The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the p...The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the popular optimal function coefficient(OFC),sphere cap harmonic analysis(SCHA),kriging and inverse distance weighting(IDW)interpolation in ZTD spatial prediction and Beidou satellite navigation system(BDS)-PPP augmentation over China.For ZTD spatial prediction,the average time consumption of the OFC,kriging,and IDW methods is less than 0.1 s,which is significantly better than that of the SCHA method(63.157 s).The overall ZTD precision of the OFC is 3.44 cm,which outperforms those of the SCHA(9.65 cm),Kriging(10.6 cm),and IDW(11.8 cm)methods.We confirmed that the low performance of kriging and IDW is caused by their weakness in modelling ZTD variation in the vertical direction.To mitigate such deficiencies,an elevation normalization factor(ENF)is introduced into the kriging and IDW models(kriging-ENF and IDW-ENF).The overall ZTD spatial prediction accuracies of IDW-ENF and kriging-ENF are 2.80 cm and 2.01 cm,respectively,which are both superior to those of the OFC and the widely used empirical model GPT3(4.92 cm).For BDS-PPP enhancement,the ZTD provided by the kriging-ENF,IDW-ENF and OFC as prior constraints can effectively reduce the convergence time.Compared with unconstrained BDS-PPP,our proposed kriging-ENF outperforms IDW-ENF and OFC by reducing the horizontal and vertical convergence times by approximately 13.2%and 5.8%in Ningxia and 30.4%and 7.84%in Guangdong,respectively.These results indicate that kriging-ENF is a promising method for ZTD spatial prediction and BDS-PPP enhancement over China.展开更多
1 Introduction Potassium is listed as one of the shortage of mineral resources in china.Geophysical and remote sensing technology plays an important role in prospecting for potash ressources.
There are many long-term and short-term prediction methods of Total Electron Content(TEC)that need to be tested for each specific region.Recently,much attention has been paid to testing TEC models in high-,low-latitud...There are many long-term and short-term prediction methods of Total Electron Content(TEC)that need to be tested for each specific region.Recently,much attention has been paid to testing TEC models in high-,low-latitude and equatorial regions.This paper compares the TEC prediction methods in the midlatitude zone according to the data of the Juliusruh,Rostov,Manzhouli stations in 2008 and 2015.For a long-term prediction,the IRI-Plas and Ne Quick models are compared with the Global Ionospheric Maps(GIM)presented by the Jet Propulsion Laboratory(JPL)and the Technical University of Catalonia(UPC).For a short-term prediction,the Standard Persistence Model(SPM)method,a 27 day median model,and the proposed short-term prediction method are compared for one day ahead.It is shown that for all stations the IRI-Plas model provides better compliance with GIM maps than the Ne Quick model irrespective of a solar activity level.An average absolute error lays in the range of 3 e3.5 TECU,relative root square mean(RMS)error in the range of 22 e27%in 2015 and 1.7 e2 TECU,20 e25%in 2008.For the Ne Quick model,these estimates were 6.7 e8.2 TECU and 42 e45%in 2015 and 2.2 e3.6 TECU,30 e37%in2008.For the short-term forecast,the best results were obtained by the SPM method with an average absolute error in the range of 1.95 e2.15 TECU in 2015 and 0.59 e0.98 TECU in 2008,a relative RMS error in the range of 17 e21%in 2015,11.5 e15%in 2008.For the proposed short-term prediction method,these errors were 2.04 e2.2 TECU and 12 e14%in 2015 and 0.7 e1.0 TECU,7 e11%in 2008.Using medians,the errors were 3.1 e3.4 TECU and 17 e21%in 2015 and 1.0 e1.3 TECU,10 e15%in 2008.The dependence of results on the Dst-index was obtained.展开更多
This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was...This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was established for water and mud inrush in tunnels by analyzing advanced prediction data for specifi c tunnel segments.Additionally,the indicator weights were determined using the analytic hierarchy process combined with the Huber weighting method.Subsequently,a multisource data decision-layer fusion algorithm was utilized to generate fused imaging results for tunnel water and mud inrush risk predictions.Meanwhile,risk analysis was performed for different tunnel sections to achieve spatial and temporal complementarity within the indicator system and optimize redundant information.Finally,model feasibility was validated using the CZ Project Sejila Mountain Tunnel segment as a case study,yielding favorable risk prediction results and enabling effi cient information fusion and support for construction decision-making.展开更多
Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with C...Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with CGO incidents under low gas pressure conditions.In pursuit of this objective,we have studied and established a mechanical model of the working face under abnormal stress and the excitation energy conditions of CGO,and proposed a method for predicting the risk of CGO under abnormal stress.On site application verification shows that when a strong outburst hazard level prediction is issued,there is a high possibility of outburst disasters occurring.In one of the three locations where we predicted strong outburst hazards,a small outburst occurred,and the accuracy of the prediction was higher than the traditional drilling cuttings index S and drilling cuttings gas desorption index q.Finally,we discuss the mechanism of CGO under the action of stress anomalies.Based on the analysis of stress distribution changes and energy accumulation characteristics of coal under abnormal stress,this article believes that the increase in outburst risk caused by high stress abnormal gradient is mainly due to two reasons:(1)The high stress abnormal gradient leads to an increase in the plastic zone of the coal seam.After the working face advances,it indirectly leads to an increase in the gas expansion energy that can be released from the coal seam before reaching a new stress equilibrium.(2)Abnormal stress leads to increased peak stress of coal body in front of working face.When coal body in elastic area transforms to plastic area,its failure speed is accelerated,which induces accelerated gas desorption and aggravates the risk of outburst.展开更多
Wellbore instability is one of the significant challenges in the drilling engineering and during the development of carbonate reservoirs,especially with open-hole completion.The problems of wellbore instability such a...Wellbore instability is one of the significant challenges in the drilling engineering and during the development of carbonate reservoirs,especially with open-hole completion.The problems of wellbore instability such as downhole collapse and silt deposit in the fractured carbonate reservoir of Tarim Basin(Ordovician)are severe.Solid destabilization and production(SDP)was proposed to describe this engineering problem of carbonate reservoirs.To clarify the mechanism and mitigate potential borehole instability problems,we conducted particle size distribution(PSD)analysis,X-ray diffraction(XRD)analysis,triaxial compression tests,and micro-scale sand production tests based on data analysis.We found that the rock fragments and silt in the wellbore came from two sources:one from the wellbore collapse in the upper unplugged layers and the other from the production of sand particles carried by the fluid in the productive layers.Based on the experimental study,a novel method combining a geomechanical model and microscopic sand production model was proposed to predict wellbore instability and analyze its influencing factors.The critical condition and failure zone predicted by the prediction model fit well with the field observations.According to the prediction results,the management and prevention measures of wellbore instability in carbonate reservoirs were proposed.It is suggested to optimize the well track in new drilling wells while upgrading the production system in old wells.This study is of great guiding significance for the optimization of carbonate solid control and it improves the understanding of the sand production problems in carbonate reservoirs.展开更多
In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data,analysis of va...In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data,analysis of variance （ANOVA）was first used to study the influence of different factors on pavement rutting. Cluster analysis was then employed to investigate the rutting development trend.Based on the clustering results,the grey theory was applied to build pavement rutting models for each cluster, which can effectively reduce the complexity of the predictive model.The results show that axial load and asphalt binder type play important roles in rutting development.The prediction model is capable of capturing the uncertainty in the pavement performance prediction process and can meet the requirements of highway pavement maintenance,and,therefore,has a wide application prospects.展开更多
The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
The discovery of intrinsically disordered proteins （IDP） （i.e., biologically active proteins that do not possess stable secondary and/or tertiary structures） came as an unexpected surprise, as the existence of suc...The discovery of intrinsically disordered proteins （IDP） （i.e., biologically active proteins that do not possess stable secondary and/or tertiary structures） came as an unexpected surprise, as the existence of such proteins is in contradiction to the traditional ＂sequence →structure →function＂ paradigm. Accurate prediction of a protein＇s predisposition to be intrinsically disordered is a necessary prerequisite for the further understanding of principles and mechanisms of protein folding and function, and is a key for the elaboration of a new structural and functional hierarchy of proteins. Therefore, prediction of IDPs has attracted the attention of many researchers, and a number of prediction tools have been developed. Predictions of disorder, in turn, are playing major roles in directing laboratory experiments that are leading to the discovery of ever more disordered proteins, and thereby leading to a positive feedback loop in the investigation of these proteins. In this review of algorithms for intrinsic disorder prediction, the basic concepts of various prediction methods for IDPs are summarized, the strengths and shortcomings of many of the methods are analyzed, and the difficulties and directions of future development of IDP prediction techniques are discussed.展开更多
