Search Results (34)

The safety performance of liquid hydrogen storage has a significant influence on its large-scale commercial application. Due to the complexity and costs of experimental investigation, computational fluid dynamics (CFD) simulations have been extensively applied to investigate the dynamic behaviors of liquid hydrogen release. The involved physical and chemical models, such as models of species thermodynamic properties and liquid–gas mass transfer, play a major role for the entire CFD model performance. However, comprehensive investigations into their impacts remain insufficient. In this study, CFD models of liquid hydrogen release were developed by using two widely used commercial simulation tools, Fluent and FLACS, and validated against experimental data available in the literature. Comparisons of the model results reveal strong discrepancies in the prediction accuracy of temperature and hydrogen volume fraction between the two models. The impact of the models of thermodynamic properties and liquid–gas mass transfer on the prediction results was subsequently explored by incorporating the FLACS sub-models to Fluent and evaluating the resulting prediction differences in temperatures and hydrogen volume fractions. The results show that the models of thermodynamic properties and liquid–gas mass transfer used in FLACS underestimate the vertical rise height and the highest hydrogen volume fraction of the cloud. Sensitivity analyses on the parameters in these sub-models indicate that the specific heats of hydrogen and nitrogen, in conjunction with the mass flow rate and outflow density of the mass transfer model, have a significant influence on model prediction of temperature. Full article

The trend of adapting powder bed fusion (PBF) for product manufacturing continues to grow as this process is highly capable of producing functional 3D components with micro-scale precision. The powder bed’s properties (e.g., powder packing, material properties, flowability, etc.) and thermal energy deposition heavily influence the build quality in the PBF process. The packing density in the powder bed dictates the bulk powder behavior and in-process performance and, therefore, significantly impacts the mechanical and physical properties of the printed components. Numerical modeling of the powder bed process helps to understand the powder spreading process and predict experimental outcomes. A two-dimensional powder bed was developed in this work using the LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) package to better understand the effect of bimodal and unimodal particle size distribution on powder bed packing. A cloud-based pouring of powders with varying volume fractions and different initialization velocities was adopted, where a blade-type recoater was used to spread the powders. The packing fraction was investigated for both bimodal and unimodal systems. The simulation results showed that the average packing fraction for bimodal and unimodal systems was 76.53% and 71.56%, respectively. A particle-size distribution-based spatially varying powder agglomeration was observed in the simulated powder bed. Powder segregation was also studied in this work, and it appeared less likely in the unimodal system compared to the bimodal system with a higher percentage of bigger particles. Full article

The starting point for the preparation of polymeric membranes by phase inversion is having a thermodynamically stable solution. Ternary diagrams for the polymer, solvent, and non-solvent can predict this stability by identifying the phase separation and describing the thermodynamic behavior of the membrane formation process. Given the lack of data for the ternary system water (H₂O)/hydrochloric acid (HCℓ)/polyamide 66 (PA66), this work employed the Flory–Huggins theory for the construction of the ternary diagrams (H₂O/HCℓ/PA66 and H₂O/formic acid (FA)/PA66) by comparing the experimental data with theoretical predictions. Pure polymer and the membranes produced by phase inversion were characterized to provide the information required to create the ternary diagrams. PA66/FA and PA66/HCℓ solutions were also evaluated regarding their classification as true solutions, and the universal quasi-chemical functional group activity coefficient (UNIFAC) method was used for determining non-solvent/solvent interaction parameters (g₁₂). Swelling measurements determined the polymer/non-solvent interaction parameter (χ₁₃) for H₂O/PA66 and the solvent/polymer interaction parameter (χ₂₃) for PA66/FA and PA66/HCℓ. The theoretical cloud point curve was calculated based on “Boom’s LCP Correlation” and compared to the curve of the experimental cloud point. The ternary Gibbs free energy of mixing and χ₂₃ indicated FA as the best solvent for the PA66. However, for HCℓ, the lower concentration (37–38%), volatility, and fraction volume of dissolved PA66 (ϕ₃) indicated that HCℓ is also adequate for PA66 solubilization based on the similar membrane morphology observed when compared to the PA66/FA membrane. Full article

