Wear-driven tool failure is one of the main hurdles in the industry.This issue can be addressed through surface coating with ceramic-reinforced metal matrix composites.However,the maximum ceramic content is limited by...Wear-driven tool failure is one of the main hurdles in the industry.This issue can be addressed through surface coating with ceramic-reinforced metal matrix composites.However,the maximum ceramic content is limited by cracking.In this work,the tribological behaviour of the functionally graded WC-ceramic-particlereinforced Stellite 6 coatings is studied.To that end,the wear resistance at room temperature and 400°C is investigated.Moreover,the tribological analysis is supported by crack sensitivity and hardness evaluation,which is of utmost importance in the processing of composite materials with ceramic-particle-reinforcement.Results indicate that functionally graded materials can be employed to increase the maximum admissible WC content,hence improving the tribological behaviour,most notably at high temperatures.Additionally,a shift from abrasive to oxidative wear is observed in high-temperature wear testing.展开更多
Although animal proteins provide indispensable amino acids that the body requires for normal growth, maintenance and function, their expensiveness makes them unaffordable especially for most families in the developing...Although animal proteins provide indispensable amino acids that the body requires for normal growth, maintenance and function, their expensiveness makes them unaffordable especially for most families in the developing countries. This has given impetus to extensive research into under-utilized protein-rich oilseeds such as sorrel as possible alternate sources of good quality protein for tackling the challenge of protein-energy malnutrition which is fast becoming a global challenge. Sorrel seed may hold great potentials as a source of good quality protein, however the presence of hard seed coat, bitter after-taste and associated antinutritional factors have limited its use as protein supplement for humans and food ingredient. This study therefore compared the effect of dehulling sorrel seed to boiling, germination and roasting. This was with the aim of enhancing its utilization as protein source for human nutrition and functional ingredient in food product development. Flours obtained were analyzed for their proximate, mineral, antinutrient, amino and fatty acids composition;in vitro starch and protein digestibility, and functional and antioxidative properties. Protein content (ranged from 24.93% - 32.91%) significantly increased due to processing;dehulling alone accounted for a percentage increase of 32.01%. Similarly, dehulling increased all essential amino acids (except isoleucine and valine) at percentage which ranged from 3.63% - 61.17% whereas other processing methods caused significant reductions. Lysine, leucine, valine, arginine and phenylalanine were the most abundant essential amino acids, while methionine and cystine were the first and second limiting amino acids. Palmitic, linoleic, oleic and stearic acids were the most abundant fatty acids. Mineral composition was K > Ca > Mg > Na > Fe > Zn > Mn. Dehulled seed flour had highest in vitro protein digestibility (75.87%). Improved amino acid composition, antioxidative and functional properties of sorrel seed flour due to dehulling may indicate the potential of this flour to serve as a protein supplement and functional ingredient for food product development.展开更多
This paper proposes a new Deep Feed-forward Neural Network(DFNN)approach for damage detection in functionally graded carbon nanotube-reinforced composite(FG-CNTRC)plates.In the proposed approach,the DFNN model is deve...This paper proposes a new Deep Feed-forward Neural Network(DFNN)approach for damage detection in functionally graded carbon nanotube-reinforced composite(FG-CNTRC)plates.In the proposed approach,the DFNN model is developed based on a data set containing 20000 samples of damage scenarios,obtained via finite element(FE)simulation,of the FG-CNTRC plates.The elemental modal kinetic energy(MKE)values,calculated from natural frequencies and translational nodal displacements of the structures,are utilized as input of the DFNN model while the damage locations and corresponding severities are considered as output.The state-of-the art Exponential Linear Units(ELU)activation function and the Adamax algorithm are employed to train the DFNN model.Additionally,in order to enhance the performance of the DFNN model,the mini-batch and early-stopping techniques are applied to the training process.A trial-and-error procedure is implemented to determine suitable parameters of the network such as the number of hidden layers and the number of neurons in each layer.The accuracy and capability of the proposed DFNN model are illustrated through two distinct configurations of the CNT-fibers constituting the FG-CNTRC plates including uniform distribution(UD)and functionally graded-V distribution(FG-VD).Furthermore,the performance and stability of the DFNN model with the consideration of noise effects on the input data are also investigated.Obtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection outcomes for the FG-CNTRC plates for both cases of noise-free and noise-influenced data.展开更多
基金supported by the Basque Government(Eusko Jaurlaritza)(Nos.KK-2022/00080 Minaku,KK-2022/00070 Edison)tthe Spanish Ministry of Science and Innovation(Nos.PID2019-109220RB-I00 Alasurf,PDC2021-121042-I00 EHU-Coax)the Basque Government(Eusko Jaurlaritza)in call IT 1573-22 for the financial support of the research group.
