Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices...Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.展开更多
Multi-view Subspace Clustering (MVSC) emerges as an advanced clustering method, designed to integrate diverse views to uncover a common subspace, enhancing the accuracy and robustness of clustering results. The signif...Multi-view Subspace Clustering (MVSC) emerges as an advanced clustering method, designed to integrate diverse views to uncover a common subspace, enhancing the accuracy and robustness of clustering results. The significance of low-rank prior in MVSC is emphasized, highlighting its role in capturing the global data structure across views for improved performance. However, it faces challenges with outlier sensitivity due to its reliance on the Frobenius norm for error measurement. Addressing this, our paper proposes a Low-Rank Multi-view Subspace Clustering Based on Sparse Regularization (LMVSC- Sparse) approach. Sparse regularization helps in selecting the most relevant features or views for clustering while ignoring irrelevant or noisy ones. This leads to a more efficient and effective representation of the data, improving the clustering accuracy and robustness, especially in the presence of outliers or noisy data. By incorporating sparse regularization, LMVSC-Sparse can effectively handle outlier sensitivity, which is a common challenge in traditional MVSC methods relying solely on low-rank priors. Then Alternating Direction Method of Multipliers (ADMM) algorithm is employed to solve the proposed optimization problems. Our comprehensive experiments demonstrate the efficiency and effectiveness of LMVSC-Sparse, offering a robust alternative to traditional MVSC methods.展开更多
Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Anal...Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Analysis (RPCA) addresses these limitations by decomposing data into a low-rank matrix capturing the underlying structure and a sparse matrix identifying outliers, enhancing robustness against noise and outliers. This paper introduces a novel RPCA variant, Robust PCA Integrating Sparse and Low-rank Priors (RPCA-SL). Each prior targets a specific aspect of the data’s underlying structure and their combination allows for a more nuanced and accurate separation of the main data components from outliers and noise. Then RPCA-SL is solved by employing a proximal gradient algorithm for improved anomaly detection and data decomposition. Experimental results on simulation and real data demonstrate significant advancements.展开更多
A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with...A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with the recovery of fully perturbed low-rank matrices. By utilizing the p-null space property (p-NSP) and the p-restricted isometry property (p-RIP) of the matrix, sufficient conditions to ensure that the stable and accurate reconstruction for low-rank matrix in the case of full perturbation are derived, and two upper bound recovery error estimation ns are given. These estimations are characterized by two vital aspects, one involving the best r-approximation error and the other concerning the overall noise. Specifically, this paper obtains two new error upper bounds based on the fact that p-RIP and p-NSP are able to recover accurately and stably low-rank matrix, and to some extent improve the conditions corresponding to RIP.展开更多
In view of the limited bandwidth of underwater video image transmission,a low bit rate underwater video compression coding method is proposed.Based on the preprocessing process of wavelet transform and coefficient dow...In view of the limited bandwidth of underwater video image transmission,a low bit rate underwater video compression coding method is proposed.Based on the preprocessing process of wavelet transform and coefficient down-sampling,the visual redundancy of underwater image is removed and the computational coefficients and coding bits are reduced.At the same time,combined with multi-level wavelet decomposition,inter frame motion compensation,entropy coding and other methods,according to the characteristics of different types of frame image data,reduce the number of calculations and improve the coding efficiency.The experimental results show that the reconstructed image quality can meet the visual requirements,and the average compression ratio of underwater video can meet the requirements of underwater acoustic channel transmission rate.展开更多
Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilizatio...Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index(LMDI) decomposition method was used to explore the influence factors of CO2 emissions in Central Asia(including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992–2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO2 emissions during the study period. Our results show that the total CO2 emissions decreased during the period 1992–1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO2 emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO2 emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO2 emissions. The contribution percentages of these four factors(economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO2 emissions were 11.80%, 39.08%, –44.82% and –4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO2 with the annual average emissions of 189.69×106, 45.55×106 and 115.38×106 t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO2 emissions and economic growth, highlighting the occurrence of a ’’weak decoupling’’ between these two variables in Central Asia. In conclusion, our results indicate that CO2 emissions are still not completely decoupled from economic growth in Central Asia. Based on these results, we suggest four key policy suggestions in this paper to help Central Asia to reduce CO2 emissions and build a resource-conserving and environment-friendly society.展开更多
