Simulated Values Research Articles

Investigation on the 2018 prolonged freezing event in South China using the WRF model at convection-permitting resolution: Model performance and sensitivity analysis of physical parameterizations

The coincidence of extreme cold, precipitation, and freezing weather is one of the most significant natural disasters in winter, with extensive impacts on public transportation, the energy industry, and the ecological landscape. Despite the importance of such events, comprehensive analyses of the performance of cutting-edge numerical weather prediction models at convection-permitting scales remain inadequate. This paper investigates the prolonged freezing event that occurred from January 24 to 28, 2018 in South China using the Weather Research and Forecasting (WRF) model with a horizontal grid spacing of 3 km. The focus is on evaluating the performance of the WRF model and the impact of microphysical parameterizations and nudging techniques. The results show that the WRF model successfully captures the main features of the prolonged freezing event, including the low-level collision of cold and warm air in the lower reaches of the Yangtze River valley and the spatial distribution of precipitation. However, the model overestimates the strength of warm air from the south, leading to a northward shift of the precipitation belt. The choice of physical parameterizations significantly influences model performance, with microphysical schemes of P3, Thompson, and MYDM showing better model skill in terms of root mean square error (RMSE). The analysis also highlights the importance of nudging techniques, particularly grid nudging, which significantly improves model performance. Furthermore, the inclusion of local, very dense station observations from the China Meteorological Administration (CMA) during the nudging process provides additional improvement. A further investigation reveals that the accuracy in reproducing low-level convergence over South China is the main factor influencing model performance across different sensitivity simulations. This study underscores the value of convection-permitting simulations in accurately reproducing extreme freezing events over China.

Simulation of biocrude production from P. tricornutum, S. platensis, and C. vulgaris using Aspenplus®

Hydrothermal liquefaction (HTL) of biomass is performed at elevated pressure and temperature to avoid the drying process. This process is also suitable for the low grade biomass with higher moisture content. In this article, simulation of three types of microalgae species, such as Phaeodactylum tricornutum, Spirulina platensis, and Chlorella vulgaris, are performed using Aspen Plus®. Simulation conditions, for instance, temperature, proximate and ultimate analyses, feed rate, water content, component names, etc., are taken from the literatures. The results of microalgae are then compared at two different temperature conditions. The values, however, are not the same for all the materials due to the data availability from the literature. The highest calorific value is obtained from C. vulgaris; it is 37.27 MJ/kg at 621K, and the highest energy recovery and energy ratio are obtained from P. tricornutum; they are 88.78 % and 1.86, both at 648K respectively. The difference between experimental and simulated calorific values of different biocrudes are ranging from 2.7 % to 3.62 % at higher temperatures and from 4.68 % to 10.72 % at lower temperatures. Finally, it is found that the simulation results corroborate with the experimental results with minimal errors.

Simulating the Permeation of Toxic Chemicals through Barrier Materials.

Chemical warfare agents that are liquids with low vapor pressure pose a contact hazard to anyone who encounters them. Personal protective equipment (PPE) is utilized to ensure safe interaction with these agents. A commonly used method to characterize the permeability of PPE towards chemical weapons is to apply droplets of the liquid agent to the surface of the material and measure for chemical breakthrough. However, this method could produce errors in the estimated values of the transport properties. In this paper, we solved numerically the three-dimensional cylindrical Fick's second law of diffusion for a liquid permeating through a non-porous rubbery membrane to determine the time the permeating species will emerge on the other side of the polymer membrane. Simulations of different amounts of surface area coverage and the geometries of permeate on the membrane surface indicated that incomplete surface area coverage affects the estimation of the transport properties, making the experimentally determined transport properties unsuitable for predictive use. We simulated different permeation values to determine the factors that most influenced the estimation error and if the error was consistent over different permeate-membrane combinations. Finally, a method to correct the experimentally determined permeability is suggested.

MRI T2w Radiomics-Based Machine Learning Models in Imaging Simulated Biopsy Add Diagnostic Value to PI-RADS in Predicting Prostate Cancer: A Retrospective Diagnostic Study.