In the process of using the original key stratum theory to predict the height of a water-flowing fractured zone(WFZ),the influence of rock strata outside the calculation range on the rock strata within the calculation...In the process of using the original key stratum theory to predict the height of a water-flowing fractured zone(WFZ),the influence of rock strata outside the calculation range on the rock strata within the calculation range as well as the fact that the shape of the overburden deformation area will change with the excavation length are ignored.In this paper,an improved key stratum theory(IKS theory)was proposed by fixing these two shortcomings.Then,a WFZ height prediction method based on IKS theory was established and applied.First,the range of overburden involved in the analysis was determined according to the tensile stress distribution range above the goaf.Second,the key stratum in the overburden involved in the analysis was identified through IKS theory.Finally,the tendency of the WFZ to develop upward was determined by judging whether or not the identified key stratum will break.The proposed method was applied and verified in a mining case study,and the reasons for the differences in the development patterns between the WFZs in coalfields in Northwest and East China were also fully explained by this method.展开更多
This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modif...This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.展开更多
Obtaining accurate development cost estimation results of general aviation aircraft is crucial for companies to adopt the best strategy in the development process.To address this problem,this paper proposes a combinat...Obtaining accurate development cost estimation results of general aviation aircraft is crucial for companies to adopt the best strategy in the development process.To address this problem,this paper proposes a combination of three commonly used single prediction methods.The optimal weight values of the three single prediction methods are determined by utilizing the shortest ideal point method.Ten cost datasets collected from literature are utilized for fitting and testing the combined prediction method,and the weight coefficients of the three individual prediction methods are calculated as 0.6859,0.0035 and 0.3106,respectively.The results of this study indicate that the developed method has better fitting and estimation accuracy than that of the three individual methods,with average fitting and predicting error values of 2.60%and 6.43%,respectively.Additionally,the cost data of military and civil aircraft development from literature are collected for verification.The results further confirm that the proposed method is not only superior to the single prediction methods in terms of high precision but has wider applications.More importantly,this research can provide important reference for general aviation aircraft companies in term of product cost planning and corporate sales strategies.展开更多
The investigation on fatigue lives of reinforced concrete （RC） structures strength- ened with fiber laminate under random loading is important for the repairing or the strengthening of bridges and the safety of the ...The investigation on fatigue lives of reinforced concrete （RC） structures strength- ened with fiber laminate under random loading is important for the repairing or the strengthening of bridges and the safety of the traffic. In this paper, two methods are developed for predicting the fatigue lives of RC structures strengthened with carbon fiber [aminate （CFL） under random loading based on a residual life and a residual strength model. To discuss the efficiency of the model, 12 RC beams strengthened with CFL are tested under random loading by the MTS810 testing system. The predicted residual strength approximately agrees with test results.展开更多
The nonlinear cumulative damage model is modified to have high prediction accuracy when the high-low cycle stress frequency ratio m is large(m500).The low cycle fatigue(LCF)tests,high cycle fatigue(HCF)tests and combi...The nonlinear cumulative damage model is modified to have high prediction accuracy when the high-low cycle stress frequency ratio m is large(m500).The low cycle fatigue(LCF)tests,high cycle fatigue(HCF)tests and combined high and low cycle fatigue(CCF)tests of TC11 titanium alloy were carried out,and the influencing factors of CCF life were analysed.The CCF life declines with the decrease of the ratio of high-low cycle stress frequency m.Both linear and nonlinear cumulative damage models are used to predict the CCF life.The CCF life prediction error of the linear cumulative damage model is great and the predictions tend to be overestimated,which is dangerous for engineering application.The accuracy is relatively high when the high-low cycle stress frequency ratio m500.The accuracy of nonlinear cumulative damage model is higher than that of linear model when the high-low cycle stress frequency ratio m500.Based on the relationship between high cycle average stress rmajor and material yield limit rp,0.2,a correction term is added to the nonlinear cumulative damage model and verified,which made the modified model more accurate when m500.展开更多
Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionl...Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.展开更多
