Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment...Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment,the firstproblem to be solved is how to introduce and retain the bacterial cells in the soil,which involves the migration and retention of bacterial cells during the biogrouting process.Soil particle size,a key factor in determining pore throat size,can have a significanteffect on the migration and retention of bacterial cells in the soil and therefore on biomineralization.To investigate the effect of particle size on the migration and retention of bacterial cells in sand and its biomineralization,two sets of tests were carried out in this study,including percolation tests and sand column treatment tests.Soil urease activity(definedas urease activity per unit mass of soil)and calcium carbonate content of the biomineralized sand were measured to comprehensively assess the migration and retention of bacterial cells in the sand.The results indicate that sands with a particle size smaller than 0.25 mmwould inhibit the migration of bacteria in the sand,resulting in a nonuniform distribution of precipitated calcium carbonate and a low strength enhancement of biomineralization.On the other hand,sands with a particle size larger than 1.18 mm are unfavorable for retaining bacterial cells in the sand,resulting in low calcium conversion efficiency.Meanwhile,particle size would also affect the formation of effective calcium carbonate through interparticle contact number and interparticle pore size,and thus biomineralization.展开更多
This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the stre...This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the strength of treated sand.Columns with a diameter of 7.5 cm were constructed using three mixing times(130,190,and 250 s),two execution procedures(normal and zigzag),threeαvalues(300,400,and 500 kg/m^(3)),and three W_(Total)/C ratios(2.5,3.0,and 3.5).For comparison,equivalent laboratory samples were also examined.Results revealed that increasing the mixing time andα,adopting the zigzag execution procedure,and reducing the W_(Total)/C ratio increase E.Outcomes indicated that an increase in E from 0.49-0.70 kJ to 0.70-0.90 kJ,0.90-1.10 kJ,and 1.10-1.40 kJ improves the unconfined compressive strength(UCS)of columns on average by 66%,124%,and 179%,respectively,and the secant modulus by 61%,110%,and 152%.Average strain at maximum stress also rises from 0.68%to 0.75%,0.81%,and 0.84%,respectively.The study identified a threshold in the direct relationship between E and the strength ratio(λ),beyond whichλdid not increase significantly with further increases in E.Additionally,at low and high E levels,DSM samples mainly failed by crushing and cracking modes,respectively.In DSM columns withα=500 kg/m^(3)and W_(Total)/C=2.5,increasing average E from 0.77 kJ to 0.95 kJ,1.08 kJ,and 1.28 kJ resulted in a reduction of coefficients of variation of UCS from 30.4%to 27.8%,24.5%,and 21.1%,respectively.展开更多
To investigate the influencesof non-plastic silt and soil aging on the re-liquefaction resistance of sands,a series of undrained triaxial tests was performed on sand-silt mixtures with finescontent ranging from 0%to 1...To investigate the influencesof non-plastic silt and soil aging on the re-liquefaction resistance of sands,a series of undrained triaxial tests was performed on sand-silt mixtures with finescontent ranging from 0%to 100%,as well as on undisturbed and reconstituted non-plastic sandy soils retrieved from earth structures with a history of earthquake-induced damage.The specimens on sand-silt mixtures were produced under an initial degree of compaction of 95%.In these tests,liquefaction histories were applied three times to a single specimen under the same cyclic stress ratio after the respective consolidation stages with the measurements of the shear wave velocities.The following conclusions can be obtained from the test results:(1)The liquefaction resistance obtained in the firstto third cyclicloading stages decreased initially with increasing finescontent up to about 45%,while it increased afterward.Therefore,the susceptibility of sands containing a relatively large amount of non-plastic silt to reliquefaction may be more significantthan that of clean sands;(2)The liquefaction resistance and the shear wave velocity decreased significantlyduring the second cyclic-loading stage and after the second consolidation,respectively,despite an increase in the specimen density caused by the first liquefaction history,while they increased in the third stage.The possible reason for this change would be the disturbance of soil structures due to liquefaction,which may be partially evaluated by the volumetric strain during the respective consolidation stages,and the stress-induced anisotropy formed in the previous liquefaction stage;and(3)The liquefaction resistance and the shear wave velocity of the undisturbed specimens,which were measured in the firstto third stages,were larger than those of the reconstituted ones due to the aging effects,respectively.That is,the aging effects may not necessarily be eliminated by the subsequent liquefaction history and may remain partially in some cases.展开更多
The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,an...The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.展开更多
基金support by the National Natural Science Foundation of China(NSFC)(Grant Nos.52178319,42477160,52338007).