Currently, prostate cancer (PCa) prebiopsy medical image diagnosis mainly relies on mpMRI and PI-RADS scores. However, PI-RADS has its limitations, such as inter- and intra-radiologist variability and the potential for imperceptible features. The primary objective of this study is to evaluate the effectiveness of a machine learning model based on radiomics analysis of MRI T2-weighted (T2w) images for predicting PCa in prebiopsy cases. A retrospective analysis was conducted using 820 lesions (363 cases, 457 controls) from The Cancer Imaging Archive (TCIA) Database for model development and validation. An additional 83 lesions (30 cases, 53 controls) from Hong Kong Queen Mary Hospital were used for independent external validation. The MRI T2w images were preprocessed, and radiomic features were extracted. Feature selection was performed using Cross Validation Least Angle Regression (CV-LARS). Using three different machine learning algorithms, a total of 18 prediction models and 3 shape control models were developed. The performance of the models, including the area under the curve (AUC) and diagnostic values such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were compared to the PI-RADS scoring system for both internal and external validation. All the models showed significant differences compared to the shape control model (all p < 0.001, except SVM model PI-RADS+2 Features p = 0.004, SVM model PI-RADS+3 Features p = 0.002). In internal validation, the best model, based on the LR algorithm, incorporated 3 radiomic features (AUC = 0.838, sensitivity = 76.85%, specificity = 77.36%). In external validation, the LR (3 features) model outperformed PI-RADS in predictive value with AUC 0.870 vs. 0.658, sensitivity 56.67% vs. 46.67%, specificity 92.45% vs. 84.91%, PPV 80.95% vs. 63.64%, and NPV 79.03% vs. 73.77%. The machine learning model based on radiomics analysis of MRI T2w images, along with simulated biopsy, provides additional diagnostic value to the PI-RADS scoring system in predicting PCa.

Spatiotemporal prediction of surface roughness evolution of C/C composites based on recurrent neural network

Carbon/carbon (C/C) composites are widely used in aerospace applications due to their excellent properties. Their surface roughness is an important factor affecting the material properties and ablation resistance, which is essential for the accurate prediction of the material. Images are often used to summarize and characterize microstructural features, which include information such as fiber microstructure and fiber orientations. An ablation shape evolution model based on optimization of attention mechanism, which combines multi-scale convolutional neural network (MSCNN) and long short-term memory (LSTM) methods for the C/C composites, is proposed. MSCNN encodes the microstructural information of the ablation image, which is fed into the LSTM model to extract the spatiotemporal features and long-term dependencies latent in the temporal law. The attention mechanism is used to assign different weights to the extracted features which makes the model focus more on the important time steps in the sequence. The results show that the proposed model achieves excellent effects in predicting the evolution of ablative morphology, with high agreement with the simulated values. The method saves time and cost, while providing an efficient and reliable method for the design and optimization of thermal protection materials.

[formula omitted] electronic structure and spin EPR-shift of [formula omitted] ion in diluted magnetic p-type [formula omitted][formula omitted]

In this correspondence, we deduce the non-parabolic band dispersion within the framework of effective mass representation (EMR) using k→⋅π→ perturbation theory in the presence of s.o interaction, magnetic impurity and external magnetic field. We measure the electronic parameters like Fermi energy, density of states, effective g factor and effective mass etc. in p-type Sn1−xEuxTe by taking into account a 6-level band structure with normal and bumped band edges. In the study, we use the experimental and simulated band gap values as functions of Eu+2 impurity and temperature. Apart from the general trend, the electronic parameters exhibit extreme behaviour near the band inversion point x=0.020 at T=300 K (Nayak et. al.2023), but in the range of impurity concentration and temperature considered; from x=0.0005 to x=0.001 and T=1.5 K to T=300 K, the behaviour is normal. Again, we follow the expression for spin-electron paramagnetic resonance (EPR) shift (Ps) where the perturbation expansion of Green’s function is used in the presence of the above-mentioned interactions. To get around the problem of loss of translational symmetry in the presence of the magnetic field, Green’s function is redefined in terms of Peierl’s phase factor. Here we have made an extensive study of the shift of Eu+2 ion in p-type Sn1−xEuxTe for several impurity concentrations from x=0.0005 to x=0.001 in the temperature range T=1.4 K to T=300 K. Lastly, we analyze the EPR shift and other electronic parameters and their anisotropies in p-type Sn1−xEuxTe as functions of carrier concentration and Eu impurity from T=1.5K to T=300K. We report the EPR shift is 2.97×10−3 at T=300 K and 3.31×10−3 at T=1.5 K with anisotropy at p=5×1020cm−3 in contrast to the experimental observation of +(3.4±0.4)×10−3 in the same system. The discrepancy is attributed to the reduction in the density of available states at Fermi energy at the L-band caused by the simultaneous rise in that at the Σ− band noticeable particularly at/above high hole concentrations p≥5×1020cm−3.