Twitter sentiment has been shown to be useful in predicting whether Bitcoin’s price will increase or decrease.Yet the state-of-the-art is limited to predicting the price direction and not the magnitude of increase/de...Twitter sentiment has been shown to be useful in predicting whether Bitcoin’s price will increase or decrease.Yet the state-of-the-art is limited to predicting the price direction and not the magnitude of increase/decrease.In this paper,we seek to build on the state-of-the-art to not only predict the direction yet to also predict the magnitude of increase/decrease.We utilise not only sentiment extracted from tweets,but also the volume of tweets.We present results from experiments exploring the relation between sentiment and future price at different temporal granularities,with the goal of discovering the optimal time interval at which the sentiment expressed becomes a reliable indicator of price change.Two different neural network models are explored and evaluated,one based on recurrent nets and one based on convolutional networks.An additional model is presented to predict the magnitude of change,which is framed as a multi-class classification problem.It is shown that this model yields more reliable predictions when used alongside a price trend prediction model.The main research contribution from this paper is that we demonstrate that not only can price direction prediction be made but the magnitude in price change can be predicted with relative accuracy(63%).展开更多
This study presents the classification and prediction of severity for brittle rock failure,focusing on failure behaviors and excessive determination based on damage depth.The research utilizes extensive field survey d...This study presents the classification and prediction of severity for brittle rock failure,focusing on failure behaviors and excessive determination based on damage depth.The research utilizes extensive field survey data from the Shuangjiangkou Hydropower Station and previous research findings.Based on field surveys and previous studies,four types of brittle rock failure with different failure mechanisms are classified,and then a prediction method is proposed.This method incorporates two variables,i.e.Kv(modified rock mass integrity coefficient)and GSI(geological strength index).The prediction method is applied to the first layer excavation of the powerhouse cavern of Shuangjiangkou Hydropower Station.The results show that the predicted brittle rock failure area agrees with the actual failure area,demonstrating the method’s applicability.Next,it extends to investigate brittle rock failure in two locations.The first is the k0-890 m section of the traffic cavern,and the second one is at K0-64 m of the main powerhouse.The criterion-based prediction indicates a severity brittle rock failure in the K0-890 m section,and a moderate brittle rock failure in the K0-64 m section,which agrees with the actual occurrence of brittle rock failure in the field.The understanding and application of the prediction method using Kv and GSI are vital for implementing a comprehensive brittle rock failure prediction process in geological engineering.To validate the adaptability of this criterion across diverse tunnel projects,a rigorous verification process using statistical findings was conducted.The assessment outcomes demonstrate high accuracy for various tunnel projects,allowing establishment of the correlations that enable valuable conclusions regarding brittle rock failure occurrence.Further validation and refinement through field and laboratory testing,as well as simulations,can broaden the contribution of this method to safer and more resilient underground construction.展开更多
This paper proposes a new method to predict the corona onset voltage for a rod- plane air gap, based on the support vector machine （SVM）. Because the SVM is not limited by the size, dimension and nonlinearity of the...This paper proposes a new method to predict the corona onset voltage for a rod- plane air gap, based on the support vector machine （SVM）. Because the SVM is not limited by the size, dimension and nonlinearity of the samples, this method can realize accurate prediction with few training data. Only electric field features are chosen as the input; no geometric parameter is included. Therefore, the experiment data of one kind of electrode can be used to predict the corona onset voltages of other electrodes with different sizes. With the experimental data obtained by ozone detection technology, and experimental data provided by the reference, the efficiency of the proposed method is validated. Accurate predicted results with an average relative less than 3% are obtained with only 6 experimental data.展开更多
To describe the complex phase transformation in the process of depletion exploitation of volatile oil reservoir,four fluid phases are defined,and production and remaining volume of these phases are calculated based on...To describe the complex phase transformation in the process of depletion exploitation of volatile oil reservoir,four fluid phases are defined,and production and remaining volume of these phases are calculated based on the principle of surface volume balance,then the recovery prediction method of volatile oil reservoir considering the influence of condensate content in released solution gas and the correction method of multiple degassing experiments data are established.Taking three typical kinds of crude oil(black oil,medium-weak volatile oil,strong volatile oil)as examples,the new improved method is used to simulate constant volume depletion experiments based on the corrected data of multiple degassing experiment to verify the reliability of the modified method.By using"experimental data and traditional method","corrected data and traditional method"and"corrected data and modified method",recovery factors of these three typical kinds of oil are calculated respectively.The source of parameters and the calculation methods have little effect on the recovery of typical black oil.However,with the increase of crude oil volatility,the oil recovery will be seriously underestimated by using experimental data or traditional method.The combination of"corrected data and modified method"considers the influence of condensate in gas phase in both experimental parameters and calculation method,and has good applicability to typical black oil and volatile oil.The strong shrinkage of volatile oil makes more"liquid oil"convert to"gaseous oil",so volatile oil reservoir can reach very high oil recovery by depletion drive.展开更多
