本文選題：Thermo-TDR　切入點(diǎn)：凍土熱特性　出處：《中國農(nóng)業(yè)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：在凍土的水熱耦合遷移研究中,凍土熱特性和凍結(jié)特征曲線的測(cè)定與模擬以及冰含量的測(cè)定具有非常重要的意義。傳統(tǒng)的穩(wěn)態(tài)法在測(cè)定凍土熱特性時(shí)經(jīng)常存在一定誤差,熱脈沖方法則在測(cè)定過程中可能引起凍土中冰的融化；熱特性預(yù)測(cè)模型廣泛應(yīng)用于土壤水熱耦合傳輸模擬中,但是目前缺乏一個(gè)簡單、準(zhǔn)確、未凍土和凍土都適用的熱導(dǎo)率預(yù)測(cè)模型。凍土中冰含量還沒有一個(gè)標(biāo)準(zhǔn)測(cè)定方法,已有的方法都有一定的限制。凍結(jié)特征曲線是凍土研究中重要的水力學(xué)參數(shù),但其測(cè)定過程常常受到過冷卻現(xiàn)象等影響。熱脈沖-時(shí)域反射技術(shù)(T hermo-TDR)可以同時(shí)測(cè)定土壤的液態(tài)水含量和熱特性,通過改進(jìn)加熱方式能將其應(yīng)用到凍土中。另外Thermo-TDR具有間接估計(jì)凍土冰含量的潛能,也可以用于凍結(jié)特征曲線的測(cè)定。本研究旨在通過優(yōu)化TTiermo-TDR的加熱方式,使其能夠準(zhǔn)確測(cè)定凍土的熱特性,并利用熱特性數(shù)據(jù)改進(jìn)熱導(dǎo)率模型和估計(jì)凍融過程中土壤冰含量變化。此外,本研究還改進(jìn)了凍結(jié)特征曲線的測(cè)定方法,探討利用凍結(jié)特征曲線來預(yù)測(cè)其他土壤物理特性。主要研究結(jié)果如下：第一,對(duì)凍土中Thermo-TDR加熱模式進(jìn)行了優(yōu)化,使其能夠準(zhǔn)確測(cè)定凍土的熱特性。當(dāng)土壤溫度低于-5℃時(shí),采用加熱時(shí)間60s和加熱量450J m-1或者加熱時(shí)間90 s和加熱量450-600 Jm-1的加熱模式,可以有效低限制凍土中冰的融化,得到準(zhǔn)確的熱容量和熱導(dǎo)率。第二,發(fā)展了一個(gè)簡單、準(zhǔn)確且同時(shí)適用于未凍土和凍土的熱導(dǎo)率預(yù)測(cè)模型。該模型以deVries(1963)模型為基礎(chǔ),通過簡化和優(yōu)化原模型的一些參數(shù),能夠準(zhǔn)確地預(yù)測(cè)未凍土和凍土的熱導(dǎo)率。利用實(shí)測(cè)和文獻(xiàn)數(shù)據(jù)對(duì)簡化de Vries模型準(zhǔn)確性的檢驗(yàn)表明,相比于已有模型,簡化模型在未凍土和凍土中預(yù)測(cè)結(jié)果的均方根誤差(RMSE)都最小。第三,可以利用TTiermo-TDR測(cè)定的凍土的容積熱容量、液態(tài)水含量以及土壤容重來間接估計(jì)土壤冰含量。利用TTiermo-TDR測(cè)定了不同初始含水量的3種不同質(zhì)地土壤凍融過程中的冰含量變化。結(jié)果表明,當(dāng)溫度低于-5℃時(shí),TTiermo-TDR測(cè)定的冰含量誤差主要在±0.05 m3m-3范圍內(nèi),但在質(zhì)地較粘土壤中測(cè)定誤差比較大(達(dá)到±0.10 m3 m-3)。第四,可以利用凍土熱導(dǎo)率結(jié)果和簡化的de Vries模型來反推得到冰含量。敏感性分析表明,熱容量法比熱導(dǎo)率法對(duì)于液態(tài)水含量等誤差源更敏感,熱導(dǎo)率法估計(jì)的冰含量要比熱容量法的結(jié)果更準(zhǔn)確。在3種土壤上冰含量的實(shí)驗(yàn)結(jié)果證實(shí)了這一理論推斷。第五,利用冰牙簽法消除了過冷卻影響,并進(jìn)一步了比較平衡法與采用不同降溫速率的動(dòng)態(tài)法測(cè)定的凍結(jié)特征曲線。結(jié)果表明,與平衡法相比,采用10℃ h-1降溫速率的動(dòng)態(tài)法的測(cè)定結(jié)果存在一定的誤差,而采用2.5℃ h-1降溫速率的結(jié)果與平衡法沒有差異,動(dòng)態(tài)法實(shí)驗(yàn)操作更簡單。第六,對(duì)不同凍結(jié)特征曲線擬合模型準(zhǔn)確性的比較指出,分段指數(shù)函數(shù)模型擬合效果最好。聯(lián)合凍結(jié)特征曲線和沙箱法數(shù)據(jù)擬合了5種不同質(zhì)地土壤的全范圍水分特征曲線。結(jié)果表明,除了砂壤土外,其他四種土壤的擬合曲線與沙箱法、壓力板法和露點(diǎn)水勢(shì)儀法實(shí)測(cè)的全范圍含水量-水勢(shì)數(shù)據(jù)具有很好的相關(guān)性,相關(guān)系數(shù)在0.948和0.985之間。凍結(jié)特征曲線上-10℃以下的數(shù)據(jù)可以用來估計(jì)土壤的比表面積,估計(jì)結(jié)果與露點(diǎn)水勢(shì)儀測(cè)定值相關(guān)系數(shù)為0.985。
[Abstract]:In the frozen soil water heat coupling migration study, has a very important significance to determination of thermal properties of frozen soil and determination of freezing characteristic curve and simulation and ice content. The conventional steady-state method often has some error in the determination of thermal properties of frozen soil, heat pulse method may cause the permafrost melting ice in the determination process of heat; the characteristic model is widely used in the coupled water and heat transfer simulation of soil, but the lack of a simple, accurate, predictive model of thermal conductivity without permafrost and the permafrost applicable rate. In the frozen soil ice content determination method is not a standard, the existing methods have certain limitations. Freezing characteristic curve is an important hydraulic study on parameters of frozen soil, but the determination process is often influenced by cooling phenomenon. Thermo time domain reflectometry (T hermo-TDR) liquid water content determination of soil and thermal characteristics, By improving the heating method can be applied to the soil. In addition Thermo-TDR has indirect estimation of permafrost ice content potential, can also be used for the determination of freezing characteristic curve. The purpose of this study is to optimize the TTiermo-TDR through heating, the thermal characteristics of accurate measurement of frozen soil, and the thermal characteristic data of ice content changes of soil thermal conductivity model and the estimation