Use of the Paired Retinol Isotope Dilution Test, but with a Single Isotope Dose, to Assess the Impact of a Vitamin A Intervention on Vitamin A Stores in Theoretical Children with Low Stores

BackgroundAs currently applied, the paired retinol isotope dilution (RID) test, which is used to assess the impact of a vitamin A intervention on vitamin A total body stores (TBS), requires 2 doses of stable isotope-labeled vitamin A. ObjectivesThe objectives of this study were to evaluate use of a single isotope dose (4 μmol) to assess TBS by RID before and after intervention in theoretical children with low/moderate TBS. MethodsWe selected 6 theoretical children with assigned values for TBS ranging from 82 to 281 μmol. Using Simulation, Analysis and Modeling software, we simulated the variable [plasma retinol specific activity (SAp)] and coefficients (Fa and S) used in the RID equation TBS (μmol) = FaS × 1/SAp in both the unsupplemented steady state at day 14 postdosing and during the subsequent 4 mo without or with vitamin A supplementation [2.8 μmol retinol/d (801 μg retinol activity equivalents/d)]. ResultsFraction of dose in plasma on day 150 compared with day 14 was similar in the unsupplemented and supplemented conditions [geometric mean, 32% (range, 20%–48%) and 30% (20%–48%), respectively] and simulated values for FaS were similar under the 2 conditions. After 2 and 4 mo of daily vitamin A supplementation with 2.8 μmol/d, TBS was 78% and 128% higher, respectively, than without supplementation. ConclusionsResults indicate that the paired RID method can successfully be done using a single 4 μmol dose of stable isotope. Furthermore, because values for the RID coefficient FaS were similar in the unsupplemented and vitamin A-supplemented conditions, these results in theoretical children indicate that FaS determined by population (“super-subject”) modeling of steady state vitamin A kinetic data could be used to predict TBS by RID after a vitamin A intervention in individuals from the same or a similar group.

Physiologically-based pharmacokinetic/pharmacodynamic modeling of meropenem in critically ill patients

This study aimed to develop a physiologically based pharmacokinetic/pharmacodynamic model (PBPK/PD) of meropenem for critically ill patients. A PBPK model of meropenem in healthy adults was established using PK-Sim software and subsequently extrapolated to critically ill patients based on anatomic and physiological parameters. The mean fold error (MFE) and geometric mean fold error (GMFE) methods were used to compare the differences between predicted and observed values of pharmacokinetic parameters Cmax, AUC0-∞, and CL to evaluate the accuracy of the PBPK model. The model was verified using meropenem plasma samples obtained from Intensive Care Unit (ICU) patients, which were determined by HPLC-MS/MS. After that, the PBPK model was combined with a PKPD model, which was developed based on f%T > MIC. Monte Carlo simulation was utilized to calculate the probability of target attainment (PTA) in patients. The developed PBPK model successfully predicted the meropenem disposition in critically ill patients, wherein the MFE average and GMFE of all predicted PK parameters were within the 1.25-fold error range. The therapeutic drug monitoring (TDM) of meropenem was conducted with 92 blood samples from 31 ICU patients, of which 71 (77.17%) blood samples were consistent with the simulated value. The TDM results showed that meropenem PBPK modeling is well simulated in critically ill patients. Monte Carlo simulations showed that extended infusion and frequent administration were necessary to achieve curative effect for critically ill patients, whereas excessive infusion time (> 4 h) was unnecessary. The PBPK/PD modeling incorporating literature and prospective study data can predict meropenem pharmacokinetics in critically ill patients correctly. Our study provides a reference for dose adjustment in critically ill patients.