基金co-supported by the National Nature Science Foundation of China(No.12303071)the Shanghai Science and Technology Plan Project,China(No.23YF1455500)+1 种基金the China Postdoctoral Science Foundation(No.2023M743653)Ministry of Industry and Information Technology of China through the High Precision Timing Service Project(No.TC220A04A-80)。
文摘The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the popular optimal function coefficient(OFC),sphere cap harmonic analysis(SCHA),kriging and inverse distance weighting(IDW)interpolation in ZTD spatial prediction and Beidou satellite navigation system(BDS)-PPP augmentation over China.For ZTD spatial prediction,the average time consumption of the OFC,kriging,and IDW methods is less than 0.1 s,which is significantly better than that of the SCHA method(63.157 s).The overall ZTD precision of the OFC is 3.44 cm,which outperforms those of the SCHA(9.65 cm),Kriging(10.6 cm),and IDW(11.8 cm)methods.We confirmed that the low performance of kriging and IDW is caused by their weakness in modelling ZTD variation in the vertical direction.To mitigate such deficiencies,an elevation normalization factor(ENF)is introduced into the kriging and IDW models(kriging-ENF and IDW-ENF).The overall ZTD spatial prediction accuracies of IDW-ENF and kriging-ENF are 2.80 cm and 2.01 cm,respectively,which are both superior to those of the OFC and the widely used empirical model GPT3(4.92 cm).For BDS-PPP enhancement,the ZTD provided by the kriging-ENF,IDW-ENF and OFC as prior constraints can effectively reduce the convergence time.Compared with unconstrained BDS-PPP,our proposed kriging-ENF outperforms IDW-ENF and OFC by reducing the horizontal and vertical convergence times by approximately 13.2%and 5.8%in Ningxia and 30.4%and 7.84%in Guangdong,respectively.These results indicate that kriging-ENF is a promising method for ZTD spatial prediction and BDS-PPP enhancement over China.
基金financially supported by projects of 2006AA06A208, 2013AA0639, 1212011120188 and 12120113099000
文摘1 Introduction Potassium is listed as one of the shortage of mineral resources in china.Geophysical and remote sensing technology plays an important role in prospecting for potash ressources.
文摘There are many long-term and short-term prediction methods of Total Electron Content(TEC)that need to be tested for each specific region.Recently,much attention has been paid to testing TEC models in high-,low-latitude and equatorial regions.This paper compares the TEC prediction methods in the midlatitude zone according to the data of the Juliusruh,Rostov,Manzhouli stations in 2008 and 2015.For a long-term prediction,the IRI-Plas and Ne Quick models are compared with the Global Ionospheric Maps(GIM)presented by the Jet Propulsion Laboratory(JPL)and the Technical University of Catalonia(UPC).For a short-term prediction,the Standard Persistence Model(SPM)method,a 27 day median model,and the proposed short-term prediction method are compared for one day ahead.It is shown that for all stations the IRI-Plas model provides better compliance with GIM maps than the Ne Quick model irrespective of a solar activity level.An average absolute error lays in the range of 3 e3.5 TECU,relative root square mean(RMS)error in the range of 22 e27%in 2015 and 1.7 e2 TECU,20 e25%in 2008.For the Ne Quick model,these estimates were 6.7 e8.2 TECU and 42 e45%in 2015 and 2.2 e3.6 TECU,30 e37%in2008.For the short-term forecast,the best results were obtained by the SPM method with an average absolute error in the range of 1.95 e2.15 TECU in 2015 and 0.59 e0.98 TECU in 2008,a relative RMS error in the range of 17 e21%in 2015,11.5 e15%in 2008.For the proposed short-term prediction method,these errors were 2.04 e2.2 TECU and 12 e14%in 2015 and 0.7 e1.0 TECU,7 e11%in 2008.Using medians,the errors were 3.1 e3.4 TECU and 17 e21%in 2015 and 1.0 e1.3 TECU,10 e15%in 2008.The dependence of results on the Dst-index was obtained.
基金supported by the National Natural Science Foundation of China (grant numbers 42293351, and U2468221)。
文摘This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was established for water and mud inrush in tunnels by analyzing advanced prediction data for specifi c tunnel segments.Additionally,the indicator weights were determined using the analytic hierarchy process combined with the Huber weighting method.Subsequently,a multisource data decision-layer fusion algorithm was utilized to generate fused imaging results for tunnel water and mud inrush risk predictions.Meanwhile,risk analysis was performed for different tunnel sections to achieve spatial and temporal complementarity within the indicator system and optimize redundant information.Finally,model feasibility was validated using the CZ Project Sejila Mountain Tunnel segment as a case study,yielding favorable risk prediction results and enabling effi cient information fusion and support for construction decision-making.
