Ahmed Saber, Murat Altin, Erdem Acar, Mehmet Ali Güler
{"title":"熔融沉积建模(FDM)法制备正正弦波纹型多单元PLA+吸能材料的准静态压缩试验数据集","authors":"Ahmed Saber, Murat Altin, Erdem Acar, Mehmet Ali Güler","doi":"10.1016/j.dib.2026.113173","DOIUrl":null,"url":null,"abstract":"<div><div>This article presents an experimental dataset for additively manufactured, sinusoidally-corrugated multi-cell (SCMC) energy absorbers tested under quasi-static axial compression. Forty SCMC configurations were generated by Latin Hypercube Sampling (LHS) over four geometric design variables, together with a nominal configuration (N-SCMC) and a simple tube without corrugation (STWC) as baseline designs. All specimens were fabricated from PLA+ filament on a Bambu Lab A1 Mini fused deposition modeling (FDM) printer, and the PLA+ mechanical behavior was characterized by uniaxial tensile testing in accordance with <span><span>ASTM D638</span><svg><path></path></svg></span>. The two baseline configurations were tested in triplicate to confirm repeatability. The dataset comprises PLA+ tensile characterization data, geometric design parameters, STL geometry files, axial force–displacement responses, and derived crashworthiness indicators such as the crush force efficiency <span><math><mrow><mo>(</mo><mrow><mi>C</mi><mi>F</mi><mi>E</mi></mrow><mo>)</mo></mrow></math></span>, and specific energy absorption <span><math><mrow><mo>(</mo><mrow><mi>S</mi><mi>E</mi><mi>A</mi></mrow><mo>)</mo></mrow></math></span>, along with sequential deformation images captured at 5 mm displacement intervals. These data support surrogate modeling, machine learning applications, optimization, and validation of numerical models for FDM-printed polymer energy absorbers.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113173"},"PeriodicalIF":1.9000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quasi-static compression test dataset of sinusoidally-corrugated multi-cell PLA+ energy absorbers fabricated by fused deposition modeling (FDM)\",\"authors\":\"Ahmed Saber, Murat Altin, Erdem Acar, Mehmet Ali Güler\",\"doi\":\"10.1016/j.dib.2026.113173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article presents an experimental dataset for additively manufactured, sinusoidally-corrugated multi-cell (SCMC) energy absorbers tested under quasi-static axial compression. Forty SCMC configurations were generated by Latin Hypercube Sampling (LHS) over four geometric design variables, together with a nominal configuration (N-SCMC) and a simple tube without corrugation (STWC) as baseline designs. All specimens were fabricated from PLA+ filament on a Bambu Lab A1 Mini fused deposition modeling (FDM) printer, and the PLA+ mechanical behavior was characterized by uniaxial tensile testing in accordance with <span><span>ASTM D638</span><svg><path></path></svg></span>. The two baseline configurations were tested in triplicate to confirm repeatability. The dataset comprises PLA+ tensile characterization data, geometric design parameters, STL geometry files, axial force–displacement responses, and derived crashworthiness indicators such as the crush force efficiency <span><math><mrow><mo>(</mo><mrow><mi>C</mi><mi>F</mi><mi>E</mi></mrow><mo>)</mo></mrow></math></span>, and specific energy absorption <span><math><mrow><mo>(</mo><mrow><mi>S</mi><mi>E</mi><mi>A</mi></mrow><mo>)</mo></mrow></math></span>, along with sequential deformation images captured at 5 mm displacement intervals. These data support surrogate modeling, machine learning applications, optimization, and validation of numerical models for FDM-printed polymer energy absorbers.</div></div>\",\"PeriodicalId\":10973,\"journal\":{\"name\":\"Data in Brief\",\"volume\":\"68 \",\"pages\":\"Article 113173\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2026-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data in Brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352340926007201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2026/8/14 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340926007201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/8/14 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Quasi-static compression test dataset of sinusoidally-corrugated multi-cell PLA+ energy absorbers fabricated by fused deposition modeling (FDM)
This article presents an experimental dataset for additively manufactured, sinusoidally-corrugated multi-cell (SCMC) energy absorbers tested under quasi-static axial compression. Forty SCMC configurations were generated by Latin Hypercube Sampling (LHS) over four geometric design variables, together with a nominal configuration (N-SCMC) and a simple tube without corrugation (STWC) as baseline designs. All specimens were fabricated from PLA+ filament on a Bambu Lab A1 Mini fused deposition modeling (FDM) printer, and the PLA+ mechanical behavior was characterized by uniaxial tensile testing in accordance with ASTM D638. The two baseline configurations were tested in triplicate to confirm repeatability. The dataset comprises PLA+ tensile characterization data, geometric design parameters, STL geometry files, axial force–displacement responses, and derived crashworthiness indicators such as the crush force efficiency , and specific energy absorption , along with sequential deformation images captured at 5 mm displacement intervals. These data support surrogate modeling, machine learning applications, optimization, and validation of numerical models for FDM-printed polymer energy absorbers.
期刊介绍:
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