Numerical investigation of liquid oxygen filling process in liquid rocket engine by a multi-dimensional co-simulation method

The liquid oxygen filling process in the thermal component downstream of the valve directly affects the starting performance and working reliability of the liquid rocket engine. The filling process is reproduced with a multi-dimensional co-simulation method including one-dimensional system simulation and three-dimensional component simulation, the former provides dynamic flow data for the latter to calculate the filling process. The characteristics of the flow and evaporation and the phenomenon of gaseous oxygen residue are investigated. The results indicate that the simulated pressure value and tendency in the thermal component agree well with the experiment. The flow and evaporation reach a temporary equilibrium due to the flash boiling of the superheated liquid oxygen in the thermal component. The pressure in the combustion chamber downstream of the thermal component plays an important role in breaking the equilibrium and promoting the transition from superheat to supercool state of liquid oxygen. Additionally, the volume proportion of residue gaseous oxygen is 35 % at ignition time, which is far from the ideal state and affects the temperature measurement in the experiment. 26 % of the gaseous oxygen has not been discharged in time, leading to the injection instability in the injection region away from the inlet.

Simulation Analysis of Three-Point Bending Fracture Process of Yellow River Ice

During the ice flood period of the Yellow River, the fracture and destruction of river ice can easily lead to the formation of ice jams and ice dams in the curved and narrow reaches. However, the occurrence and development mechanism of river ice fracture remain incompletely understood in the Yellow River. Therefore, based on the three-point bending physical test of the Yellow River ice, a three-point bending fracture numerical model of the Yellow River ice was constructed. The fracture failure process of the Yellow River ice under three-point bending was simulated, and the effects of the crack-to-height ratio and ice grain size on the fracture properties of the river ice were analyzed. By comparing the results with those of physical tests on river ice, it is evident that the fracture model can effectively simulate the cracking process of river ice. Within the confines of the simulated sample size spectrum, as the crack-to-height ratio varies from 0.2 to 0.8, the fracture toughness value of the Yellow River ice spans a range from 115.01 to 143.37 KPa·m1/2. Correspondingly, within the simulated calculation values ranging from 5.38 mm to 24.07 mm for ice crystal size, the fracture toughness value of the Yellow River ice exhibits a range from 116.89 to 143.37 KPa·m1/2. The findings reveal that an increase in the crack-to-depth ratio leads to a decrement in the fracture toughness of river ice. Within the scale range encompassed by the model calculations, as the average size of the ice crystal grains augments, the fracture toughness of the river ice exhibits a gradual ascending trend. The research results provide a parameter basis for studying the fracture performance of the Yellow River ice using a numerical simulation method and lays a foundation for investigating the cracking process of river ice from macro and micro multi-scales.

Piezoelectric micropump cooler for high-power electronic cooling

Micro-liquid cooling is highly effective for the thermal management of electronic chips. However, it is challenging to apply to high heat flux and compact electronic devices because of the limited cooling power and large pump volume. To address this issue, a compact piezoelectric micropump cooler (PMC) integrating a parallel piezoelectric micropump (PPMP) and a heat sink with a fluid guidance structure is designed. The flow and heat transfer performance of the PMC is theoretically optimized through a numerical coupling model considering mechanics, flow-solid heat transfer, and piezoelectric effect. Simulation results suggest that a copper electrode-PZT ratio of 1.4 increases the output flow rate of the PMC, and the design of five fluid guidance structures enhances its heat dissipation effectiveness. Based on the optimized results, the PMC prototype is manufactured employing 3D printing technology. Experimental results show that the flow rate maximum is 62 mL/min with a precision of 0.07 mL/V·min. When the flow rate of PMC increases to 50 mL/min, the temperature of a heat source with 50 W/cm2 can be reduced to 57 °C, which is comparable with the simulation value. The developed model accurately characterizes the heat transfer properties of the PMC thermal management approach, providing a valuable reference for future research. The proposed PMC is characterized by its compact size, high level of integration, and exceptional cooling performance, making it suitable for electronic cooling applications with high heat flux.