基金supported by the National Natural Science Foundation of China(52174162)the Fundamental Research Funds for the Central Universities(FRF-TP-20-002A3).
文摘Accurate prediction of coal and gas outburst(CGO)hazards is paramount in gas disaster prevention and control.This paper endeavors to overcome the constraints posed by traditional prediction indexes when dealing with CGO incidents under low gas pressure conditions.In pursuit of this objective,we have studied and established a mechanical model of the working face under abnormal stress and the excitation energy conditions of CGO,and proposed a method for predicting the risk of CGO under abnormal stress.On site application verification shows that when a strong outburst hazard level prediction is issued,there is a high possibility of outburst disasters occurring.In one of the three locations where we predicted strong outburst hazards,a small outburst occurred,and the accuracy of the prediction was higher than the traditional drilling cuttings index S and drilling cuttings gas desorption index q.Finally,we discuss the mechanism of CGO under the action of stress anomalies.Based on the analysis of stress distribution changes and energy accumulation characteristics of coal under abnormal stress,this article believes that the increase in outburst risk caused by high stress abnormal gradient is mainly due to two reasons:(1)The high stress abnormal gradient leads to an increase in the plastic zone of the coal seam.After the working face advances,it indirectly leads to an increase in the gas expansion energy that can be released from the coal seam before reaching a new stress equilibrium.(2)Abnormal stress leads to increased peak stress of coal body in front of working face.When coal body in elastic area transforms to plastic area,its failure speed is accelerated,which induces accelerated gas desorption and aggravates the risk of outburst.
基金financially supported by the National Natural Science Foundation of China(Grant No.52074331).
文摘Wellbore instability is one of the significant challenges in the drilling engineering and during the development of carbonate reservoirs,especially with open-hole completion.The problems of wellbore instability such as downhole collapse and silt deposit in the fractured carbonate reservoir of Tarim Basin(Ordovician)are severe.Solid destabilization and production(SDP)was proposed to describe this engineering problem of carbonate reservoirs.To clarify the mechanism and mitigate potential borehole instability problems,we conducted particle size distribution(PSD)analysis,X-ray diffraction(XRD)analysis,triaxial compression tests,and micro-scale sand production tests based on data analysis.We found that the rock fragments and silt in the wellbore came from two sources:one from the wellbore collapse in the upper unplugged layers and the other from the production of sand particles carried by the fluid in the productive layers.Based on the experimental study,a novel method combining a geomechanical model and microscopic sand production model was proposed to predict wellbore instability and analyze its influencing factors.The critical condition and failure zone predicted by the prediction model fit well with the field observations.According to the prediction results,the management and prevention measures of wellbore instability in carbonate reservoirs were proposed.It is suggested to optimize the well track in new drilling wells while upgrading the production system in old wells.This study is of great guiding significance for the optimization of carbonate solid control and it improves the understanding of the sand production problems in carbonate reservoirs.
基金The Major Scientific and Technological Special Project of Jiangsu Provincial Communications Department(No.2011Y/02-G1)
文摘In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data,analysis of variance （ANOVA）was first used to study the influence of different factors on pavement rutting. Cluster analysis was then employed to investigate the rutting development trend.Based on the clustering results,the grey theory was applied to build pavement rutting models for each cluster, which can effectively reduce the complexity of the predictive model.The results show that axial load and asphalt binder type play important roles in rutting development.The prediction model is capable of capturing the uncertainty in the pavement performance prediction process and can meet the requirements of highway pavement maintenance,and,therefore,has a wide application prospects.
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
文摘The discovery of intrinsically disordered proteins （IDP） （i.e., biologically active proteins that do not possess stable secondary and/or tertiary structures） came as an unexpected surprise, as the existence of such proteins is in contradiction to the traditional ＂sequence →structure →function＂ paradigm. Accurate prediction of a protein＇s predisposition to be intrinsically disordered is a necessary prerequisite for the further understanding of principles and mechanisms of protein folding and function, and is a key for the elaboration of a new structural and functional hierarchy of proteins. Therefore, prediction of IDPs has attracted the attention of many researchers, and a number of prediction tools have been developed. Predictions of disorder, in turn, are playing major roles in directing laboratory experiments that are leading to the discovery of ever more disordered proteins, and thereby leading to a positive feedback loop in the investigation of these proteins. In this review of algorithms for intrinsic disorder prediction, the basic concepts of various prediction methods for IDPs are summarized, the strengths and shortcomings of many of the methods are analyzed, and the difficulties and directions of future development of IDP prediction techniques are discussed.
