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( Lifang Yue ),( Hexin Lv ),( Jing Zhen ),( Shengping Jiang ),( Shiru Jia ),( Shigang Shen ),( Lu Gao ),( Yujie Dai ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.4
Preservation of fresh algae plays an important role in algae seed subculture and aquaculture. The determination and examination of the changes of cell viability, composition, and bacterial species during storage would help to take suitable preservation methods to prolong the preservation time of fresh algae. Nostoc flagelliforme is a kind of edible cyanobacterium with important herbal and dietary values. This article investigated the changes of bacterial species and biochemical characteristics of fresh N. flagelliforme concentrate during natural storage. It was found that the viability of cells decreased along with the storage time. Fourteen bacteria strains in the algae concentrate were identified by PCR-DGGE and were grouped into four phyla, including Cyanobacteria, Firmicutes, Proteobacteria, and Bacteroidetes. Among them, Enterococcus viikkiensis may be a concern in the preservation. Eleven volatile organic compounds were identified from N. flagelliforme cells, in which geosmin could be treated as an indicator of the freshness of N. flagelliforme. The occurrence of indole compound may be an indicator of the degradation of cells.
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An efficient method to structural static reanalysis with deleting support constraints
Haifeng Liu,Shigang Yue 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.6
Structural design is usually an optimization process. Numerous parameters such as the member shapes and sizes, the elasticity modulus of material, the locations of nodes and the support constraints can be selected as design variables. These variables are progressively revised in order to obtain a satisfactory structure. Each modification requires a fresh analysis for the displacements and stresses, and reanalysis can be employed to reduce the computational cost. This paper is focused on static reanalysis problem withmodification of deleting some supports. An efficient reanalysis method is proposed. The method makes full use of the initial information and preserves the ease of implementation. Numerical examples show that thecalculated results of the proposed method are the identical as those of the direct analysis, while thecomputational time is remarkably reduced.
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An efficient method to structural static reanalysis with deleting support constraints
Liu, Haifeng,Yue, Shigang Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.6
Structural design is usually an optimization process. Numerous parameters such as the member shapes and sizes, the elasticity modulus of material, the locations of nodes and the support constraints can be selected as design variables. These variables are progressively revised in order to obtain a satisfactory structure. Each modification requires a fresh analysis for the displacements and stresses, and reanalysis can be employed to reduce the computational cost. This paper is focused on static reanalysis problem with modification of deleting some supports. An efficient reanalysis method is proposed. The method makes full use of the initial information and preserves the ease of implementation. Numerical examples show that the calculated results of the proposed method are the identical as those of the direct analysis, while the computational time is remarkably reduced.
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Isakhani Hamid,Bellotto Nicola,Fu Qinbing,Yue Shigang 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.5
Gliding is generally one of the most efficient modes of flight in natural fliers that can be further emphasized in the aircraft industry to reduce emissions and facilitate endured flights. Natural wings being fundamentally responsible for this phenomenon are developed over millions of years of evolution. Artificial wings, on the other hand, are limited to the human-proposed conceptual design phase often leading to sub-optimal results. However, the novel Generative Design (GD) method claims to produce mechanically improved solutions based on robust and rigorous models of design conditions and performance criteria. This study investigates the potential applications of this Computer-Associated Design (CAsD) technology to generate novel micro aerial vehicle wing concepts that are structurally more stable and efficient. Multiple performance-driven solutions (wings) with high-level goals are generated by an infinite scale cloud computing solution executing a machine learning-based GD algorithm. Ultimately, the highest performing CAsD concepts are numerically analysed, fabricated, and mechanically tested according to our previous study, and the results are compared to the literature for qualitative as well as quantitative analysis and validations. It was concluded that the GD-based tandem wings’ (forewing and hindwing) ability to withstand fracture failure without compromising structural rigidity was optimized by 78% compared to its peer models. However, the weight was slightly increased by 11% with 14% drop in stiffness when compared to our models from previous study.
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