Numerical study on benchmark analysis of NACIE-UP facility with uniform and non-uniform power distribution

The NACIE-UP (NAtural Circulation Experiment-Upgrade) facility is located at the ENEA Brasimone Research Centre (Italy) and is designed to investigate the thermal–hydraulic properties of Lead-Bismuth Eutectic (LBE) within a wire-spaced assembly under uniform and non-uniform power distribution conditions. This benchmark exercise proposed by ENEA is based on previous experiment results, intending for development and validation of CFD/TH system code, stand-alone CFD simulation, etc. In this study, the thermal–hydraulic characteristics of Fuel Pin Simulator (FPS) are analyzed, which contains inlet bend and outlet section. ANSYS Fluent solver is applied with the COUPLE algorithm of RANS SSTk-ω model. Cheng&Tak correlation and computational conditions are implanted into Fluent in the form of UDFs. Moreover, calculations were performed for ADP10, ADP06 and ADP07. The results show that the RMSEs of ADP10SS1 and ADP10SS2 are 2.52 K and 3.69 K, 7.05 K and 8.48 K for ADP06SS1 and ADP06SS2, respectively, which indicate that the adopted models have good prediction ability for the temperature of the experimental conditions. Meanwhile, the heat transfer characteristics of different sub-channels and sections are investigated and compared with the correlations of Ushakov, Mikityuk, Kazimi and Carelli. The experimental and simulation values of the uniformly heated ADP10 are in good agreement with the correlations, while there is a large deviation for the non-uniformly heated ADP06. Therefore, it is necessary to develop new correlations for the heat transfer characteristics of LBE in wire-wrapped bundle. Above all, this study provides quantitative and qualitative analysis for verification and validation of CFD/TH system code and stand-alone CFD simulation.

Research on Output Characteristics of a Non-Contact Piezoelectric Actuator’s Micro-Displacement Amplifying Mechanism

A non-contact piezoelectric actuator is proposed. The non-contact power transfer between stator and rotor is realized by pneumatic transmission, characterized by fast response, long life, compact structure, and easy miniaturization and control. The structure of the non-contact piezoelectric actuator is designed and its working principle is elucidated. The equation of the relationship between the output displacements of the non-contact piezoelectric actuator’s micro-displacement amplifying mechanism and the input displacements of piezoelectric stack is deduced, and the simulation analysis method of output displacement of the micro-displacement amplifying mechanism is established. Using the equation and the simulation analysis, the output characteristics of micro-displacement amplifying mechanism for the non-contact piezoelectric actuator and their changes along with the system parameters are investigated. The detailed process of optimal design of the micro-displacement amplifying mechanism is given by means of mathematical statistics. The prototype is made and the performance test is carried out. The correctness of the theoretical calculation and simulation analysis is verified by comparing the experimental values with the theoretical and simulated values of the output displacement of the micro-displacement amplifying mechanism. The results show that the initial angle of bridge structure I has an obvious effect on the output characteristics of the micro-displacement amplifying mechanism in the range of 5°–15°. When the lever’s rod length is 13 mm–15 mm, the bridge structure II’s rod length is 6 mm–7 mm, and the power arm length of bridge structure I’s driving lever is 5 mm–7 mm, the bridge structure II’s rod horizontal projection length is 5 mm–6 mm and the output displacement of the micro-displacement amplifying mechanism is larger. Through the optimal design, it is obtained that the bridge structure I’s initial angle is 8°, the lever’s rod length is 15 mm, the bridge structure II’s rod length is 7 mm, and the power arm length of bridge structure I driving lever is 5 mm, the bridge structure II’s rod horizontal projection length is 6 mm, and the simulated output displacement of the micro-displacement amplifying mechanism is 0.1415 mm. The prototype test reveals that as the input excitation displacement decreases, the error increases, while as the input excitation displacement increases, the error decreases. Specifically, when the input excitation displacement is 0.005 mm, the measured output displacement of the micro-displacement amplifying mechanism is 0.1239 mm, resulting in a 19.8% deviation from the theoretical value and a 12.44% deviation from the simulated value. The research work in this paper enriches the research achievements of non-contact piezoelectric actuators, and also provides a reference for designing small structure and large travel micro-displacement amplifying mechanisms of this type of actuator.