Iron-based perovskite-type compounds modified by Ru were prepared through sol-gel process to study its catalytic activity of NOx direct decomposition at low temperature and evaluate the conversion of NO under the expe...Iron-based perovskite-type compounds modified by Ru were prepared through sol-gel process to study its catalytic activity of NOx direct decomposition at low temperature and evaluate the conversion of NO under the experimental conditions. The catalytic activity of La 0.9Ce 0.1Fe 0.8-nCo 0.2RunO3 （n=0.01,0.03,0.05,0.07,0.09）series for the NO, NO-CO two components, CO-HC-NO three components were also analyzed. The catalytic investigation evidenced that the presence of Ru is necessary for making highly activity in decomposition of nitric oxide even at low temperature（400 ℃）and La 0.9Ce 0.9Fe 0.75Co 0.2Ru 0.05O3 （n=0.05） has better activity in all the samples, the conversion of it is 58.5%. With the reducing gas（CO,C3H6）added into the gas, the catalyst displayed very high activity in decomposition of NO and the conversion of it is 80% and 92.5% separately.展开更多
The effect of rare earth metals(REM)on the characteristics of auto-tempering and decomposition of martensite for low-carbon and low-alloy steels(20SiMn2V and 20SiMn2VRE)was investigated using TEM,dilatometer and micro...The effect of rare earth metals(REM)on the characteristics of auto-tempering and decomposition of martensite for low-carbon and low-alloy steels(20SiMn2V and 20SiMn2VRE)was investigated using TEM,dilatometer and microhardness test.Results show that both ε.and θ carbides,during auto-tempering, may precipitate from the low-carbon martensite matrix at the same time in the 20SiMn2V steel,however,the precipitation of the ε-carbides can be inhibited by the REM contained in the 20SiMn2 VRE steel,resulting in change of the type of precipitated carbides and decrease of the extent of auto-tempering.The“in-situ”ob- servations show that the decomposition of martensite is also inhibited by the REM contained in the 20SiMn2 VRE steel during low temperature tempering.展开更多
Based on the problems caused by many oxygen-containing functional groups and poor floatability on the surface of low rank coal,the characteristics of low rank coal were analyzed systematically by means of scanning ele...Based on the problems caused by many oxygen-containing functional groups and poor floatability on the surface of low rank coal,the characteristics of low rank coal were analyzed systematically by means of scanning electron microscopy(SEM),X-ray diffraction(XRD)and X-Ray photoelectron spectroscopy(XPS)techniques.The bubble-particle induction time was used to determine the characterization of the bubble-particle attachment,and the bubble-particle attachment of low rank coal modified by soaking the coal samples in an acid or alkaline solution was analyzed.The floatability of the modified coal surface was verified by flotation tests.The results show that the particle size of 0.125–0.074 mm of the coal sample exhibited better bubble-particle attachment characteristics.The small bubble,the larger approach velocity of bubble and the larger bubble deformation were more helpful to enhance the bubbleparticle attachment.For an acid solution,the smaller the p H was and the longer the soaking time was,the better the floatability of the coal sample and the higher the combustible material recovery were.The combustible material recovery of low rank coal was increased to 78.79%by soaking the sample in an acid solution of pH=0 for 180 min.On the contrary there was a best concentration for the alkaline solution.展开更多
A series of char samples were derived from pyrolysis of two typical low-rank coals in China （Shengli lig- nite and Shenmu bituminous coal） at low, medium and fast heating rates, respectively, to the same pyrol- ysis...A series of char samples were derived from pyrolysis of two typical low-rank coals in China （Shengli lig- nite and Shenmu bituminous coal） at low, medium and fast heating rates, respectively, to the same pyrol- ysis temperature 750℃. Then these chars were characterized by means of thermogravimetric analysis and Fourier transform infrared spectrometer with the aim to investigate the influence of heating rate in pyrolysis process on gasification reactivity and surface chemistry of them. Besides, a homogeneous model was used to quantitatively analyze the activation energy of gasification reaction. The results reveal that Shengli lignite and its derived chars behave higher gasification reactivity and have less content of oxygen functional groups than Shenmu coal and chars. Meanwhile, chars derived from Shengli lignite at 50℃/min and Shenmu coal at 200℃/min have the greatest gasification reactivity, respectively. The oxygen functional groups in Shengli lignite are easily thermo-decomposed, and they are less affected by the heating rate, while that in Shenmu coal have a significant change with the variation of heating rate. In addition, there is no good correlation between the change of oxygen functional groups and that of the gasification reactivity of the derived chars from pyrolysis at different heating rates.展开更多
