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Building Drag Parameterization Including Anisotropy and Its Coupling with the Weather Research and Forecasting Model 认领 引用
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作者 Yuhang TIAN Zhenghui XIE +7 位作者 Jinbo XIE Binghao JIA Shuai SUN Peihua QIN Ruichao LI Longhuan WANG Heng YAN Yanbin YOU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第7期1461-1477,共17页
Buildings increase the urban surface roughness and reduce near-surface wind speeds due to the drag effect,which depends on the flow direction.In this study,a building drag parameterization scheme including the buildin... Buildings increase the urban surface roughness and reduce near-surface wind speeds due to the drag effect,which depends on the flow direction.In this study,a building drag parameterization scheme including the building anisotropy for all flow directions was developed through approximating buildings with elliptical columns to represent anisotropic frontal area index.The new scheme was coupled with the Weather Research and Forecasting(WRF)model to improve urban simulations in those including near-surface wind speeds.The conducted offline sensitivity tests with the developed scheme,using horizontal wind along different directions,show continuous transitions of drag coefficient and other variables depending on flow direction.The maximum difference of drag coefficient between the new and the original scheme reached 10%–20%of that from the original one.These monthly simulations of the WRF model with the new building drag scheme for Chengdu were conducted to validate the updated model against station observation and reanalysis data.Compared to the original scheme,the updated scheme reduces overestimation of 10-m wind speed by 0.1–0.2 m s−1(5%–15%of the original bias),overestimation of 2-m temperature by 0.1℃–0.4℃(20%–60%),and underestimation of 2-m relative humidity by 1%–3%(20%–60%).This is achieved by increasing the drag coefficient through an enhanced frontal area index and reducing wind speed.The diminished wind speed reduces sensible heat flux,enhances latent heat flux,and suppresses vertical motions,resulting in humidity accumulation and cooling in the lower atmosphere.These suggest that reasonable representation of the building anisotropy is important in researching urban climate. 展开更多
关键词 building drag parameterization frontal area index building anisotropy urban canopy model Weather Research and Forecasting model
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Comparison of bottom friction parameterization schemes and the application in tidal simulation and tidal energy dissipation assessment 认领 引用
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作者 Jiarui LIAN Hailong GUO +1 位作者 Yizhou LAI Feimeng HUANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2026年第2期590-602,共13页
Bottom frictional dissipation is one of the key mechanisms regulating the tidal movement in the areas surrounding Taiwan Island,China.However,our existing understanding in this field remains incomplete,because the bot... Bottom frictional dissipation is one of the key mechanisms regulating the tidal movement in the areas surrounding Taiwan Island,China.However,our existing understanding in this field remains incomplete,because the bottom friction coefficient(BFC)of this area is still unclear.Based on the Semi-implicit Cross-scale Hydroscience Integrated System Model(SCHISM)ocean numerical model,three bottom friction parameterization schemes(BFPSs)were compared,namely the Adjoint Data Assimilation(ADA),Manning Depth-dependent Formula(MDF),and Constant.This research finds that the ADA scheme performed best in tidal simulation.The error of elevation is less than 8.48 cm.Based on the simulation results of the ADA scheme,the tidal dynamic characteristics and bottom frictional dissipation surrounding Taiwan Island were systematically analyzed.Results show that the amplitude peaks of the semidiurnal tides are located in the vicinity of 25°N,119°E.A densely-packed zone of isophase lines and a zero-ellipticity demarcation line were observed at 23.5°N.Regarding the diurnal tides,the amplitudes exhibit an increasing trend from the southeast towards the northwest,and the isophase lines are orthogonal to the coastline.The frictional dissipation rate is generally high within the strait(mean of 3.1×103W/m2).However,it is relatively low in the Penghu Channel(mean of 1.34×105W/m2).Therefore,the tidal energy flux in the strait is concentrated at the northern and southern extremities(mean of 1.5×106W/m)as well as in the Penghu Channel.Similar correlations between tidal energy flux and bottom frictional dissipation rate are manifested in the eastern,southern,and northern parts of Taiwan Island. 展开更多
关键词 tidal simulation tidal energy flux bottom friction parameterization schemes(BFPSs) bottom friction dissipation areas surrounding Taiwan Island
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Aerodynamic shape optimization of hypersonic aircraft using data-driven generative nonlinear parameterization 认领 引用