of the freezing thawing process improvement. In addition, this study also improved the determination method of freezing characteristic curve, to explore the use of freezing characteristic curve to predict the physical properties of other soil. The main results are as follows: first, the Thermo-TDR heating mode in frozen soil were optimized. The thermal characteristics can be accurately determined. When the soil is frozen the temperature is lower than -5 DEG C, the heating time and heating capacity of 450J 60s M-1 90 s or heating time and heating rate of 450-600 Jm-1 heating mode, can effectively lower limit Frozen in the ice melts, accurate heat capacity and thermal conductivity. Second, the development of a simple, accurate prediction model of thermal conductivity and also applicable to frozen soil and permafrost. In this model, deVries (1963) model as the foundation, through the simplification and optimization of some parameters of the original model, can not accurately predict the frozen soil and permafrost thermal conductivity rate. Using the measured data to test and document the simplified de Vries model accuracy show that compared to the existing simplified model, the root mean square error of prediction results in frozen soil and frozen soils (RMSE) are minimum. Third, the volumetric heat capacity determined by TTiermo-TDR liquid water content of frozen soil. And the capacity of soil heavy soil ice content. Indirect estimates of 3 different kinds of soil freezing and thawing process of the ice content changes of different initial water content was determined by TTiermo-TDR. The results show that when the temperature is lower than -5 DEG C, TTier The ice content error measured by mo-TDR mainly in the 0.05 m3m-3 range, but the texture is sticky soil determination error is relatively large (up to 0.10 m3 M-3). De fourth, Vries model can be simplified by using frozen rate results and the thermal conductivity of ice to determine the content. The sensitivity analysis showed that the thermal conductivity method specific heat capacity method more sensitive to the error of liquid water content source, the amount of ice thermal conductivity estimation to specific heat capacity and the method is more accurate. In 3 kinds of soil ice content was confirmed by the experimental results that this theory. Fifth, use ice toothpick method to eliminate the cooling effect, and further compared with equilibrium method dynamic method at different cooling rates for the determination of freezing characteristic curve. The results show that, compared with the results of the dynamic balance method, determination method with 10 DEG H-1 cooling rate has some error, and using H-1 2.5 degrees of cooling rate and results There is no difference between the method of dynamic balance method, the experimental operation is simple. Sixth, comparing to different freezing characteristic curve fitting accuracy of the model, piecewise exponential model best fitting effect. Combined with freezing characteristic curve and the sandbox method of data fitting 5 different soil texture full range water characteristic curve. The results show that, in addition to outside sandy loam the other four kinds of soil, the fitting curve and the sandbox method, the full range of pressure plate and dewpoint waterpotential instrument method to measure the water content and water potential data has good correlation, the correlation coefficient between 0.948 and 0.985 degrees Celsius. Frozen data -10 characteristic curve can be used to estimate the soil surface area, the estimated value of the relevant coefficient of determination results and dewpoint waterpotential instrument 0.985.

【學(xué)位授予單位】：中國農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：S152

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