Frost Resistance of Pervious Concrete Mixed with Waste Glass Powder

The contents of waste glass powder(WGP)(0%,10%,15%,20%,25%)and water-binder ratio(W/C)(0.24,0.26,0.28)were used as influencing factors,and the quality loss rate(Δm)and compressive strength loss rate(Δfc)were used as characterization parameters.The Ca/Si ratio and main element contents of C-S-H gels with different WGP content were investigated by energy dispersive spectrometry(EDS).The pore structure evolution characteristics of WGP composite cementing materials were investigated by low field nuclear magnetic resonance(NMR).UsingΔfc as the index of frost resistance degradation and Weibull function,the frost resistance degradation of glass doped pervious concrete(WGP-PC)was modeled.The results show that,with WGP,for the same number of cycles,Δm andΔfc decrease and increase with the increase of WGP.Under the same WGP content,Δm andΔfc decrease first and then increase with the increase of W/C.After 100 freeze-thaw cycles,the samples with WGP content of 20%and W/C of 0.26 have the best freeze-resistance.Microscopic tests show that with the increase of WGP content,the Ca/Si ratio of C-S-H gel decreases at first and then increases with the increase of WGP content.The extreme value of Ca/Si is 2.36 when WGP is added by 20%.The pore volume of hardened paste with 20%WGP content decreased by 18.6%compared with that of cement system without WGP.The overall compactness of the specimen was improved.On the basis of the test data,a life prediction model was established according to Weibull function.The experiment showed thatΔfc could be used as a durability degradation index,and the slope of the reliability curve became gentle after WGP was added,which reduced the damage degradation rate of PC.W/C was 0.26.It's about 5000 hours.

A Novel Method to Enhance the Inversion Speed and Precision of the NMR T_(2) Spectrum by the TSVD Based Linearized Bregman Iteration

The low-field nuclear magnetic resonance(NMR)technique has been used to probe the pore size distribution and the fluid composition in geophysical prospecting and related fields.However,the speed and accuracy of the existing numerical inversion methods are still challenging due to the ill-posed nature of the first kind Fredholm integral equation and the contamination of the noises.This paper proposes a novel inversion algorithmto accelerate the convergence and enhance the precision using empirical truncated singular value decompositions(TSVD)and the linearized Bregman iteration.The L1 penalty term is applied to construct the objective function,and then the linearized Bregman iteration is utilized to obtain fast convergence.To reduce the complexity of the computation,empirical TSVD is proposed to compress the kernel matrix and determine the appropriate truncated position.This novel inversion method is validated using numerical simulations.The results indicate that the proposed novel method is significantly efficient and can achieve quick and effective data solutions with low signal-to-noise ratios.

Simultaneous Determination of Oil and Water in Soybean by LF-NMR Relaxometry and Chemometrics

A fast, non-destructive and eco-friendly method was developed to simultaneously determine the oil and water contents of soybean based on low field nuclear magnetic resonance（LF-NMR） relaxometry combined with chemometrics, such as partial least squares regression（PLSR）. The Carr-Purcell-Meiboom-Gill（CPMG） magnetiza- tion decay data of ten soybean samples were acquired by LF-NMR and directly applied to the PLSR analysis. Cali- bration models were established via PLSR with full cross-validation based on the reference values obtained by the Soxhlet extraction method for measuring oil and oven-drying method for measuring water. The results indicate that the calibration models are satisfactory for both oil and water determinations; the root mean squared errors of cross-validation（RMSECV） for oil and water are 0.2285% and 0.0178%, respectively. Furthermore, the oil and water contents in unknown soybean samples were predicted by the PLSR models and the results were compared with the reference values. The relative errors of the predicted oil and water contents were in ranges of 1.25%---4.96% and 0.44%--2.49%, respectively. These results demonstrate that the combination of LF-NMR relaxometry with chemo- metrics shows great potential for the simultaneous determination of contents of oil and water in soybean with high accuracy.

Pore size distribution of high volatile bituminous coal of the southern Junggar Basin: a full-scale characterization applying multiple methods

Studying on the pore size distribution of coal is vital for determining reasonable coalbed methane development strategies.The coalbed methane project is in progress in the southern Junggar Basin of northwestern China,where high volatile bituminous coal is reserved.In this study,with the purpose of accurately characterizing the full-scale pore size distribution of the high volatile bituminous coal of the southern Junggar Basin,two grouped coal samples were applied for mercury intrusion porosimetry,low-temperature nitrogen adsorption,low-field nuclear magnetic resonance,rate-controlled mercury penetration,scanning electron microscopy,and nano-CT measurements.A comprehensive pore size distribution was proposed by combining the corrected mercury intrusion porosimetry data and low-temperature nitrogen adsorption data.The relationship between transverse relaxation time(T2,ms)and the pore diameter was determined by comparing the T2 spectrum with the comprehensive pore size distribution.The macro-pore and throat size distributions derived from nano-CT and rate-controlled mercury penetration were distinguishingly analyzed.The results showed that:1)comprehensive pore size distribution analysis can be regarded as an accurate method to characterize the pore size distribution of high volatile bituminous coal;2)for the high volatile bituminous coal of the southern Junggar Basin,the meso-pore volume was the greatest,followed by the transition pore volume or macro-pore volume,and the micro-pore volume was the lowest;3)the relationship between T2 and the pore diameter varied for different samples,even for samples with close maturities;4)the throat size distribution derived from nano-CT was close to that derived from rate-controlled mercury penetration,while the macro-pore size distributions derived from those two methods were very different.This work can deepen the knowledge of the pore size distribution characterization techniques of coal and provide new insight for accurate pore size distribution characterization of high volatile bituminous coal.