Fabrication of organic thin films using slit nozzle with a wide viscosity spectrum

A slit nozzle with a broad viscosity spectrum is highly demanded for slit coating of various materials with different viscosities without a compromise on the film quality. To this end, we have fabricated a multi-cavity slit nozzle with the inlet and vent holes for each cavity. Compared with a slit nozzle with a high-volume single cavity, such a multi-cavity slit nozzle further reduces the dead volume and thus material waste. As a design parameter in computational fluid dynamics (CFD) simulations for the multi-cavity slit nozzles, we have calculated the coefficient of variation in the internal pressure (Pcv) of the cavity and investigated the correlation between the simulated Pcv value and the measured thickness uniformity of low-viscosity (tens of cPs) poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), medium-viscosity (5000 cPs) polydimethylsiloxane (PDMS), and high-viscosity (18,000 cPs) hard-PDMS films. It is addressed that the Pcv value that can ensure the thickness non-uniformity of less than 5 % is of the order of 1 %, and the internal pressure of the nozzle should not exceed a specific upper limit to protect a coating system against overload. Based on the design guideline provided, we have found that the upper limit of the viscosity spectrum of the triple-cavity slit nozzle with the 800-μm-thick shim is 79,000 cPs when the flow rate is 50 ml/min. Using the multi-cavity slit nozzle, we have fabricated a highly uniform PDMS film exhibiting the tensile strain as high as 180 %, which can be used as a substrate for stretchable displays. Furthermore, we have successfully fabricated flexible OLED stripes on the slit-coated conductive PEDOT:PSS stripes, showing the average luminance of 72.8 cd/m2 at 5 V and inter-stripe luminance non-uniformity as low as 8.2 %.

Integrated analysis of remote sensing with meteorological and health data for allergic rhinitis forecasting in Tianjin.

Long time series of vegetation monitoring can be carried out by remote sensing data, the level of urban greening is objectively described, and the spatial characteristics of plant pollen are indirectly understood. Pollen is the main allergen in patients with seasonal allergic rhinitis. Meteorological factors affect the release and diffusion of pollen. Therefore, studying of the complex relationship between meteorological factors and allergic rhinitis is essential for effective prevention and treatment of the disease. In this study, we leverage remote sensing data for a comprehensive decade-long analysis of urban greening in Tianjin, which exhibits an annual increase in vegetative cover of 0.51 per annum, focusing on its impact on allergic rhinitis through changes in pollen distribution. Utilizing high-resolution imagery, we quantify changes in urban Fractional Vegetation Coverage (FVC) and its correlation with pollen types and allergic rhinitis cases. Our analysis reveals a significant correlation between FVC trends and pollen concentrations, with a surprising value of 0.71, highlighting the influence of urban greenery on allergenic pollen levels. We establish a robust connection between the seasonal patterns of pollen outbreaks and allergic rhinitis consultations, with a noticeable increase in consultations during high pollen seasons. our findings indicate a higher allergenic potential of herbaceous compared to woody vegetation. This nuanced understanding underscores the importance of pollen sensitivity, alongside concentration, in driving allergic rhinitis incidents. Utilizing a Generalized Linear Model, significant features influencing the number of visits for allergic rhinitis (P < 0.05) were identified. Both GLM and LSTM models were employed to forecast the visitation volumes for rhinitis during the spring and summer-autumn of 2022. Upon validation, it was found that the R² values between the simulated and actual values for both GLM and LSTM models surpassed the 95% confidence threshold. Moreover, the R² values for the summer-autumn seasons (GLM: 0.56, LSTM: 0.72) were higher than those for spring (GLM: 0.22, LSTM: 0.47). Comparing the errors between the simulated and actual values of GLM and LSTM models, LSTM exhibited higher simulation precision in both spring and summer-autumn seasons, demonstrating superior simulation performance. Overall, our study pioneers the integration of remote sensing with meteorological and health data for allergic rhinitis forecasting. This integrative approach provides valuable insights for public health planning, particularly in urban settings, and lays the groundwork for advanced, location-specific allergenic pollen forecasting and mitigation strategies.