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作者 Yan CHEN Jichao LI Jinsheng CAI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期64-76,共13页
Aerodynamic shape optimization of hypersonic vehicles is critically important yet profoundly challenging.The difficulties arise from the need to manage multiple competing objectives,complex three-dimensional geometrie... Aerodynamic shape optimization of hypersonic vehicles is critically important yet profoundly challenging.The difficulties arise from the need to manage multiple competing objectives,complex three-dimensional geometries,and the extreme computational cost of high-fidelity aerodynamic simulations across subsonic,transonic,and hypersonic regimes.Despite recent advances,an effective global optimization strategy for hypersonic aircraft design remains limited,largely hindered by the curse of dimensionality.To remove this barrier,we propose a data-driven generative nonlinear shape parameterization framework for efficient aerodynamic design of hypersonic aircraft.This framework begins by constructing diverse hypersonic aircraft shapes that cover the feasible sub-domains of a high-dimensional design space.A linear dimension reduction method is used to transform the high-dimensional point-cloud database to a low-dimensional modal space.Subsequently,a nonlinear generative model is trained to learn the statistical distribution feature of the linear mode coefficients.The resulting generative latent space provides an efficient,lowdimensional,and expressive parameterization of aerodynamic shapes.The proposed method is validated in both single-point and multi-point optimization of hypersonic aircraft,demonstrating superior efficiency and effectiveness compared with conventional parameterization approaches.This study presents an efficient roadmap for aerodynamic shape parameterization and global optimization of next-generation aircraft. 展开更多
关键词 Aerodynamic shape optimization Deep-learning Dimension reduction Generative parameterization Hypersonic aircraft design
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Typhoon Kompasu(2118)simulation with planetary boundary layer and cloud physics parameterization improvements 认领 引用
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作者 Xiaowei Tan Zhiqiu Gao Yubin Li 《Atmospheric and Oceanic Science Letters》 CAS CSCD 2026年第1期41-46,共6页
This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the pred... This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure. 展开更多
关键词 Tropical cyclone Numerical simulation Planetary boundary layer parameterization scheme Cloud physics scheme
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Advanced Meta-Heuristic Optimization for Accurate Photovoltaic Model Parameterization:A High-Accuracy Estimation Using Spider Wasp Optimization 认领 引用
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作者 Sarah M.Alhammad Diaa Salama AbdElminaam +1 位作者 Asmaa Rizk Ibrahim Ahmed Taha 《Computers, Materials & Continua》 SCIE EI 2026年第3期2269-2303,共35页
Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.W... Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.While a wide range of metaheuristic optimisation techniques have been applied to this problem,many existing methods are hindered by slow convergence rates,susceptibility to premature stagnation,and reduced accuracy when applied to complex multi-diode PV configurations.These limitations can lead to suboptimal modelling,reducing the efficiency of PV system design and operation.In this work,we propose an enhanced hybrid optimisation approach,the modified Spider Wasp Optimization(mSWO)with Opposition-Based Learning algorithm,which integrates the exploration and exploitation capabilities of the Spider Wasp Optimization(SWO)metaheuristic with the diversityenhancing mechanism of Opposition-Based Learning(OBL).The hybridisation is designed to dynamically expand the search space coverage,avoid premature convergence,and improve both convergence speed and precision in highdimensional optimisation tasks.The mSWO algorithm is applied to three well-established PV configurations:the single diode model(SDM),the double diode model(DDM),and the triple diode model(TDM).Real experimental current-voltage(I-V)datasets from a commercial PV module under standard test conditions(STC)are used for evaluation.Comparative analysis is conducted against eighteen advanced metaheuristic algorithms,including BSDE,RLGBO,GWOCS,MFO,EO,TSA,and SCA.Performance metrics include minimum,mean,and maximum root mean square error(RMSE),standard deviation(SD),and convergence behaviour over 30 independent runs.The results reveal that mSWO consistently delivers superior accuracy and robustness across all PV models,achieving the lowest RMSE values of 0.000986022(SDM),0.000982884(DDM),and 0.000982529(TDM),with minimal SD values,indicating remarkable repeatability.Convergence analyses further show that mSWO reaches optimal solutions more rapidly and with fewer oscillations than all competing methods,with the performance gap widening as model complexity increases.These findings demonstrate that mSWO provides a scalable,computationally efficient,and highly reliable framework for PV parameter extraction.Its adaptability to models of growing complexity suggests strong potential for broader applications in renewable energy systems,including performance monitoring,fault detection,and intelligent control,thereby contributing to the optimisation of next-generation solar energy solutions. 展开更多
