中国工程科学
中國工程科學
중국공정과학
ENGINEERING SCIENCE
2014年
3期
59-63
,共5页
黄耀英%丁月梅%吕晓曼%徐佰林
黃耀英%丁月梅%呂曉曼%徐佰林
황요영%정월매%려효만%서백림
闸墩%表面保温%通水冷却%浇筑温度%智能优选
閘墩%錶麵保溫%通水冷卻%澆築溫度%智能優選
갑돈%표면보온%통수냉각%요축온도%지능우선
sluice pier%superficial heat preservation%water cooling%pouring temperature%intelligent optimization
闸墩混凝土温控防裂是一个与温控措施和材料参数相关的复杂多因素系统优选问题，本文尝试已知混凝土热力学材料参数情况下的温控措施优选，将闸墩混凝土结构内部和表面主拉应力历时曲线和抗拉强度增长曲线关系的最小值作为输入，闸墩表面保温效果、浇筑温度、通水水温、通水时间作为输出，建立了温控措施优选的神经网络模型，采用均匀设计原理进行温控参数组合，并采用水管冷却有限元法仿真分析含冷却水管的闸墩混凝土结构温度场和徐变应力场，获得样本进行学习，以此训练好的网络描述结构主拉应力历时曲线和抗拉强度增长曲线关系的最小值与不同温控措施的非线性关系。将合适的结构主拉应力历时曲线和抗拉强度增长曲线关系的最小值输入训练好的网络，可自动优选出温控防裂措施。算例分析表明，本文建立的温控措施优选神经网络模型是可行的。
閘墩混凝土溫控防裂是一箇與溫控措施和材料參數相關的複雜多因素繫統優選問題，本文嘗試已知混凝土熱力學材料參數情況下的溫控措施優選，將閘墩混凝土結構內部和錶麵主拉應力歷時麯線和抗拉彊度增長麯線關繫的最小值作為輸入，閘墩錶麵保溫效果、澆築溫度、通水水溫、通水時間作為輸齣，建立瞭溫控措施優選的神經網絡模型，採用均勻設計原理進行溫控參數組閤，併採用水管冷卻有限元法倣真分析含冷卻水管的閘墩混凝土結構溫度場和徐變應力場，穫得樣本進行學習，以此訓練好的網絡描述結構主拉應力歷時麯線和抗拉彊度增長麯線關繫的最小值與不同溫控措施的非線性關繫。將閤適的結構主拉應力歷時麯線和抗拉彊度增長麯線關繫的最小值輸入訓練好的網絡，可自動優選齣溫控防裂措施。算例分析錶明，本文建立的溫控措施優選神經網絡模型是可行的。
갑돈혼응토온공방렬시일개여온공조시화재료삼수상관적복잡다인소계통우선문제，본문상시이지혼응토열역학재료삼수정황하적온공조시우선，장갑돈혼응토결구내부화표면주랍응력력시곡선화항랍강도증장곡선관계적최소치작위수입，갑돈표면보온효과、요축온도、통수수온、통수시간작위수출，건립료온공조시우선적신경망락모형，채용균균설계원리진행온공삼수조합，병채용수관냉각유한원법방진분석함냉각수관적갑돈혼응토결구온도장화서변응력장，획득양본진행학습，이차훈련호적망락묘술결구주랍응력력시곡선화항랍강도증장곡선관계적최소치여불동온공조시적비선성관계。장합괄적결구주랍응력력시곡선화항랍강도증장곡선관계적최소치수입훈련호적망락，가자동우선출온공방렬조시。산례분석표명，본문건립적온공조시우선신경망락모형시가행적。
To the sluice pier concrete,temperature control and crack prevention is a complex and multi-factor problem of system optimization related to temperature control measures and material parameters. This paper tries optimal temperature control measures with the known con-crete material thermodynamics parameters,takes minimum values of the relationships between the sluice pier concrete structure’s internal/surface principal tensile stress duration curve and tensile strength growth curve as inputs and the sluice pier superficial heat preservation effect, pouring temperature,pipe cooling temperature and duration time as outputs,establishes the neural network model of the optimal temperature control measures,takes the uniform design principle to have the temperature control parameter combination,adopts the pipe cooling finite element method(FEM)to simulate and analyze the temperature field and creep stress field of the sluice pier concrete structure with cooling pipe,and gets samples to train network to de-scribe the nonlinear relationship between the relationship’s minimum value of the structure’s principal tensile stress duration curve and tensile strength growth curve and different tempera-ture control measures. Inputting the appropriate relationship’s minimum value of structure’s the principal tensile stress duration curve and tensile strength growth curve to the trained net-work,it can automatically select the optimal temperature control measures. The example shows that the neural network model of the optimal temperature control measures is feasible.
