THERMAL PARAMETERS OF WHEAT-STRAW FIBER REINFORCED NOVEL MATERIAL MEASURED WITH HOT-WIRE METHOD

ZHU Jing; FENG Shihui; LIU Shaotong; QU Zijian; SONG Lizhuo

doi:10.13204/j.gyjzG21012105

Volume 51 Issue 4

Aug. 2021

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Article Navigation > INDUSTRIAL CONSTRUCTION > 2021 > 51(4): 53-57

YANG Yuan, CUI Qiandao, LIAN Jijian, LIU Hongbo, ZHOU Guangen, CHEN Zhihua. LSTM-BASED DAMAGE PREDICTION AND ASSESSMENT OF SPATIAL FRAME STRUCTURE[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(7): 203-208. doi: 10.13204/j.gyjzG20092308

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ZHU Jing, FENG Shihui, LIU Shaotong, QU Zijian, SONG Lizhuo. THERMAL PARAMETERS OF WHEAT-STRAW FIBER REINFORCED NOVEL MATERIAL MEASURED WITH HOT-WIRE METHOD[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(4): 53-57. doi: 10.13204/j.gyjzG21012105

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THERMAL PARAMETERS OF WHEAT-STRAW FIBER REINFORCED NOVEL MATERIAL MEASURED WITH HOT-WIRE METHOD

doi: 10.13204/j.gyjzG21012105

1. College of Civil Engineering and Architecture, Harbin University of Science and Technology, Harbin 150080, China;
2. Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China

Received Date: 2021-01-21
Available Online: 2021-08-19

Abstract

Abstract

The thermal parameters (thermal conductivity, thermal diffusion and specific heat capacity) of PF-AASCM were measured with hot-wire method at high temperatures (20 to 800℃). The thermal conductivity, thermal diffusion and specific heat capacity of PF-AASCM ranged from 0.8 to 3.7 W/(m·K), from 0.3 to 1.1 m²/s, and from 0.5 to 1.8 kJ/(kg·K), respectively. The thermal parameters showed a small peak at 200℃, which is indicated that a strong exothermic reaction happens. The thermal conductivity of PF-AASCM and concrete material was compared, and the analysis results showed that the thermal conductivity of PF-AASCM at 800℃ was basically the same as that of concrete. Its thermal diffusivity is higher, thermal conductivity and specific heat are relatively lower. It shows that PF-AASCM has good thermal diffusivity, but poor heat conduction and storage capacity, which indicates that PF-AASCM has heat insulation and heat storage capacity. The central temperature of the high-temperature specimen was measured, which was compared with the simulation results of finite element in the temperature field, the increase of the central temperature of the specimens is in good agreement.
- alkali-activated slag cementitious material,
- plant fiber,
- hot-wire method,
- thermal performance

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References

[1]	ZHU J, ZHENG W Z, XIE L L, et al. A High-Temperature-Resistant Inorganic Matrix for Concrete Structures Enhanced by Fiber-Reinforced Polymer[J]. Alexandria Engineering Journal, 2021,60(1):131-143.
[2]	朱晶, 郑文忠, 谢礼立, 等. 不同纤维增强碱矿渣胶凝材料高温后力学性能试验研究[J].工业建筑, 2019, 49(5):109-114.
[3]	ZHU J, ZHENG W Z, XIE L L, et al. Alkali-Activated Slag Cement:Alternative Adhesives for CFRP Sheets Bonded to Concrete at Elevated Temperatures[J]. Journal of New Materials for Electrochemical Systems, 2020,23(3):167-176.
[4]	张东磊.碱激发矿渣胶凝材料综述[J].四川建材,2018,44(11):45-46.
[5]	ZHU J, ZHENG W Z, LESLEY H S, et al. Mechanical Properties of Plant Fibers Reinforced Alkali-activated Slag Cementitious Material at High Temperature[J]. Annales de Chimie:Science des Materiaux, 2019, 43(4):240-255.
[6]	JIAO Z Z,WANG Y,ZHENG W Z,et al.Effect of Dosage of Sodium Carbonate on the Strength and Drying Shrinkage of Sodium Hydroxide Based Alkali-Activated Slag paste[J].Construction and Building Materials,2018, 179(10):11-24.
[7]	郑文忠, 朱晶. 碱矿渣胶凝材料结构工程应用基础[M].哈尔滨:哈尔滨工业大学出版社, 2015:1-12.
[8]	朱晶, LESLEY H S, 黄莹, 等. 不同纤维增强碱矿渣胶凝材料的配合比试验研究[J]. 武汉理工大学学报(交通科学与工程版), 2020,44(1):97-102.
[9]	中国标准化委员会. 耐火材料导热系数试验方法(热线法):GB/T 5990-2006[S]. 北京:中国标准出版社, 2006:11-45.
[10]	郑文忠, 王睿, 王英. 活性粉末混凝土热工参数试验研究[J]. 建筑结构学报, 2014, 35(9):107-114.
[11]	ZUDA L,ROVNANIK P,BAYER P,et al. Thermal Properties of Alkali-Activated Slag Subjected to High Temperature[J]. Journal of Building Physics, 2007,30(4):337-350.
[12]	ZUDA L,CERNY R. Measurement of Linear Thermal Expansion Coefficient of Alkali-Activated Aluminosilicate Composites up to 1000℃[J]. Cement and Concrete Composites,2009, 31(4):263-267.
[13]	RAMANAIAH K A V, RATNA P K, HEMA C R. Thermal and Mechanical Properties of Waste Grass Broom Fiber-Reinforced Polyester Composites[J]. Materials and Design,2012, 40(1):103-108.
[14]	王兴肖. 植物纤维增强砌块砌体力学性能试验研究与有限元分析[D]. 武汉:武汉理工大学,2010:12-39.
[15]	李国忠,于衍真,司志明,等. 植物纤维增强水泥基复合材料的性能研究[J]. 硅酸盐通报, 1997(3):42-45.
[16]	ZHU J, ZHENG W Z, QIN C Z, et al. Effect of Different Fibers on Mechanical Properties and Ductility of Alkali-Activated Slag Cementitious Material[J]. Materials Science and Mechanical Engineering, 2017, 292:60-66.
[17]	GONCALVES J R A, BOLUK Y, BINDIGANAVILE V. Thermal Properties of Fibre-Reinforced Alkali-Activated Concrete in Extremetem Peratures[J]. Magazine of Concrete Research, 2018, 70(18):954-964.
[18]	KHALIQ W, KODUR V. Thermal and Mechanical Properties of Fiber Reinforced High Performance Self-Consolidating Concrete at Elevated Temperatures[J]. Cement and Concrete Research, 2011, 41(11):1112-1122.
[19]	苏有文, 李超飞, 杨婷惠,等. 稻草纤维混凝土空心砌块热工性能试验研究[J]. 混凝土, 2016(10):132-134, 138.
[20]	ZHU J, ZHENG W Z, XIE L L, et al. Study on the Performance of Reinforced Concrete Blocks Treated by Styrene-Acrylic Emulsion[J]. Chemical Engineering Transactions, 2018(66):85-90.

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