-10, Vol.5 (7), p.832 |
issn | 2662-995X 2661-8907 |
language | eng |
recordid | cdi_proquest_journals_3097630720 |
source | SpringerLink Journals - AutoHoldings |
subjects | Adaptive systems Armor penetration Artificial intelligence Artificial neural networks Back propagation networks Brinell hardness tests Chemical composition Composite fabrication Composite materials Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Datasets Design of experiments Elastic deformation Elastic properties Fillers Finite element method Fourier transforms Heat resistance Impact analysis Information Systems and Communication Service Interfacial bonding Machine learning Manufacturing Mathematical models Mechanical properties Neural networks Noise control Original Research Particle size Pattern Recognition and Graphics Phase transitions Polymers Projectiles Research Advancements in Intelligent Computing Shell stability Sieve analysis Signal to noise ratio Software Engineering/Programming and Operating Systems Strain Tensile strength Thermal stability Thickness Vision |
title | Robust Design and Intelligent Modelling of Organic-Based Composites for Armoury Applications |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T20%3A59%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Robust%20Design%20and%20Intelligent%20Modelling%20of%20Organic-Based%20Composites%20for%20Armoury%20Applications&rft.jtitle=SN%20computer%20science&rft.au=Ihueze,%20Christopher%20Chukwutoo&rft.date=2024-10-01&rft.volume=5&rft.issue=7&rft.spage=832&rft.pages=832-&rft.issn=2662-995X&rft.eissn=2661-8907&rft_id=info:doi/10.1007/s42979-024-03199-0&rft_dat=%3Cproquest_sprin%3E3097630720%3C/proquest_sprin%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3097630720&rft_id=info:pmid/&rfr_iscdi=true |