关键词 modified Spider Wasp Optimizer(mSWO) photovoltaic(PV)modeling meta-heuristic optimization solar energy parameter estimation renewable energy technologies
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Is convection-permitting model really better than cumulus parameterization for simulating summer precipitation in the Hengduan Mountains?——A case study of summer 2009 认领 引用
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作者 LIU Xudong CHEN Ying +3 位作者 CEN Sixian LU Yaqiong BING Jiawei MING Guijia 《Journal of Mountain Science》 SCIE CSCD 2025年第12期4392-4407,共16页
The Hengduan Mountains are susceptible to hydrological disasters,with precipitation representing a significant risk factor.For effective disaster mitigation strategies,accurate rainfall simulation is essential,typical... The Hengduan Mountains are susceptible to hydrological disasters,with precipitation representing a significant risk factor.For effective disaster mitigation strategies,accurate rainfall simulation is essential,typically achieved through the use of numerical models.Some research has indicated that using a convection-permitting model(CPM)at high resolution(<4 km)could provide more precise rainfall estimates than traditional cumulus parameterization schemes(CPs)at lower resolutions,but CPM demands substantial computational resources.Therefore,to assess whether CPM maintains superior simulation accuracy,this study employed the Weather Research and Forecasting(WRF)model to simulate summer precipitation over the Hengduan Mountains in 2009,comparing CPM(4 km)and CPs(10 km)resolutions.The simulations were evaluated against satellite observations to quantify their performance differences.The results showed that all simulations overestimated amounts and frequency.The CPM outperformed most CPs,except the Tiedtke scheme,which exhibited Root Mean Square Errors(RMSEs)of 2.51 mm·day-1 for amount and 5.63%for frequency.The CPM had slightly higher RMSEs of 2.80 mm·day-1 and 6.98%,respectively.Both CPM and Tiedtke captured the spatial distribution of precipitation,but overestimations occurred in central and southern regions and underestimations in river valleys.While Tiedtke demonstrated superiority in various aspects,CPM provided more detail.Additionally,the study noted significant differences in diurnal variation at intermediate altitudes and found correlations between rainfall amounts and convective available potential energy(CAPE),frequency,and outgoing longwave radiation(OLR),respectively.Consequently,the Tiedtke scheme is suggested as a more resource-efficient alternative to CPM for simulating precipitation in the Hengduan Mountains. 展开更多
关键词 Convection-permitting model Cumulus parameterization Numerical simulation WRF
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Cloud Droplet Spectrum Evolution Driven by Aerosol Activation and Vapor Condensation:A Comparative Study of Different Bulk Parameterization Schemes 认领 引用
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作者 Jun ZHANG Jiming SUN +2 位作者 Yu KONG Wei DENG Wenhao HU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第7期1316-1332,共17页
Accurate descriptions of cloud droplet spectra from aerosol activation to vapor condensation using microphysical parameterization schemes are crucial for numerical simulations of precipitation and climate change in we... Accurate descriptions of cloud droplet spectra from aerosol activation to vapor condensation using microphysical parameterization schemes are crucial for numerical simulations of precipitation and climate change in weather forecasting and climate prediction models.Hence,the latest activation and triple-moment condensation schemes were combined to simulate and analyze the evolution characteristics of a cloud droplet spectrum from activation to condensation and compared with a high-resolution Lagrangian bin model and the current double-moment condensation schemes,in which the spectral shape parameter is fixed or diagnosed by an empirical formula.The results demonstrate that the latest schemes effectively capture the evolution characteristics of the cloud droplet spectrum during activation and condensation,which is in line with the performance of the bin model.The simulation of the latest activation and condensation schemes in a parcel model shows that the cloud droplet spectrum gradually widens and exhibits a multimodal distribution during the activation process,accompanied by a decrease in the spectral shape and slope parameters over time.Conversely,during the condensation process,the cloud droplet spectrum gradually narrows,resulting in increases in the spectral shape and slope parameters.However,these double-moment schemes fail to accurately replicate the evolution of the cloud droplet spectrum and its multimodal distribution characteristics.Furthermore,the latest schemes were coupled into a 1.5D cumulus model,and an observation case was simulated.The simulations confirm that the cloud droplet spectrum appears wider at the supersaturated cloud base and cloud top due to activation,while it becomes narrower at the middle altitudes of the cloud due to condensation growth. 展开更多