Hydrodynamic modeling of dam breach floods for predicting downstream inundation scenarios using integrated approach of satellite data, unmanned aerial vehicles (UAVs), and Google Earth Engine (GEE)

Dam breach floods pose significant threats to downstream areas, necessitating accurate prediction of inundation scenarios to mitigate potential damage. This paper presents a novel methodology for hydrodynamic modeling of dam breach floods, leveraging a comprehensive approach that integrates satellite imagery, unmanned aerial vehicles (UAVs), and Google Earth Engine (GEE) to forecast downstream inundation scenarios. Specifically, UAVs were utilized to generate high-resolution Digital Elevation Models (DEMs) of the flood-affected areas, ensuring precise representation of topography in the model. The approach incorporates Cartosat DEM data for catchment modeling, while NASA's Global Precipitation Measurement mission data, integrated with GEE, facilitated accurate estimation of rainfall in ungagged catchment areas. Furthermore, the Hydrological Engineering Center-Hydrological Modeling System was employed for rainfall-runoff simulation and flood hydrograph derivation, followed by application of the HEC River Analysis System (RAS) for hydrodynamic modeling under dam breach conditions. This integrated modeling approach was applied as a case study of Banaskantha district, Gujarat, India. The outcome was the generation of scenario maps based on HEC-RAS results, which include flood extent, water depth, and flow velocity, highlighting downstream areas affected by flooding. Validation of the hydrodynamic dam breach model performance was conducted using actual field measurements and simulated results, employing statistical analysis methods including Support Vector Regression (SVR) and linear regression to determine coefficient of determination (R2), Root-Mean-Square Error, and Mean Absolute Error of observed and simulated data. The coefficient of determination (R2) values for measured and simulated flow (0.91) and water level (0.86) calculated using SVR demonstrate strong correlation between observed and simulated values. This integrated study of hydrodynamic modeling in data-scarce areas aids in accurate estimation of future probable flooding in downstream areas in the event of a dam break, underscoring the potential of advanced surveying and modeling techniques in flood assessment and management. Ultimately, this integration of technologies aims to enhance community resilience and mitigate socioeconomic costs associated with dam breach floods.

Thermal performance of MgCl2–NaCl–KCl eutectic salt for the next generation concentrated solar power and correlation between structure and thermophysical properties: Insights from atomic and electronic levels

MgCl2–NaCl–KCl (MgNaK) eutectic salt has emerged as a highly promising candidate for concentrated solar power (CSP), with extensive research conducted in recent years. However, the thermal property data for the MgNaK eutectic salt are still very limited. Here, we present a novel and accurate many-body potential trained by machine learning (ML) for MgNaK eutectic salt (with mole fractions of 45.4 %, 33 %, and 21.6 % respectively), developed using energies and forces extracted from first-principles molecular dynamics calculations (FPMD). The performance of the potential is well tested. We conduct a detailed investigation on the temperature-dependent structural and corresponding thermal properties, analyzing them from both the atomic and electronic perspectives. The introduction of Na+ or K+ ions disrupts the net structure formed by corner-joint and edge-joint MgClx units, thereby affecting the transport properties. The calculated density (ρ) and constant pressure specific heat capacity (CP) exhibit agreement with experimental data within a margin of 2 %. We observe and discuss the typical λ of negative linear temperature correlation, which is similar to other molten alkali chloride salts. Finally, based on the simulated and experimental values, we provide reliable recommendations for the λ and viscosities (η) of MgNaK eutectic salt across its entire operating temperature range.

