Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation gener...Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.展开更多
Biomass tar is an obstacle in biomass gasification. Partial combustion is a potential method for tar elimination. To better study the tar conversion conditions and design reasonable partial combustion reactor, 2D/3D t...Biomass tar is an obstacle in biomass gasification. Partial combustion is a potential method for tar elimination. To better study the tar conversion conditions and design reasonable partial combustion reactor, 2D/3D throat models are establish to calculate the tar reduction during partial combustion using numerical method. Different number of nozzles, injection directions and injection velocities were investigated. SIMPLE algorithm was used in this calculation. The results indicated that the best performance of partial combustion was obtained when ER (equivalent ratio) = 0.34. A performance of 3 nozzles, perpendicular injection and 20 m/s injection velocity could reach lowest tar content of 3.09 wt%.展开更多
Particle image velocimetry （PIV）, thermocouples and flue gas analyzer are used to study swirling coal combustion and NO formation under different secondary-air ratios. Eulerian-Lagrangian large-eddy sim-ulation （LE...Particle image velocimetry （PIV）, thermocouples and flue gas analyzer are used to study swirling coal combustion and NO formation under different secondary-air ratios. Eulerian-Lagrangian large-eddy sim-ulation （LES） using the Smagorinsky-Lilly sub-grid scale stress model, presumed-PDF fast chemistry and eddy-break-up （EBU） gas combustion models, particle devolatilization and particle combustion models, are simultaneously used to simulate swirling coal combustion. Statistical LES results are validated by measurement results. Instantaneous LES results show that the coherent structures for swirling coal com- bustion are stronger than those for swirling gas combustion. Particles are shown to concentrate along the periphery of the coherent structures. Combustion flame is located in the high vorticity and high par-ticle concentration zones. Measurement shows that secondary-air ratios have little effect on final NO formation at the exit of the combustor.展开更多
基金supported by the National Key Research and Development Program of China(2020AAA0109300)the Shanghai Collaborative Innovation Center of data intelligence technology(No.0232-A1-8900-24-13).
文摘Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.
文摘Biomass tar is an obstacle in biomass gasification. Partial combustion is a potential method for tar elimination. To better study the tar conversion conditions and design reasonable partial combustion reactor, 2D/3D throat models are establish to calculate the tar reduction during partial combustion using numerical method. Different number of nozzles, injection directions and injection velocities were investigated. SIMPLE algorithm was used in this calculation. The results indicated that the best performance of partial combustion was obtained when ER (equivalent ratio) = 0.34. A performance of 3 nozzles, perpendicular injection and 20 m/s injection velocity could reach lowest tar content of 3.09 wt%.
基金supported mainly by the National Natural Science Foundation of China under the Grant 50606026supported by the National Natural Science Foundation of China under the Grant 50736006the Foundation of the National Key Laboratory of Engines,Tianjin University underthe Grant K-2010-07
文摘Particle image velocimetry （PIV）, thermocouples and flue gas analyzer are used to study swirling coal combustion and NO formation under different secondary-air ratios. Eulerian-Lagrangian large-eddy sim-ulation （LES） using the Smagorinsky-Lilly sub-grid scale stress model, presumed-PDF fast chemistry and eddy-break-up （EBU） gas combustion models, particle devolatilization and particle combustion models, are simultaneously used to simulate swirling coal combustion. Statistical LES results are validated by measurement results. Instantaneous LES results show that the coherent structures for swirling coal com- bustion are stronger than those for swirling gas combustion. Particles are shown to concentrate along the periphery of the coherent structures. Combustion flame is located in the high vorticity and high par-ticle concentration zones. Measurement shows that secondary-air ratios have little effect on final NO formation at the exit of the combustor.