关键词 cloud microphysical parameterization cloud droplet spectrum aerosol activation cloud droplet condensation
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Improved Simulation of Tropical Cyclone Soudelor(2015)Using a Modified Three-Dimensional Turbulence Parameterization 认领 引用
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作者 Gengjiao YE Xu ZHANG +3 位作者 Shanghong WANG Hui YU Xuesong ZHU Mengjuan LIU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第7期1407-1422,共16页
A modified three-dimensional turbulence parameterization scheme,implemented by replacing the conventional eddydiffusivity formulation with the H-gradient model,has shown good performance in representing the subgrid-sc... A modified three-dimensional turbulence parameterization scheme,implemented by replacing the conventional eddydiffusivity formulation with the H-gradient model,has shown good performance in representing the subgrid-scale(SGS)turbulent fluxes associated with convective clouds in idealized tropical cyclone(TC)simulations.To evaluate the capability of the modified scheme in simulating real TCs,two sets of simulations of TC Soudelor(2015),one with the modified scheme and the other with the original scheme,are conducted.Comparisons with observations and coarse-grained results from large eddy simulation benchmarks demonstrate that the modified scheme improves the forecasting of the intensity and structure,as well as the SGS turbulent fluxes of Soudelor.Using the modified turbulence scheme,a TC with stronger intensity,smaller size,a shallower but stronger inflow layer,and a more intense but less inclined convective updraft is simulated.The rapid intensification process and secondary eyewall features can also be captured better by the modified scheme.By analyzing the mechanism by which turbulent transport impacts the intensity and structure of TCs,it is shown that accurately representing the turbulent transport associated with convective clouds above the planetary boundary layer helps to initiate the TC spin-up process. 展开更多
关键词 tropical cyclone turbulence parameterization numerical simulation tropical cyclone intensity tropical cyclone structure tropical cyclone spin-up process
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Towards a physics-constrained and interpretable datadriven parameterization scheme for mesoscale eddies in ocean modeling 认领 引用
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作者 Guosong Wang Shuai Song +5 位作者 Min Hou Xinrong Wu Xidong Wang Yaming Zhao Song Pan Zhigang Gao 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2025年第7期15-32,共18页
Mesoscale eddies play a pivotal role in deciphering the intricacies of ocean dynamics and the transport of heat,salt,and nutrients.Accurate representation of these eddies in ocean models is essential for improving mod... Mesoscale eddies play a pivotal role in deciphering the intricacies of ocean dynamics and the transport of heat,salt,and nutrients.Accurate representation of these eddies in ocean models is essential for improving model predictions.In this study,we propose a convolutional neural network(CNN)that combines data-driven techniques with physical principles to develop a robust and interpretable parameterization scheme for mesoscale eddies in ocean modeling.We use a highresolution reanalysis dataset to extract subgrid eddy momentum and then applying machine learning algorithms to identify patterns and correlations.To ensure physical consistency,we have introduced conservation of momentum constraints in our CNN parameterization scheme through soft and hard constraints.The interpretability analysis illustrate that the pre-trained CNN parameterization shows promising results in accurately solving the resolved mean velocity and effectively capturing the representation of unresolved subgrid turbulence processes.Furthermore,to validate the CNN parameterization scheme offline,we conduct simulations using the Massachusetts Institute of Technology general circulation model(MITgcm)ocean model.A series of experiments is conducted to compare the performance of the model with the CNN parameterization scheme and high-resolution simulations.The offline validation demonstrates the effectiveness of the CNN parameterization scheme in improving the representation of mesoscale eddies in the MITgcm ocean model.Incorporating the CNN parameterization scheme leads to better agreement with high-resolution simulations and a more accurate representation of the kinetic energy spectra. 展开更多