Since 2020, southern Brazil’s Rio Grande do Sul (RS) State has been affected by extreme precipitation episodes caused by different atmospheric systems. However, the most extreme was registered between the end of April and the beginning of May 2024. This extreme precipitation caused floods in most parts of the state, affecting 2,398,255 people and leading to 183 deaths and 27 missing persons. Due to the severity of this episode, we need to understand its drivers. In this context, the main objective of this study is a multi-scale analysis of the extreme precipitation between 26 April and 5 May, i.e., an analysis of the large-scale patterns of the atmosphere, a description of the synoptic environment, and an analysis of the mesoscale viewpoint (cloud-top features and lightning). Data from different sources (reanalysis, satellite, radar, and pluviometers) were used in this study, and different methods were applied. The National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN) registered accumulated rainfall above 400 mm between 26 April and 5 May using 27 pluviometers located in the central-northern part of RS. The monthly volumes reached 667 mm and 803 mm, respectively, for April and May 2024, against a climatological average of 151 mm and 137 mm for these months. The maximum precipitation recorded was 300 mm in a single day on 30 April 2024. From a large-scale point of view, an anomalous heat source in the western Indian Ocean triggered a Rossby wave that contributed to a barotropic anticyclonic anomalous circulation over mid-southeastern Brazil. While the precipitant systems were inhibited over this region (the synoptic view), the anomalous stronger subtropical jet southward of the anticyclonic circulation caused uplift over RS State and, consequently, conditions leading to mesoscale convective system (MCS) development. In addition, the low-level jet east of the Andes transported warm and moist air to southern Brazil, which also interacted with two cold fronts that reached RS during the 10-day period, helping to establish the precipitation. Severe deep MCSs (with a cloud-top temperature lower than −80 °C) were responsible for a high lightning rate (above 10 flashes km⁻² in 10 days) and accumulated precipitation (above 600 mm in 10 days), as observed by satellite measurements. This high volume of rainfall caused an increase in soil moisture, which exceeded a volume fraction of 0.55, making water infiltration into the soil difficult and, consequently, favoring flood occurrence. Full article

Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in the storage area of a hydrogen production station is numerically simulated. The effects of ambient wind direction, wind speed, leakage mass flow rate, and the mass fraction of gas phase at the leakage port on the diffusion behavior of the liquid hydrogen leakage were investigated. The results show that the ambient wind direction directly determines the direction of liquid hydrogen leakage diffusion. The wind speed significantly affects the diffusion distance. When the wind speed is 6 m/s, the diffusion distance of the flammable hydrogen cloud reaches 40.08 m, which is 2.63 times that under windless conditions. The liquid hydrogen leakage mass flow rate and the mass fraction of the gas phase have a greater effect on the volume of the flammable hydrogen cloud. As the leakage mass flow rate increased from 5.15 kg/s to 10 kg/s, the flammable hydrogen cloud volume increased from 5734.31 m³ to 10,305.5 m³. The installation of a barrier wall in front of the leakage port can limit the horizontal diffusion of the flammable hydrogen cloud, elevate the diffusion height, and effectively reduce the volume of the flammable hydrogen cloud. This study can provide theoretical support for the construction and operation of hydrogen production stations. Full article

Forest aboveground biomass (AGB) retrieval using synthetic aperture radar (SAR) backscatter has received extensive attention. The water cloud model (WCM), because of its simplicity and physical significance, has been one of the most commonly used models for estimating forest AGB using SAR backscatter. Nevertheless, forest AGB estimation using the WCM is usually based on simplified assumptions and empirical fitting, leading to results that tend to overestimate or underestimate. Moreover, the physical connection between the model and the polarimetric synthetic aperture radar (PolSAR) is not established, which leads to the limitation of the inversion scale. In this paper, based on the fully polarimetric SAR data from the Advanced Land Observing Satellite-2 (ALOS-2) Phased Array-type L-band Synthetic Aperture Radar (PALSAR-2), the relative contributions of the three major scattering mechanisms were first analyzed in a hilly area of southern China. On this basis, the traditional WCM was extended by considering the secondary scattering mechanism. Then, to establish the direct relationship between the vegetation scattering mechanism and forest AGB, a new relationship equation between the PolSAR decomposition model and the improved water cloud model (I-WCM) was constructed without the help of external data. Finally, a nonlinear iterative method was used to estimate the forest AGB. The results show that volume scattering is the dominant mechanism, accounting for more than 60%. Double-bounce scattering accounts for the smallest fraction, but still about 10%, which means that the contribution of the double-bounce scattering component is not negligible in forested areas because of the strong penetration capability of the long-wave SAR. The modified method provides a correlation coefficient R² of 0.665 and a root mean square error (RMSE) of 21.902, which is an improvement of 36.42% compared to the traditional fitting method. Moreover, it enables the extraction of forest parameters at the pix scale using PolSAR data without the need for low-resolution external data and is thus helpful for high-resolution mapping of forest AGB. Full article

