DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES
This study performs a design and multi-objective optimization of auxetic honeycomb sandwich panels (AHSPs) subjected to air blast loading to enhance the blastworthiness of armored ghting vehicle (AFV) structures. The objective metrics used as the blastworthiness parameters are permanent displacem...
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Teknik (Rekayasa, enjinering dan kegiatan berkaitan) Andika DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
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This study performs a design and multi-objective optimization of auxetic honeycomb
sandwich panels (AHSPs) subjected to air blast loading to enhance the
blastworthiness of armored ghting vehicle (AFV) structures. The objective
metrics used as the blastworthiness parameters are permanent displacement
and specic energy absorption (SEA). Four auxetic geometries are proposed
for the sandwich core: re-entrant honeycomb (REH), double-arrow honeycomb
(DAH), star honeycomb (SH), and tetra-chiral honeycomb (CH). Each geometry
is evaluated for its potential to improve energy absorption and minimize
deformation under blast conditions.
Combination of nite element (FE) simulations and machine learning (ML)
methodologies is employed to assess the blastworthiness of dierent AHSP geometries.
Multi-objective optimization is conducted using the non-dominated
sorting genetic algorithm II (NSGA-II) method based on an articial neural
network (ANN) metamodel. The Pareto front from the optimization results
shows the congurations which the blastworthiness signicantly improved,
with notable reductions in permanent displacement and enhancements in SEA
compared to baseline models. Furthermore, the DAH structures provide better
performance than other auxetic geometries. The conguration of the optimized
AHSP DAH includes 15 cells in the horizontal direction and 5 cells
in the vertical direction, with a corner angle of 0.1?, and a thickness of 1.72
mm. This conguration surpasses the optimized aluminium foam sandwich
panels (AFSPs) in terms of permanent displacement reduction and specic
energy absorption (SEA) increase, with improvements of 36.67% and 155.13%,
respectively.
The global sensitivity analysis (GSA) using SHapley Additive exPlanations
(SHAP) reveals that cell thickness is the most critical factor aecting blastworthiness
performance, followed by the number of cells in the horizontal and
vertical directions, and the corner angle or node radius for the CH model. Additionally,
the study observes that the global negative Poisson's ratio (NPR)
behavior of AHSPs under air blast loading is inconsistent due to the very high
velocity impact from the blast impulses, occurring primarily in specic condii tions such as small relative density. The results show that better NPR behavior
does not always correlate with improved performance. However, the conguration
of auxetic structures allows for ecient energy absorption, thereby
increasing the blast resistance of the structure.
Lastly, the application of optimized AHSP DAH for AFV protection under an
8 kg TNT explosion is evaluated to meet the requirements of NATO STANAG
4569. The optimized conguration show promising results, with no failure occurring
in the occupant oor. The AFV equipped with the optimized AHSP
DAH signicantly reduce the maximum displacement and acceleration of occupant
oors by 39% and 43.56%, respectively, and enhance the SEA by 48.43%
compared to optimized AFSP. This study concludes that AHSPs have potential
applications in defense, automotive, and aerospace industries. However,
further research is needed to comprehensively understand their response to air
blast loading and to explore additional optimization objectives. baik tidak selalu berkorelasi dengan performa yang lebih baik. Namun, kongurasi
struktur auxetic memungkinkan penyerapan energi yang esien, sehingga
meningkatkan resistansi ledakan struktur.
Terakhir, aplikasi AHSP DAH optimal untuk perlindungan kendaraan lapis
baja di bawah ledakan TNT 8 kg dievaluasi untuk memenuhi persyaratan
NATO STANAG 4569. Kongurasi optimal menunjukkan hasil yang menjanjikan,
dimana tidak terjadi kegagalan di lantai penumpang. Kendaraan lapis
baja yang ditambahkan dengan AHSP DAH optimal secara signikan mengurangi
perpindahan maksimum dan percepatan dari lantai penumpang sebesar
39% dan 43.56%, berturut-turut, dan meningkatkan penyerapan energi spesik
sebesar 48.43% dibandingkan panel sandwich berinti busa aluminium optimal.