关键词 subgrid parameterization ocean mesoscale eddies physics-informed deep learning kinetic energy backscatter numerical simulation
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Multivariate GARCH models with spherical parameterizations:an oil price application 认领 引用
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作者 Luca Vincenzo Ballestra Riccardo De Blasis Graziella Pacelli 《Financial Innovation》 2025年第1期1158-1177,共20页
In popular Baba-Engle-Kraft-Kroner(BEKK)and dynamic conditional correlation(DCC)multivariate generalized autoregressive conditional heteroskedasticity models,the large number of parameters and the requirement of posit... In popular Baba-Engle-Kraft-Kroner(BEKK)and dynamic conditional correlation(DCC)multivariate generalized autoregressive conditional heteroskedasticity models,the large number of parameters and the requirement of positive definiteness of the covariance and correlation matrices pose some difficulties during the estimation process.To avoid these issues,we propose two modifications to the BEKK and DCC models that employ two spherical parameterizations applied to the Cholesky decompositions of the covariance and correlation matrices.In their full specifications,the introduced Cholesky-BEKK and Cholesky-DCC models allow for a reduction in the number of parameters compared with their traditional counterparts.Moreover,the application of spherical transformation does not require the imposition of inequality constraints on the parameters during the estimation.An application to two crude oils,WTI and Brent,and the main exchange rate prices demonstrates that the Cholesky-BEKK and Cholesky-DCC models can capture the dynamics of covariances and correlations.In addition,the Kupiec test on different portfolio compositions confirms the satisfactory performance of the proposed models. 展开更多
关键词 BEKK Cholesky-GARCH Crude oils DCC Exchange rates Spherical parameterization
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Large system study of chalcopyrite and pyrite flotation surfaces based on SCC-DFTB parameterization method 认领 引用
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作者 Jianhua Chen Yibing Zhang 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2025年第7期1037-1055,共19页
In recent years,the study of chalcopyrite and pyrite flotation surfaces using computational chemistry methods has made significant progress.However,current computational methods are limited by the small size of their ... In recent years,the study of chalcopyrite and pyrite flotation surfaces using computational chemistry methods has made significant progress.However,current computational methods are limited by the small size of their systems and insufficient consideration of hydration and temperature effects,making it difficult to fully replicate the real flotation environment of chalcopyrite and pyrite.In this study,we employed the self-consistent charge density functional tight-binding(SCC-DFTB)parameterization method to develop a parameter set,CuFeOrg,which includes the interactions between Cu-Fe-C-H-O-N-S-P-Zn elements,to investigate the surface interactions in large-scale flotation systems of chalcopyrite and pyrite.The results of bulk modulus,atomic displacement,band structure,surface relaxation,surface Mulliken charge distribution,and adsorption tests of typical flotation reagents on mineral surfaces demonstrate that CuFeOrg achieves DFT-level accuracy while significantly outperforming DFT in computational efficiency.By constructing large-scale hydration systems of mineral surfaces,as well as large-scale systems incorporating the combined interactions of mineral surfaces,flotation reagents,and hydration,we more realistically reproduce the actual flotation environment.Furthermore,the dynamic analysis results are consistent with mineral surface contact angle experiments.Additionally,CuFeOrg lays the foundation for future studies of more complex and diverse chalcopyrite and pyrite flotation surface systems. 展开更多
关键词 SCC-DFTB Parameterization Chalcopyrite Pyrite Flotation surface Large-scale system
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Physically Constrained Adaptive Deep Learning for Ocean Vertical-Mixing Parameterization 认领 引用 被引量：1
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作者 Junjie FANG Xiaojie LI +4 位作者 Jin LI Zhanao HUANG Yongqiang YU Xiaomeng HUANG Xi WU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第1期165-177,共13页