Understory biomass plays an important role in forests, and explicit characterizations of live and dead understory vegetation are critical for wildland fuel characterization and to link understory vegetation to ecosystem processes. Current methods to accurately model understory fuel complexity in 3D rely on expensive and often inaccessible technologies. Structure-from-motion close-range photogrammetry, in which ordinary photographs or video stills are overlaid to generate point clouds, is promising as an alternative method to generate 3D models of fuels at a fraction of the cost of more traditional field surveys. In this study, we compared the performance of close-range photogrammetry with field sampling surveys to assess the utility of this alternative technique for quantifying understory fuel structure. Using a commercially available GoPro camera, we generated 3D point cloud models from video-derived image stills of 138 sampling plots across two western ponderosa pine and two southeastern slash pine sites. We directly compared structural metrics derived from the photogrammetry to those derived from field sampling, then evaluated predictive models of biomass calibrated by means of destructive sampling. Photogrammetry-derived measures of occupied volume and fuel height showed strong agreements with field sampling (Pearson’s R = 0.81 and 0.86, respectively). While we found weak relationships between photogrammetry metrics and biomass 0 to 10 cm in height, occupied volume and a novel metric to characterize the vertical profile of vegetation produced the strongest relationships with biomass above the litter layer (i.e., >10 cm) across different fuel types (R² = 0.55–0.76). The application of this technique has the potential to provide managers with an accessible option for inexpensive data collection and can lay the groundwork for the rapid collection of input datasets to train landscape-scale fuel models. Full article

Thunderstorms are the main natural source of forest fires. The ignition mechanism of trees begins with the impact of cloud-to-ground lightning discharge. A common drawback of all predicting systems is that they ignore the physical mechanism of forest fire as a result of thunderstorm activity. The purpose of this article is to develop a physically based mathematical model for the ignition of a coniferous tree via cloud-to-ground lightning discharge, taking into account thermophysical, electrophysical, and physicochemical processes. The novelty of the article is explained by the development of an improved mathematical model for the ignition of coniferous trees via cloud-to-ground lightning discharge, taking into account the processes of soot formation caused by the thermal decomposition phase of dry organic matter. Mathematically, the process of tree ignition is described by a system of non-stationary nonlinear differential equations of heat conduction and diffusion. In this research, a locally one-dimensional method is used to solve three-dimensional partial differential equations. The finite difference method is used to solve one-dimensional heat conduction and diffusion equations. Difference analogues of the equations are solved using the marching method. To resolve nonlinearity, a simple iteration method is used. Temperature distributions in a structurally inhomogeneous trunk of a coniferous tree, as well as distributions of volume fractions of phases and concentrations of gas mixture components, are obtained. The conditions for tree trunk ignition under conditions of thunderstorm activity are determined. As a result, a complex three-dimensional mathematical model is developed, which makes it possible to identify the conditions for the ignition of a coniferous tree trunk via cloud-to-ground lightning discharge. Full article

The cloud amount, referred to as the frequency of cloud occurrences, is of great importance for the Earth–atmosphere system. It was conventionally quantified as the area fraction of clouds in a given region, discarding the three-dimensional nature of both cloud entities and their spatial distribution. Although the area fraction is explicit, it is the volume fraction that fully depicts cloud occurrences, and the area fraction is just related to a projection of the volume fraction. In this study, by using spaceborne radar measurements, the spatial distribution of cloud volume fraction throughout the troposphere was investigated, and the contributions of various cloud types at each location were clarified. Overall, the volume fraction of total clouds in the whole troposphere is 15.9%, while the corresponding area fraction relative to the global surface is 73.6%. The peak volume fraction occurs at 1 km altitude, mainly contributed by stratocumulus and cumulus. For a single cloud type, the maximum fraction is 48.8%, which is from stratocumulus and occurs at 1 km altitude above the Greenland Sea. Half of the eight cloud types, altostratus, cirrus, nimbostratus, and deep convective clouds, reach the nominal tropopause. In particular, the vertical distribution difference among multiple cloud types in each category (low-level, middle-level, and vertically extending) was clarified, and it was found that the dominant cloud type in a category varies notably with the location in the atmosphere. Full article