The pretreatment of low rank coal with nitric acid oxidation can promote its bio-liquefaction. However, the detailed mechanism of which remains an unresolved problem. In the present work, the characteristics of Fushun...The pretreatment of low rank coal with nitric acid oxidation can promote its bio-liquefaction. However, the detailed mechanism of which remains an unresolved problem. In the present work, the characteristics of Fushun coal before and after oxidation by nitric acid were investigated combined with elemental composition, pore volume and pore size, Zeta potential, FT-IR, and 13C solid NMR spectrum analysis. The results show that the inorganic substance inlaid in coal are dissolved by ni- tric acid, which results in the decrease of coal ash content and increase of pore volume and pore size. Furthermore, there exist obvious chemical reactions between nitric acid and the functional groups of coal including aromatic ring carboxylation, side chain alkyl of aromatic ring oxidation and aromatic ring nitration. Among these reactions, some led to the increase in content of carboxyl, aliphatic carbon connected with O and humic acid carbon, while others caused the reduction of aromaticity, methyl carbon, substituted aryl carbon and side chain.展开更多
Laojunmiao coal samples from the eastern Junggar basin were studied to understand the relationship between coal resistivity and the physical parameters of coal reservoirs under high temperatures and pressures.Specific...Laojunmiao coal samples from the eastern Junggar basin were studied to understand the relationship between coal resistivity and the physical parameters of coal reservoirs under high temperatures and pressures.Specifically,we analysed the relationship of coal resistivity to porosity and permeability via heating and pressurization experiments.The results indicated that coal resistivity decreases exponentially with increasing pressure.Increasing the temperature decreases the resistivity.The sensitivity of coal resistivity to the confining pressure is worse when the temperature is higher.The resistivity of dry coal samples was linearly related to φ~m.Increasing the temperature decreased the cementation exponent(m).Increasing the confining pressure exponentially decreases the porosity.Decreasing the pressure increases the resistivity and porosity for a constant temperature.Increasing the temperature yields a quadratic relationship between the resistivity and permeability for a constant confining pressure.Based on the Archie formula,we obtained the coupling relationship between coal resistivity and permeability for Laojunmiao coal samples at different temperatures and confining pressures.展开更多
The high-value utilization of low-rank coal would allow for expanding energy sources,improving energy efficiencies,and alleviating environmental issues.In order to use low-rank coal effectively,the hypercoals(HPCs)wer...The high-value utilization of low-rank coal would allow for expanding energy sources,improving energy efficiencies,and alleviating environmental issues.In order to use low-rank coal effectively,the hypercoals(HPCs)were co-extracted from two types of low-rank coal and biomass via N-methyl-2-purrolidinone(NMP)under mild conditions.The structures of the HPCs and residues were characterized by proximate and ultimate analysis,Raman spectra,and Fourier transform infrared(FT-IR)spectra.The carbon structure changes within the raw coals and HPCs were discussed.The individual thermal dissolution of Xibu(XB)coal,Guandi(GD)coal,and the biomass demonstrated that the biomass provided the lowest thermal dissolution yield Y1 and the highest thermal soluble yield Y2 at 280℃,and the ash content of three HPCs decreased as the extraction temperature rose.Co-thermal extractions in NMP at various coal/biomass mass ratios were performed,demonstrating a positive synergic effect for Y2 in the whole coal/biomass mass ratios.The maximum value of Y2 was 52.25wt% for XB coal obtained with a XB coal/biomass of 50wt% biomass.The maximum value of Y2 was 50.77wt% for GD coal obtained with a GD coal/biomass of 1:4.The difference for the optimal coal/biomass mass ratios between XB and GD coals could be attributed to the different co-extraction mechanisms for this two type coals.展开更多
To reasonably utilize the coal direct liquefaction residue(DLR), contrasting research on the co-pyrolysis between different low-rank coals and DLR was investigated using a TGA coupled with an FT-IR spectrophotometer a...To reasonably utilize the coal direct liquefaction residue(DLR), contrasting research on the co-pyrolysis between different low-rank coals and DLR was investigated using a TGA coupled with an FT-IR spectrophotometer and a fixed-bed reactor. GC–MS, FTIR, and XRD were used to explore the reaction mechanisms of the various co-pyrolysis processes. Based on the TGA results, it was confirmed that the tetrahydrofuran insoluble fraction of DLR helped to catalyze the conversion reaction of lignite. Also, the addition of DLR improved the yield of tar in the fixed-bed, with altering the composition of the tar. Moreover, a kinetic analysis during the co-pyrolysis was conducted using a distributed activation energy model. The co-pyrolysis reactions showed an approximate double-Gaussian distribution.展开更多
基金supported by the National Natural Science Foundation of China(62171088,U19A2052,62020106011)the Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China(ZYGX2021YGLH215,ZYGX2022YGRH005)。
文摘Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.