Existing traditional ocean vertical-mixing schemes are empirically developed without a thorough understanding of the physical processes involved,resulting in a discrepancy between the parameterization and forecast res... Existing traditional ocean vertical-mixing schemes are empirically developed without a thorough understanding of the physical processes involved,resulting in a discrepancy between the parameterization and forecast results.The uncertainty in ocean-mixing parameterization is primarily responsible for the bias in ocean models.Benefiting from deep-learning technology,we design the Adaptive Fully Connected Module with an Inception module as the baseline to minimize bias.It adaptively extracts the best features through fully connected layers with different widths,and better learns the nonlinear relationship between input variables and parameterization fields.Moreover,to obtain more accurate results,we impose KPP(K-Profile Parameterization)and PP(Pacanowski–Philander)schemes as physical constraints to make the network parameterization process follow the basic physical laws more closely.Since model data are calculated with human experience,lacking some unknown physical processes,which may differ from the actual data,we use a decade-long time record of hydrological and turbulence observations in the tropical Pacific Ocean as training data.Combining physical constraints and a nonlinear activation function,our method catches its nonlinear change and better adapts to the oceanmixing parameterization process.The use of physical constraints can improve the final results. 展开更多
关键词 deep learning vertical-mixing parameterization ocean sciences adaptive network
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Parameterization of turbulent mixing by deep learning in the continental shelf sea east of Hainan Island 认领 引用 被引量：1
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作者 Minghao HU Lingling XIE +1 位作者 Mingming LI Quanan ZHENG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2025年第3期657-675,共19页
The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed wit... The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed with the hydrological and microstructure observations conducted in summer 2012 in the shelf sea east of Hainan Island, in South China Sea(SCS). The deep neural network model is used and incorporates the Richardson number Ri, the normalized depth D, the horizontal velocity speed U, the shear S2, the stratification N2, and the density ρ as input parameters. Comparing to the scheme without parameter D and region division, the depth-dependent scheme improves the prediction of the turbulent kinetic energy dissipation rate ε. The correlation coefficient(r) between predicted and observed lgε increases from 0.49 to 0.62, and the root mean square error decreases from 0.56 to 0.48. Comparing to the traditional physics-driven parameterization schemes, such as the G89 and MG03, the data-driven approach achieves higher accuracy and generalization. The SHapley Additive Explanations(SHAP) framework analysis reveals the importance descending order of the input parameters as: ρ, D, U, N2, S2, and Ri in the whole depth, while D is most important in the upper and bottom boundary layers(D≤0.3&D≥0.65) and least important in middle layer(0.3<D<0.65). The research shows applicability of constructing deep learning-based ocean turbulent mixing parameterization schemes using limited observational data and well-established physical processes. 展开更多
关键词 ocean turbulent mixing parameterization continental shelf sea deep learning SHapley Additive Explanations(SHAP)
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Stabilized adaptive waveform inversion for enhanced robustness in Gaussian penalty matrix parameterization and transcranial ultrasound imaging 认领 引用
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作者 Jun-Jie Zhao Shan-Mu Jin +2 位作者 Yue-Kun Wang Yu Wang Ya-Hui Peng 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第8期606-621,共16页
Achieving high-resolution intracranial imaging in a safe and portable manner is critical for the diagnosis of intracranial diseases,preoperative planning of craniotomies and intraoperative management during craniotomy... Achieving high-resolution intracranial imaging in a safe and portable manner is critical for the diagnosis of intracranial diseases,preoperative planning of craniotomies and intraoperative management during craniotomy procedures.Adaptive waveform inversion(AWI),a variant of full waveform inversion(FWI),has shown potential in intracranial ultrasound imaging.However,the robustness of AWI is affected by the parameterization of the Gaussian penalty matrix and the challenges posed by transcranial scenarios.Conventional AWI struggles to produce accurate images in these cases,limiting its application in critical medical settings.To address these issues,we propose a stabilized adaptive waveform inversion(SAWI)method,which introduces a user-defined zero-lag position for theWiener filter.Numerical experiments demonstrate that SAWI can achieve accurate imaging under Gaussian penalty matrix parameter settings where AWI fails,perform successful transcranial imaging in configurations where AWI cannot,and maintain the same imaging accuracy as AWI.The advantage of this method is that it achieves these advancements without modifying the AWI framework or increasing computational costs,which helps to promote the application of AWI in medical fields,particularly in transcranial scenarios. 展开更多
关键词 ultrasound brain imaging full waveform inversion robustness parameterization