基金supported by the Key Projects of Natural Science Foundation of China(No.41931284)the Scientific Research Start-Up Fund for High-Level Introduced Talents of Anhui University of Science and Technology(No.2022yjrc21).
文摘In the process of using the original key stratum theory to predict the height of a water-flowing fractured zone(WFZ),the influence of rock strata outside the calculation range on the rock strata within the calculation range as well as the fact that the shape of the overburden deformation area will change with the excavation length are ignored.In this paper,an improved key stratum theory(IKS theory)was proposed by fixing these two shortcomings.Then,a WFZ height prediction method based on IKS theory was established and applied.First,the range of overburden involved in the analysis was determined according to the tensile stress distribution range above the goaf.Second,the key stratum in the overburden involved in the analysis was identified through IKS theory.Finally,the tendency of the WFZ to develop upward was determined by judging whether or not the identified key stratum will break.The proposed method was applied and verified in a mining case study,and the reasons for the differences in the development patterns between the WFZs in coalfields in Northwest and East China were also fully explained by this method.
基金Project(51675061)supported by the National Natural Science Foundation of China。
文摘This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.
基金the National Postdoctoral Program for Innovative Talents,Postdoctoral Science Foundation of China(No.2017M610740)the supports from Hefei General Aviation Research Institute,Beihang University。
文摘Obtaining accurate development cost estimation results of general aviation aircraft is crucial for companies to adopt the best strategy in the development process.To address this problem,this paper proposes a combination of three commonly used single prediction methods.The optimal weight values of the three single prediction methods are determined by utilizing the shortest ideal point method.Ten cost datasets collected from literature are utilized for fitting and testing the combined prediction method,and the weight coefficients of the three individual prediction methods are calculated as 0.6859,0.0035 and 0.3106,respectively.The results of this study indicate that the developed method has better fitting and estimation accuracy than that of the three individual methods,with average fitting and predicting error values of 2.60%and 6.43%,respectively.Additionally,the cost data of military and civil aircraft development from literature are collected for verification.The results further confirm that the proposed method is not only superior to the single prediction methods in terms of high precision but has wider applications.More importantly,this research can provide important reference for general aviation aircraft companies in term of product cost planning and corporate sales strategies.
基金supported by the National Natural Science Foundation of China(No.10672060)the Guangdong Provincial Nature Science Foundation of China(No.07006538).
文摘The investigation on fatigue lives of reinforced concrete （RC） structures strength- ened with fiber laminate under random loading is important for the repairing or the strengthening of bridges and the safety of the traffic. In this paper, two methods are developed for predicting the fatigue lives of RC structures strengthened with carbon fiber [aminate （CFL） under random loading based on a residual life and a residual strength model. To discuss the efficiency of the model, 12 RC beams strengthened with CFL are tested under random loading by the MTS810 testing system. The predicted residual strength approximately agrees with test results.
基金This study was co-supported by the National Natural Science Foundation of China(No.51301090).
文摘The nonlinear cumulative damage model is modified to have high prediction accuracy when the high-low cycle stress frequency ratio m is large(m500).The low cycle fatigue(LCF)tests,high cycle fatigue(HCF)tests and combined high and low cycle fatigue(CCF)tests of TC11 titanium alloy were carried out,and the influencing factors of CCF life were analysed.The CCF life declines with the decrease of the ratio of high-low cycle stress frequency m.Both linear and nonlinear cumulative damage models are used to predict the CCF life.The CCF life prediction error of the linear cumulative damage model is great and the predictions tend to be overestimated,which is dangerous for engineering application.The accuracy is relatively high when the high-low cycle stress frequency ratio m500.The accuracy of nonlinear cumulative damage model is higher than that of linear model when the high-low cycle stress frequency ratio m500.Based on the relationship between high cycle average stress rmajor and material yield limit rp,0.2,a correction term is added to the nonlinear cumulative damage model and verified,which made the modified model more accurate when m500.
基金Project(2011ZX05009-004)supported by the National Science and Technology Major Projects of China
文摘Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.