文摘Multi-view Subspace Clustering (MVSC) emerges as an advanced clustering method, designed to integrate diverse views to uncover a common subspace, enhancing the accuracy and robustness of clustering results. The significance of low-rank prior in MVSC is emphasized, highlighting its role in capturing the global data structure across views for improved performance. However, it faces challenges with outlier sensitivity due to its reliance on the Frobenius norm for error measurement. Addressing this, our paper proposes a Low-Rank Multi-view Subspace Clustering Based on Sparse Regularization (LMVSC- Sparse) approach. Sparse regularization helps in selecting the most relevant features or views for clustering while ignoring irrelevant or noisy ones. This leads to a more efficient and effective representation of the data, improving the clustering accuracy and robustness, especially in the presence of outliers or noisy data. By incorporating sparse regularization, LMVSC-Sparse can effectively handle outlier sensitivity, which is a common challenge in traditional MVSC methods relying solely on low-rank priors. Then Alternating Direction Method of Multipliers (ADMM) algorithm is employed to solve the proposed optimization problems. Our comprehensive experiments demonstrate the efficiency and effectiveness of LMVSC-Sparse, offering a robust alternative to traditional MVSC methods.
文摘Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Analysis (RPCA) addresses these limitations by decomposing data into a low-rank matrix capturing the underlying structure and a sparse matrix identifying outliers, enhancing robustness against noise and outliers. This paper introduces a novel RPCA variant, Robust PCA Integrating Sparse and Low-rank Priors (RPCA-SL). Each prior targets a specific aspect of the data’s underlying structure and their combination allows for a more nuanced and accurate separation of the main data components from outliers and noise. Then RPCA-SL is solved by employing a proximal gradient algorithm for improved anomaly detection and data decomposition. Experimental results on simulation and real data demonstrate significant advancements.
文摘A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with the recovery of fully perturbed low-rank matrices. By utilizing the p-null space property (p-NSP) and the p-restricted isometry property (p-RIP) of the matrix, sufficient conditions to ensure that the stable and accurate reconstruction for low-rank matrix in the case of full perturbation are derived, and two upper bound recovery error estimation ns are given. These estimations are characterized by two vital aspects, one involving the best r-approximation error and the other concerning the overall noise. Specifically, this paper obtains two new error upper bounds based on the fact that p-RIP and p-NSP are able to recover accurately and stably low-rank matrix, and to some extent improve the conditions corresponding to RIP.
文摘In view of the limited bandwidth of underwater video image transmission,a low bit rate underwater video compression coding method is proposed.Based on the preprocessing process of wavelet transform and coefficient down-sampling,the visual redundancy of underwater image is removed and the computational coefficients and coding bits are reduced.At the same time,combined with multi-level wavelet decomposition,inter frame motion compensation,entropy coding and other methods,according to the characteristics of different types of frame image data,reduce the number of calculations and improve the coding efficiency.The experimental results show that the reconstructed image quality can meet the visual requirements,and the average compression ratio of underwater video can meet the requirements of underwater acoustic channel transmission rate.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19030204)the West Light Foundation of the Chinese Academy of Sciences (2015-XBQN-17)
文摘Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index(LMDI) decomposition method was used to explore the influence factors of CO2 emissions in Central Asia(including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992–2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO2 emissions during the study period. Our results show that the total CO2 emissions decreased during the period 1992–1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO2 emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO2 emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO2 emissions. The contribution percentages of these four factors(economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO2 emissions were 11.80%, 39.08%, –44.82% and –4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO2 with the annual average emissions of 189.69×106, 45.55×106 and 115.38×106 t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO2 emissions and economic growth, highlighting the occurrence of a ’’weak decoupling’’ between these two variables in Central Asia. In conclusion, our results indicate that CO2 emissions are still not completely decoupled from economic growth in Central Asia. Based on these results, we suggest four key policy suggestions in this paper to help Central Asia to reduce CO2 emissions and build a resource-conserving and environment-friendly society.
基金Sponsored by the National Natural Science Foundation of China(Grant No.20271019 and 20576027), Natural Science Foundation of Heilongjiang Prov-ince(Grant No.B200504), Postdoctoral Foundationof Heilongjiang Province(Grant No.LBH-Z05066) and Education Department Foundation of Hei-longjiang Province(Grant No.11511270).