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MS-GAN:3D deep generative model for multispecies propeller parameterization and generation 认领 引用
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作者 Chenyu WANG Bo CHEN +2 位作者 Haiyang FU Yitong FAN Weipeng LI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第6期382-395,共14页
In this study,we introduce a deep generative model,named Multi-Species Generative Adversarial Network(MS-GAN),which is developed to extract the low-dimensional manifold of three-dimensional multi-species surfaces.In t... In this study,we introduce a deep generative model,named Multi-Species Generative Adversarial Network(MS-GAN),which is developed to extract the low-dimensional manifold of three-dimensional multi-species surfaces.In the development of MS-GAN,we extend the freeform deformation by incorporating principal component analysis to increase the non-linear deformation ability while maintaining geometric smoothness.The implicit information of multiple baselines is embedded in the feature extraction layers,to enhance the diversity and parameterization of multi-species dataset.Furthermore,Wasserstein GAN with a gradient penalty is used to ensure the stability and convergence of the training networks.Two experiments,ruled surfaces and propeller blade surfaces,are performed to demonstrate the advantages and superiorities of MS-GAN. 展开更多
关键词 Propellers Dimensionality reduction Parameterize Artificial intelligence Generative design
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Efficient Parameterization for Knowledge Graph Embedding Using Hierarchical Attention Network 认领 引用
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作者 Zhen-Yu Chen Feng-Chi Liu +2 位作者 Xin Wang Cheng-Hsiung Lee Ching-Sheng Lin 《Computers, Materials & Continua》 SCIE EI 2025年第3期4287-4300,共14页
In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with l... In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with large-scale knowledge graphs that contain vast numbers of entities and relations.In particular,resource-intensive embeddings often lead to increased computational costs,and may limit scalability and adaptability in practical environ-ments,such as in low-resource settings or real-world applications.This paper explores an approach to knowledge graph representation learning that leverages small,reserved entities and relation sets for parameter-efficient embedding.We introduce a hierarchical attention network designed to refine and maximize the representational quality of embeddings by selectively focusing on these reserved sets,thereby reducing model complexity.Empirical assessments validate that our model achieves high performance on the benchmark dataset with fewer parameters and smaller embedding dimensions.The ablation studies further highlight the impact and contribution of each component in the proposed hierarchical attention structure. 展开更多
关键词 Knowledge graph embedding parameter efficiency representation learning reserved entity and relation sets hierarchical attention network
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Understanding primary and secondary sources of ambient oxygenated volatile organic compounds in Shenzhen utilizing photochemical age-based parameterization method 认领 引用 被引量：22
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作者 Bo Zhu Yu Han +5 位作者 Chuan Wang Xiaofeng Huang Shiyong Xia Yingbo Niu Zixuan Yin Lingyan He 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2019年第1期105-114,共10页
Oxygenated volatile organic compounds(OVOCs) are key intermediates in the atmospheric photooxidation process. To further study the primary and secondary sources of OVOCs,their ambient levels were monitored using a pro... Oxygenated volatile organic compounds(OVOCs) are key intermediates in the atmospheric photooxidation process. To further study the primary and secondary sources of OVOCs,their ambient levels were monitored using a proton-transfer reaction mass spectrometer(PTR-MS) at an urban site in the Pearl River Delta of China. Continuous monitoring campaigns were conducted in the spring, summer, fall, and winter of 2016. Among the six types of OVOC species, the mean concentrations of methanol were the highest in each season(up to 13–20 ppbv), followed by those of acetone, acetaldehyde and acetic acid(approximately 2–4 ppbv), while those of formic acid and methyl ethyl ketone(MEK) were the lowest(approximately 1–2 ppbv). As observed from a diurnal variation chart, the OVOCs observed in Shenzhen may have been affected by numerous factors such as their primary and secondary sources and photochemical consumption. The photochemical age-based parameterization method was used to apportion the sources of ambient OVOCs. Methanol had significant anthropogenic primary sources but negligible anthropogenic secondary sources during all of the seasons. Acetone, MEK and acetic acid were mostly attributed to anthropogenic primary sources during each season with smaller contributions from anthropogenic secondary sources. Acetaldehyde had similar contributions from both anthropogenic secondary and anthropogenic primary sources throughout the year.Meanwhile, anthropogenic primary sources contributed the most to formic acid. 展开更多