文摘Wear-driven tool failure is one of the main hurdles in the industry.This issue can be addressed through surface coating with ceramic-reinforced metal matrix composites.However,the maximum ceramic content is limited by cracking.In this work,the tribological behaviour of the functionally graded WC-ceramic-particlereinforced Stellite 6 coatings is studied.To that end,the wear resistance at room temperature and 400°C is investigated.Moreover,the tribological analysis is supported by crack sensitivity and hardness evaluation,which is of utmost importance in the processing of composite materials with ceramic-particle-reinforcement.Results indicate that functionally graded materials can be employed to increase the maximum admissible WC content,hence improving the tribological behaviour,most notably at high temperatures.Additionally,a shift from abrasive to oxidative wear is observed in high-temperature wear testing.
文摘Although animal proteins provide indispensable amino acids that the body requires for normal growth, maintenance and function, their expensiveness makes them unaffordable especially for most families in the developing countries. This has given impetus to extensive research into under-utilized protein-rich oilseeds such as sorrel as possible alternate sources of good quality protein for tackling the challenge of protein-energy malnutrition which is fast becoming a global challenge. Sorrel seed may hold great potentials as a source of good quality protein, however the presence of hard seed coat, bitter after-taste and associated antinutritional factors have limited its use as protein supplement for humans and food ingredient. This study therefore compared the effect of dehulling sorrel seed to boiling, germination and roasting. This was with the aim of enhancing its utilization as protein source for human nutrition and functional ingredient in food product development. Flours obtained were analyzed for their proximate, mineral, antinutrient, amino and fatty acids composition;in vitro starch and protein digestibility, and functional and antioxidative properties. Protein content (ranged from 24.93% - 32.91%) significantly increased due to processing;dehulling alone accounted for a percentage increase of 32.01%. Similarly, dehulling increased all essential amino acids (except isoleucine and valine) at percentage which ranged from 3.63% - 61.17% whereas other processing methods caused significant reductions. Lysine, leucine, valine, arginine and phenylalanine were the most abundant essential amino acids, while methionine and cystine were the first and second limiting amino acids. Palmitic, linoleic, oleic and stearic acids were the most abundant fatty acids. Mineral composition was K > Ca > Mg > Na > Fe > Zn > Mn. Dehulled seed flour had highest in vitro protein digestibility (75.87%). Improved amino acid composition, antioxidative and functional properties of sorrel seed flour due to dehulling may indicate the potential of this flour to serve as a protein supplement and functional ingredient for food product development.
基金This research was funded by Vietnam National Foundation for Science and Technology Development(NAFOSTED)under No.107.02-2019.330.
文摘This paper proposes a new Deep Feed-forward Neural Network(DFNN)approach for damage detection in functionally graded carbon nanotube-reinforced composite(FG-CNTRC)plates.In the proposed approach,the DFNN model is developed based on a data set containing 20000 samples of damage scenarios,obtained via finite element(FE)simulation,of the FG-CNTRC plates.The elemental modal kinetic energy(MKE)values,calculated from natural frequencies and translational nodal displacements of the structures,are utilized as input of the DFNN model while the damage locations and corresponding severities are considered as output.The state-of-the art Exponential Linear Units(ELU)activation function and the Adamax algorithm are employed to train the DFNN model.Additionally,in order to enhance the performance of the DFNN model,the mini-batch and early-stopping techniques are applied to the training process.A trial-and-error procedure is implemented to determine suitable parameters of the network such as the number of hidden layers and the number of neurons in each layer.The accuracy and capability of the proposed DFNN model are illustrated through two distinct configurations of the CNT-fibers constituting the FG-CNTRC plates including uniform distribution(UD)and functionally graded-V distribution(FG-VD).Furthermore,the performance and stability of the DFNN model with the consideration of noise effects on the input data are also investigated.Obtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection outcomes for the FG-CNTRC plates for both cases of noise-free and noise-influenced data.