文摘Iron-based perovskite-type compounds modified by Ru were prepared through sol-gel process to study its catalytic activity of NOx direct decomposition at low temperature and evaluate the conversion of NO under the experimental conditions. The catalytic activity of La 0.9Ce 0.1Fe 0.8-nCo 0.2RunO3 （n=0.01,0.03,0.05,0.07,0.09）series for the NO, NO-CO two components, CO-HC-NO three components were also analyzed. The catalytic investigation evidenced that the presence of Ru is necessary for making highly activity in decomposition of nitric oxide even at low temperature（400 ℃）and La 0.9Ce 0.9Fe 0.75Co 0.2Ru 0.05O3 （n=0.05） has better activity in all the samples, the conversion of it is 58.5%. With the reducing gas（CO,C3H6）added into the gas, the catalyst displayed very high activity in decomposition of NO and the conversion of it is 80% and 92.5% separately.
文摘The effect of rare earth metals(REM)on the characteristics of auto-tempering and decomposition of martensite for low-carbon and low-alloy steels(20SiMn2V and 20SiMn2VRE)was investigated using TEM,dilatometer and microhardness test.Results show that both ε.and θ carbides,during auto-tempering, may precipitate from the low-carbon martensite matrix at the same time in the 20SiMn2V steel,however,the precipitation of the ε-carbides can be inhibited by the REM contained in the 20SiMn2 VRE steel,resulting in change of the type of precipitated carbides and decrease of the extent of auto-tempering.The“in-situ”ob- servations show that the decomposition of martensite is also inhibited by the REM contained in the 20SiMn2 VRE steel during low temperature tempering.
基金financially supported by the National Key R&D Program of China(No.2018YFC0604702)the National Natural Science Foundation of China(No.51774284).
文摘Based on the problems caused by many oxygen-containing functional groups and poor floatability on the surface of low rank coal,the characteristics of low rank coal were analyzed systematically by means of scanning electron microscopy(SEM),X-ray diffraction(XRD)and X-Ray photoelectron spectroscopy(XPS)techniques.The bubble-particle induction time was used to determine the characterization of the bubble-particle attachment,and the bubble-particle attachment of low rank coal modified by soaking the coal samples in an acid or alkaline solution was analyzed.The floatability of the modified coal surface was verified by flotation tests.The results show that the particle size of 0.125–0.074 mm of the coal sample exhibited better bubble-particle attachment characteristics.The small bubble,the larger approach velocity of bubble and the larger bubble deformation were more helpful to enhance the bubbleparticle attachment.For an acid solution,the smaller the p H was and the longer the soaking time was,the better the floatability of the coal sample and the higher the combustible material recovery were.The combustible material recovery of low rank coal was increased to 78.79%by soaking the sample in an acid solution of pH=0 for 180 min.On the contrary there was a best concentration for the alkaline solution.
基金financial support from the Basic Fund for the Scientific Research and Operation of Central Universities of China (No. 2009KH10
文摘A series of char samples were derived from pyrolysis of two typical low-rank coals in China （Shengli lig- nite and Shenmu bituminous coal） at low, medium and fast heating rates, respectively, to the same pyrol- ysis temperature 750℃. Then these chars were characterized by means of thermogravimetric analysis and Fourier transform infrared spectrometer with the aim to investigate the influence of heating rate in pyrolysis process on gasification reactivity and surface chemistry of them. Besides, a homogeneous model was used to quantitatively analyze the activation energy of gasification reaction. The results reveal that Shengli lignite and its derived chars behave higher gasification reactivity and have less content of oxygen functional groups than Shenmu coal and chars. Meanwhile, chars derived from Shengli lignite at 50℃/min and Shenmu coal at 200℃/min have the greatest gasification reactivity, respectively. The oxygen functional groups in Shengli lignite are easily thermo-decomposed, and they are less affected by the heating rate, while that in Shenmu coal have a significant change with the variation of heating rate. In addition, there is no good correlation between the change of oxygen functional groups and that of the gasification reactivity of the derived chars from pyrolysis at different heating rates.