关键词 OVOCs PTR-MS Photochemical age-based parameterization method
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On the Radiative Properties of Ice Clouds:Light Scattering, Remote Sensing,and Radiation Parameterization 认领 引用 被引量：16
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作者 Ping YANG Kuo-Nan LIOU +3 位作者 Lei BI Chao LIU Bingqi YI Bryan A.BAUM 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2015年第1期32-63,共32页
Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical ... Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the singlescattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed.With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared（IR） bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed.The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models（GCMs）. The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven. 展开更多
关键词 ice clouds light scattering remote sensing radiative property parameterization
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Improving the CoLM in Taklimakan Desert Hinterland with Accurate Key Parameters and an Appropriate Parameterization Scheme 认领 引用 被引量：17
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作者 刘永强 何清 +1 位作者 张宏升 艾力.买买提明 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2012年第2期381-390,共10页
Improving and validating land surface models based on integrated observations in deserts is one of the challenges in land modeling. Particularly, key parameters and parameterization schemes in desert regions need to b... Improving and validating land surface models based on integrated observations in deserts is one of the challenges in land modeling. Particularly, key parameters and parameterization schemes in desert regions need to be evaluated in-situ to improve the models. In this study, we calibrated the land-surface key parameters and evaluated several formulations or schemes for thermal roughness length （z 0h ） in the common land model （CoLM）. Our parameter calibration and scheme evaluation were based on the observed data during a torrid summer （29 July to 11 September 2009） over the Taklimakan Desert hinterland. First, the importance of the key parameters in the experiment was evaluated based on their physics principles and the significance of these key parameters were further validated using sensitivity test. Second, difference schemes （or physics-based formulas） of z 0h were adopted to simulate the variations of energy-related variables （e.g., sensible heat flux and surface skin temperature） and the simulated variations were then compared with the observed data. Third, the z 0h scheme that performed best （i.e., Y07） was then selected to replace the defaulted one （i.e., Z98）; the revised scheme and the superiority of Y07 over Z98 was further demonstrated by comparing the simulated results with the observed data. Admittedly, the revised model did a relatively poor job of simulating the diurnal variations of surface soil heat flux, and nighttime soil temperature was also underestimated, calling for further improvement of the model for desert regions. 展开更多
关键词 common land model （CoLM） parameter parameterization scheme Taklimakan Desert
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A Parameterization Scheme of Surface Turbulent Momentum and Sensible Heat over the Gobi Underlying Surface 认领 引用 被引量：26
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作者 张强 黄荣辉 田辉 《Advances in Atmospheric Sciences》 SCIE CAS 2003年第1期111-118,共8页
The parameterization of surface turbulent fluxes over the Gobi Desert in arid regions is studied by using rationally screened observational data. First, the characteristics of Monin-Obukhov similarity functions are an... The parameterization of surface turbulent fluxes over the Gobi Desert in arid regions is studied by using rationally screened observational data. First, the characteristics of Monin-Obukhov similarity functions are analyzed and their empirical formulae are fitted. The results show that fitted curves of changes of similarity functions of wind speed and temperature with stability parameter differ little from the typical empirical curves and are within the ranges of scatter of the empirical curves, but their values in the neutral condition arc different from the typical values to some extent. Furthermore, average values of momentum and scalar (sensible heat) roughness lengths as well as changes of scalar roughness length with friction velocity are determined by utilizing the data. It is found that the average values of scalar roughness length are about one order smaller than that of the momentum roughness length and decrease with increasing friction velocity, but they are evidently larger than their theoretically forecasted values. 展开更多
关键词 Gobi surface turbulent flux parameterization similarity functions scalar roughness length
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