文摘Twitter sentiment has been shown to be useful in predicting whether Bitcoin’s price will increase or decrease.Yet the state-of-the-art is limited to predicting the price direction and not the magnitude of increase/decrease.In this paper,we seek to build on the state-of-the-art to not only predict the direction yet to also predict the magnitude of increase/decrease.We utilise not only sentiment extracted from tweets,but also the volume of tweets.We present results from experiments exploring the relation between sentiment and future price at different temporal granularities,with the goal of discovering the optimal time interval at which the sentiment expressed becomes a reliable indicator of price change.Two different neural network models are explored and evaluated,one based on recurrent nets and one based on convolutional networks.An additional model is presented to predict the magnitude of change,which is framed as a multi-class classification problem.It is shown that this model yields more reliable predictions when used alongside a price trend prediction model.The main research contribution from this paper is that we demonstrate that not only can price direction prediction be made but the magnitude in price change can be predicted with relative accuracy(63%).
基金the National Natural Science Foundation of China(Nos.41825018,42141009)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0904).
文摘This study presents the classification and prediction of severity for brittle rock failure,focusing on failure behaviors and excessive determination based on damage depth.The research utilizes extensive field survey data from the Shuangjiangkou Hydropower Station and previous research findings.Based on field surveys and previous studies,four types of brittle rock failure with different failure mechanisms are classified,and then a prediction method is proposed.This method incorporates two variables,i.e.Kv(modified rock mass integrity coefficient)and GSI(geological strength index).The prediction method is applied to the first layer excavation of the powerhouse cavern of Shuangjiangkou Hydropower Station.The results show that the predicted brittle rock failure area agrees with the actual failure area,demonstrating the method’s applicability.Next,it extends to investigate brittle rock failure in two locations.The first is the k0-890 m section of the traffic cavern,and the second one is at K0-64 m of the main powerhouse.The criterion-based prediction indicates a severity brittle rock failure in the K0-890 m section,and a moderate brittle rock failure in the K0-64 m section,which agrees with the actual occurrence of brittle rock failure in the field.The understanding and application of the prediction method using Kv and GSI are vital for implementing a comprehensive brittle rock failure prediction process in geological engineering.To validate the adaptability of this criterion across diverse tunnel projects,a rigorous verification process using statistical findings was conducted.The assessment outcomes demonstrate high accuracy for various tunnel projects,allowing establishment of the correlations that enable valuable conclusions regarding brittle rock failure occurrence.Further validation and refinement through field and laboratory testing,as well as simulations,can broaden the contribution of this method to safer and more resilient underground construction.
基金supported by National Natural Science Foundation of China(No.51477120)
文摘This paper proposes a new method to predict the corona onset voltage for a rod- plane air gap, based on the support vector machine （SVM）. Because the SVM is not limited by the size, dimension and nonlinearity of the samples, this method can realize accurate prediction with few training data. Only electric field features are chosen as the input; no geometric parameter is included. Therefore, the experiment data of one kind of electrode can be used to predict the corona onset voltages of other electrodes with different sizes. With the experimental data obtained by ozone detection technology, and experimental data provided by the reference, the efficiency of the proposed method is validated. Accurate predicted results with an average relative less than 3% are obtained with only 6 experimental data.
基金Supported by the China National Science and Technology Major Project(2016ZX05027)。
文摘To describe the complex phase transformation in the process of depletion exploitation of volatile oil reservoir,four fluid phases are defined,and production and remaining volume of these phases are calculated based on the principle of surface volume balance,then the recovery prediction method of volatile oil reservoir considering the influence of condensate content in released solution gas and the correction method of multiple degassing experiments data are established.Taking three typical kinds of crude oil(black oil,medium-weak volatile oil,strong volatile oil)as examples,the new improved method is used to simulate constant volume depletion experiments based on the corrected data of multiple degassing experiment to verify the reliability of the modified method.By using"experimental data and traditional method","corrected data and traditional method"and"corrected data and modified method",recovery factors of these three typical kinds of oil are calculated respectively.The source of parameters and the calculation methods have little effect on the recovery of typical black oil.However,with the increase of crude oil volatility,the oil recovery will be seriously underestimated by using experimental data or traditional method.The combination of"corrected data and modified method"considers the influence of condensate in gas phase in both experimental parameters and calculation method,and has good applicability to typical black oil and volatile oil.The strong shrinkage of volatile oil makes more"liquid oil"convert to"gaseous oil",so volatile oil reservoir can reach very high oil recovery by depletion drive.