基金Supported by the National Natural Science Foundation of China （50874107） the Guizhou Science and Technology Fund （Qiankehe J zi [2012]2306）+1 种基金 the Guizhou High-level Talent Special Assistant Fund （TZJF-2011-04） the Guizhou Research Laboratory Platform of Clean and Efficient Use of Coal Resources （Qianke Platform [2011] 4003）
文摘The pretreatment of low rank coal with nitric acid oxidation can promote its bio-liquefaction. However, the detailed mechanism of which remains an unresolved problem. In the present work, the characteristics of Fushun coal before and after oxidation by nitric acid were investigated combined with elemental composition, pore volume and pore size, Zeta potential, FT-IR, and 13C solid NMR spectrum analysis. The results show that the inorganic substance inlaid in coal are dissolved by ni- tric acid, which results in the decrease of coal ash content and increase of pore volume and pore size. Furthermore, there exist obvious chemical reactions between nitric acid and the functional groups of coal including aromatic ring carboxylation, side chain alkyl of aromatic ring oxidation and aromatic ring nitration. Among these reactions, some led to the increase in content of carboxyl, aliphatic carbon connected with O and humic acid carbon, while others caused the reduction of aromaticity, methyl carbon, substituted aryl carbon and side chain.
基金supported by the National Natural Science Foundation of China(No.41302131)the Special Fund for Fostering Major Projects at the China University of Mining and Technology(No.2014ZDP03)the Fundamental Research Funds for the Central Universities(No.2012QNB32)
文摘Laojunmiao coal samples from the eastern Junggar basin were studied to understand the relationship between coal resistivity and the physical parameters of coal reservoirs under high temperatures and pressures.Specifically,we analysed the relationship of coal resistivity to porosity and permeability via heating and pressurization experiments.The results indicated that coal resistivity decreases exponentially with increasing pressure.Increasing the temperature decreases the resistivity.The sensitivity of coal resistivity to the confining pressure is worse when the temperature is higher.The resistivity of dry coal samples was linearly related to φ~m.Increasing the temperature decreased the cementation exponent(m).Increasing the confining pressure exponentially decreases the porosity.Decreasing the pressure increases the resistivity and porosity for a constant temperature.Increasing the temperature yields a quadratic relationship between the resistivity and permeability for a constant confining pressure.Based on the Archie formula,we obtained the coupling relationship between coal resistivity and permeability for Laojunmiao coal samples at different temperatures and confining pressures.
基金financially supported by the National Natural Science Foundation of China (No. 51574023)
文摘The high-value utilization of low-rank coal would allow for expanding energy sources,improving energy efficiencies,and alleviating environmental issues.In order to use low-rank coal effectively,the hypercoals(HPCs)were co-extracted from two types of low-rank coal and biomass via N-methyl-2-purrolidinone(NMP)under mild conditions.The structures of the HPCs and residues were characterized by proximate and ultimate analysis,Raman spectra,and Fourier transform infrared(FT-IR)spectra.The carbon structure changes within the raw coals and HPCs were discussed.The individual thermal dissolution of Xibu(XB)coal,Guandi(GD)coal,and the biomass demonstrated that the biomass provided the lowest thermal dissolution yield Y1 and the highest thermal soluble yield Y2 at 280℃,and the ash content of three HPCs decreased as the extraction temperature rose.Co-thermal extractions in NMP at various coal/biomass mass ratios were performed,demonstrating a positive synergic effect for Y2 in the whole coal/biomass mass ratios.The maximum value of Y2 was 52.25wt% for XB coal obtained with a XB coal/biomass of 50wt% biomass.The maximum value of Y2 was 50.77wt% for GD coal obtained with a GD coal/biomass of 1:4.The difference for the optimal coal/biomass mass ratios between XB and GD coals could be attributed to the different co-extraction mechanisms for this two type coals.
基金Supported by National High-tech Research and Development Program of China(2011AA05A2021)the National Natural Science Foundation of China(21536009)Science and Technology Plan Projects of Shaanxi Province(2017ZDCXL-GY-10-03).
文摘To reasonably utilize the coal direct liquefaction residue(DLR), contrasting research on the co-pyrolysis between different low-rank coals and DLR was investigated using a TGA coupled with an FT-IR spectrophotometer and a fixed-bed reactor. GC–MS, FTIR, and XRD were used to explore the reaction mechanisms of the various co-pyrolysis processes. Based on the TGA results, it was confirmed that the tetrahydrofuran insoluble fraction of DLR helped to catalyze the conversion reaction of lignite. Also, the addition of DLR improved the yield of tar in the fixed-bed, with altering the composition of the tar. Moreover, a kinetic analysis during the co-pyrolysis was conducted using a distributed activation energy model. The co-pyrolysis reactions showed an approximate double-Gaussian distribution.