Reconciling Rapid Glacial Erosion and Steady Basin Accumulation Rates in the Late Cenozoic Through the Effect of Glacial Sediment on Fluvial Erosion

AbstractThe onset of glaciation in the late Cenozoic caused rapid bedrock erosion above the snowline; however, whether the influx of eroded sediment is recorded in continental weathering and basin accumulation rates is an ongoing debate. We propose that the transport of glacially eroded bedrock through the fluvial system damps the signal of rapid headwater erosion and results in steady basin‐integrated sediment flux. Using a numerical model with integrated glacial and fluvial erosion, we find that headwater bedrock erosion rates increase rapidly at the onset of glaciation and continue to fluctuate with climatic oscillation. However, bedrock erosion rates decrease in the downstream fluvial system because larger grain sizes from glaciers result in an increase in sediment cover effect. When erosion and sediment flux rates are averaged, long‐term sediment flux is similar to nonglacial flux values, while localized bedrock erosion rates in the glaciated landscape are elevated 2–4 times compared to nonglacial values. Our simulated values are consistent with field measurements of headwater bedrock erosion, and the pattern of sediment flux and fluvial erosion matches paraglacial theory and terrace aggradation records. Thus, we emphasize that the bedload produced from glacial erosion provides a missing link to reconcile late Cenozoic erosion records.

Computer simulation help predict the frame deformation following a Venus-A transcatheter aortic valve implantation in patients with pure aortic regurgitation: a retrospective study.

Patient-specific computer simulation of transcatheter aortic valve implantation (TAVI) predicts the interaction between an implanted device and the surrounding anatomy. In this study, we validated the predictive value of computer simulation for the frame deformation following a Venus-A TAVI implant in patients with pure aortic regurgitation (AR). Furthermore, we used the validated computational model to evaluate the anchoring mechanism within the same cohort. This was a retrospective study. FEops HEARTguide technology was used to simulate the virtual implantation of a Venus-A valve model in a patient-specific geometry. The predicted frame deformation was quantitatively compared to the postoperative device deformation at multiple levels. The outward forces acting on the frame were extracted for each patient and the total outward force acting around the aortic annular (AA) and sinotubular junction (STJ) planes were recorded. Thirty patients were enrolled in the study with 10 in the migration group and 20 in the non-migration group. The dimensions of the simulated and observed frames had good correlations at Dmax (R2=0.88), Dmin (R2=0.91), perimeter (R2=0.92), and area (R2=0.92). The predicted outward force acting on the frame at the AA level was comparable between the migration and no-migration groups. The predicted outward force acting on the frame at the STJ level was always significantly higher in the migration group than the no migration group at different bandwidths: 3 mm (P=0.002), 5 mm (P=0.005), 10 mm (P=0.002). Patient-specific computer simulation of TAVI accurately predicted frame deformation in Chinese patients with pure AR. The forces at the STJ facilitated stabilization of the device within the aortic root, which might be used as a discriminator to identify patients at risk of device migration prior to intervention.

A methodology for computationally generating phase space files for Monte Carlo simulations applied to treatment plans for medical linear accelerators

The application of Monte Carlo (MC) simulation in the context of Medical Linear Accelerator (LinAc) treatment planning has increased in recent decades owing to its accuracy in dose calculations. The Multileaf Collimator (MLC), a component of the LinAc heads, plays an essential role by allowing the precise customization of the treatment beam's shape, effectively targeting the tumor area while minimizing radiation exposure to surrounding healthy structures. During a jaws static treatment, this MLC configuration varies for each angular position of the accelerator gantry, while the rest of the LinAc geometry remains static. To address the operation of the accelerator during the treatment planning avoiding the need of computationally intensive and repetitive simulations, phase-space files (PSF) are widely employed in LinAc MC calculations. This study aims to introduce and validate a methodology for the computational generation of PSFs specifically defined just below the MLC. These PSFs will assume the appropriate shape corresponding to the angle at which the accelerator gantry is positioned during treatment. The core of this methodology involves the creation of a comprehensive database containing precalculated probability functions derived from MC. In order to validate the methodology, simulated dose values of a LinAc emitting a 6 MV photon beam have been employed. The results have been tested against experimental data, and compared with the results from complete simulations, yielding PSFs of varying shapes. Finally, this study reveals that the results obtained by comparing organ dose values computed from the generated PSFs to those from the reference PSF are statistically compatible. This innovative method not only offers a valuable tool for optimizing LinAc treatment planning but also underscores the importance of accurate dose calculations in the field of radiation therapy.