文摘Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment,the firstproblem to be solved is how to introduce and retain the bacterial cells in the soil,which involves the migration and retention of bacterial cells during the biogrouting process.Soil particle size,a key factor in determining pore throat size,can have a significanteffect on the migration and retention of bacterial cells in the soil and therefore on biomineralization.To investigate the effect of particle size on the migration and retention of bacterial cells in sand and its biomineralization,two sets of tests were carried out in this study,including percolation tests and sand column treatment tests.Soil urease activity(definedas urease activity per unit mass of soil)and calcium carbonate content of the biomineralized sand were measured to comprehensively assess the migration and retention of bacterial cells in the sand.The results indicate that sands with a particle size smaller than 0.25 mmwould inhibit the migration of bacteria in the sand,resulting in a nonuniform distribution of precipitated calcium carbonate and a low strength enhancement of biomineralization.On the other hand,sands with a particle size larger than 1.18 mm are unfavorable for retaining bacterial cells in the sand,resulting in low calcium conversion efficiency.Meanwhile,particle size would also affect the formation of effective calcium carbonate through interparticle contact number and interparticle pore size,and thus biomineralization.
文摘This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the strength of treated sand.Columns with a diameter of 7.5 cm were constructed using three mixing times(130,190,and 250 s),two execution procedures(normal and zigzag),threeαvalues(300,400,and 500 kg/m^(3)),and three W_(Total)/C ratios(2.5,3.0,and 3.5).For comparison,equivalent laboratory samples were also examined.Results revealed that increasing the mixing time andα,adopting the zigzag execution procedure,and reducing the W_(Total)/C ratio increase E.Outcomes indicated that an increase in E from 0.49-0.70 kJ to 0.70-0.90 kJ,0.90-1.10 kJ,and 1.10-1.40 kJ improves the unconfined compressive strength(UCS)of columns on average by 66%,124%,and 179%,respectively,and the secant modulus by 61%,110%,and 152%.Average strain at maximum stress also rises from 0.68%to 0.75%,0.81%,and 0.84%,respectively.The study identified a threshold in the direct relationship between E and the strength ratio(λ),beyond whichλdid not increase significantly with further increases in E.Additionally,at low and high E levels,DSM samples mainly failed by crushing and cracking modes,respectively.In DSM columns withα=500 kg/m^(3)and W_(Total)/C=2.5,increasing average E from 0.77 kJ to 0.95 kJ,1.08 kJ,and 1.28 kJ resulted in a reduction of coefficients of variation of UCS from 30.4%to 27.8%,24.5%,and 21.1%,respectively.
基金supported by JSPS KAKENHI(Grant Nos.JP22K04305 and JP19K15083).
文摘To investigate the influencesof non-plastic silt and soil aging on the re-liquefaction resistance of sands,a series of undrained triaxial tests was performed on sand-silt mixtures with finescontent ranging from 0%to 100%,as well as on undisturbed and reconstituted non-plastic sandy soils retrieved from earth structures with a history of earthquake-induced damage.The specimens on sand-silt mixtures were produced under an initial degree of compaction of 95%.In these tests,liquefaction histories were applied three times to a single specimen under the same cyclic stress ratio after the respective consolidation stages with the measurements of the shear wave velocities.The following conclusions can be obtained from the test results:(1)The liquefaction resistance obtained in the firstto third cyclicloading stages decreased initially with increasing finescontent up to about 45%,while it increased afterward.Therefore,the susceptibility of sands containing a relatively large amount of non-plastic silt to reliquefaction may be more significantthan that of clean sands;(2)The liquefaction resistance and the shear wave velocity decreased significantlyduring the second cyclic-loading stage and after the second consolidation,respectively,despite an increase in the specimen density caused by the first liquefaction history,while they increased in the third stage.The possible reason for this change would be the disturbance of soil structures due to liquefaction,which may be partially evaluated by the volumetric strain during the respective consolidation stages,and the stress-induced anisotropy formed in the previous liquefaction stage;and(3)The liquefaction resistance and the shear wave velocity of the undisturbed specimens,which were measured in the firstto third stages,were larger than those of the reconstituted ones due to the aging effects,respectively.That is,the aging effects may not necessarily be eliminated by the subsequent liquefaction history and may remain partially in some cases.
文摘The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.