Studi ini menyimpulkan bahwa AHSP memiliki potensi aplikasi dalam industri
pertahanan, otomotif, dan kedirgantaraan. Namun, penelitian lebih lanjut
diperlukan untuk memahami secara komprehensif respons mereka terhadap
beban ledakan udara dan untuk mengeksplorasi objektif optimisasi lainnya. |
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title |
DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
title_short |
DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
title_full |
DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
title_fullStr |
DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
title_full_unstemmed |
DESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES |
title_sort |
design and multi-objective optimization of auxetic honeycomb sandwich panels for blastworthy structures |
url |
https://digilib.itb.ac.id/gdl/view/86567 |
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id-itb.:865672024-11-15T16:05:58ZDESIGN AND MULTI-OBJECTIVE OPTIMIZATION OF AUXETIC HONEYCOMB SANDWICH PANELS FOR BLASTWORTHY STRUCTURES Andika Teknik (Rekayasa, enjinering dan kegiatan berkaitan) Indonesia Theses Structural blastworthiness, Auxetic structure, Finite element, Machine learning, SHapley Additive exPlanations, Armored ghting vehicle INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/86567 This study performs a design and multi-objective optimization of auxetic honeycomb sandwich panels (AHSPs) subjected to air blast loading to enhance the blastworthiness of armored ghting vehicle (AFV) structures. The objective metrics used as the blastworthiness parameters are permanent displacement and specic energy absorption (SEA). Four auxetic geometries are proposed for the sandwich core: re-entrant honeycomb (REH), double-arrow honeycomb (DAH), star honeycomb (SH), and tetra-chiral honeycomb (CH). Each geometry is evaluated for its potential to improve energy absorption and minimize deformation under blast conditions. Combination of nite element (FE) simulations and machine learning (ML) methodologies is employed to assess the blastworthiness of dierent AHSP geometries. Multi-objective optimization is conducted using the non-dominated sorting genetic algorithm II (NSGA-II) method based on an articial neural network (ANN) metamodel. The Pareto front from the optimization results shows the congurations which the blastworthiness signicantly improved, with notable reductions in permanent displacement and enhancements in SEA compared to baseline models. Furthermore, the DAH structures provide better performance than other auxetic geometries. The conguration of the optimized AHSP DAH includes 15 cells in the horizontal direction and 5 cells in the vertical direction, with a corner angle of 0.1?, and a thickness of 1.72 mm. This conguration surpasses the optimized aluminium foam sandwich panels (AFSPs) in terms of permanent displacement reduction and specic energy absorption (SEA) increase, with improvements of 36.67% and 155.13%, respectively. The global sensitivity analysis (GSA) using SHapley Additive exPlanations (SHAP) reveals that cell thickness is the most critical factor aecting blastworthiness performance, followed by the number of cells in the horizontal and vertical directions, and the corner angle or node radius for the CH model. Additionally, the study observes that the global negative Poisson's ratio (NPR) behavior of AHSPs under air blast loading is inconsistent due to the very high velocity impact from the blast impulses, occurring primarily in specic condii tions such as small relative density. The results show that better NPR behavior does not always correlate with improved performance. However, the conguration of auxetic structures allows for ecient energy absorption, thereby increasing the blast resistance of the structure. Lastly, the application of optimized AHSP DAH for AFV protection under an 8 kg TNT explosion is evaluated to meet the requirements of NATO STANAG 4569. The optimized conguration show promising results, with no failure occurring in the occupant oor. The AFV equipped with the optimized AHSP DAH signicantly reduce the maximum displacement and acceleration of occupant oors by 39% and 43.56%, respectively, and enhance the SEA by 48.43% compared to optimized AFSP. This study concludes that AHSPs have potential applications in defense, automotive, and aerospace industries. However, further research is needed to comprehensively understand their response to air blast loading and to explore additional optimization objectives. baik tidak selalu berkorelasi dengan performa yang lebih baik. Namun, kongurasi struktur auxetic memungkinkan penyerapan energi yang esien, sehingga meningkatkan resistansi ledakan struktur. Terakhir, aplikasi AHSP DAH optimal untuk perlindungan kendaraan lapis baja di bawah ledakan TNT 8 kg dievaluasi untuk memenuhi persyaratan NATO STANAG 4569. Kongurasi optimal menunjukkan hasil yang menjanjikan, dimana tidak terjadi kegagalan di lantai penumpang. Kendaraan lapis baja yang ditambahkan dengan AHSP DAH optimal secara signikan mengurangi perpindahan maksimum dan percepatan dari lantai penumpang sebesar 39% dan 43.56%, berturut-turut, dan meningkatkan penyerapan energi spesik sebesar 48.43% dibandingkan panel sandwich berinti busa aluminium optimal. Studi ini menyimpulkan bahwa AHSP memiliki potensi aplikasi dalam industri pertahanan, otomotif, dan kedirgantaraan. Namun, penelitian lebih lanjut diperlukan untuk memahami secara komprehensif respons mereka terhadap beban ledakan udara dan untuk mengeksplorasi objektif optimisasi lainnya. text |