A model of a submerged angular cavitation nozzle is established, which consists of a contraction part, parallel middle part, and expansion part. Based on the CFD technique, a numerical simulation of the flow field of the submerged cavitation nozzle is carried out, in which a multiphase mixture model, cavitation model, and renormalization group (RNG) k-ε turbulence model are applied. Considering the influence of mixture density on cavitation, the effects of the inlet contraction part, parallel middle part, and outlet expansion part on the velocity and vapor volume fraction are studied. The numerical simulation results show that the mixture density is essential in the cavitation jet. When the nozzle diameter d is fixed, the designed angular cavitation nozzle with contraction angle α = 13.5°, parallel middle part length Ld = 3d, expansion part length Le = 4d, and expansion angle β = 60° can effectively bring out cavitation. A cavitation cloud is produced near the rigid wall of the outlet expansion section and diffuses in a vortex ring shape. Optimizing the nozzle structure can improve the cavitation effect of the nozzle. The feasibility of this model is verified by relevant experimental data. Full article

Understanding the network usage patterns of university users is very important today. This paper focuses on the research of DNS request behaviors of university users in Shanghai, China. Based on the DNS logs of a large number of university users recorded by CERNET, we conduct a general analysis of the behavior of network browsing from two perspectives: the characteristics of university users’ behavior and the market share of CDN service providers. We also undertake experiments on DNS requests patterns for CDN service providers using different prediction models. Firstly, in order to understand the university users’ Internet access patterns, we select the top seven universities with the most DNS requests and reveal the characteristics of different university users. Subsequently, to obtain the market share of different CDN service providers, we analyze the overall situation of the traffic distribution among different CDN service providers and its dynamic evolution trend. We find that Tencent Cloud and Alibaba Cloud are leading in both IPv4 and IPv6 traffic. Baidu Cloud has close to 15% in IPv4 traffic, but almost no fraction in IPv6 traffic. Finally, for the characteristics of different CDN service providers, we adopt statistical models, traditional machine learning models, and deep learning models to construct tools that can accurately predict the change in request volume of DNS requests. The conclusions obtained in this paper are beneficial for Internet service providers, CDN service providers, and users. Full article

This article presents a method, based on orbital remote sensing, to map the extent of forest plantations in São Paulo State (Southeast Brazil). The proposed method uses the random forest machine learning algorithm available on the Google Earth Engine (GEE) cloud computing platform. We used 30 m annual mosaics derived from Landsat-5 Thematic Mapper (TM) images and from Landsat-8 Operational Land Imager (OLI) images for the 1985 to 1995 and 2013 to 2021 time periods, respectively. These time periods were selected based on the planted areas’ rotation, especially the eucalypt’s short rotation. To classify the forest plantations, green, red, NIR, and MIR spectral bands, NDVI, GNDVI, NDWI, and NBR spectral indices, and vegetation, shade, and soil fractions were used for both sensors. These indices and the fraction images have the advantage of reducing the volume of data to be analyzed and highlighting the forest plantations’ characteristics. In addition, we also generated one mosaic for each fraction image for the TM and OLI datasets by computing the maximum value through the period analyzed, facilitating the classification of areas occupied by forest plantations in the study area. The proposed method allowed us to classify the areas occupied by two forest plantation classes: eucalypt and pine. The results of the proposed method compared with the forest plantation areas extracted from the land use and land cover maps, provided by the MapBiomas product, presented the Kappa values of 0.54 and 0.69 for 1995 and 2020, respectively. In addition, two pilot areas were used to evaluate the classification maps and to monitor the phenological stages of eucalypt and pine plantations, showing the rotation cycle of these plantations. The results are very useful for planning and managing planted forests by commercial companies and can contribute to developing an automatic method to map forest plantations on regional and global scales. Full article

Cloud point extraction is a versatile method aimed at separating compounds from complex mixtures and arouses great technological interest, particularly among the biochemical industries. However, one must have deep knowledge of the liquid–liquid equilibrium behavior of systems to properly use the method. Thus, we used thermodynamic parameters to evaluate the effect of citrate, sulfate, and tartrate anions on the phase separation of water + Triton X-114^® mixtures at 283.2 K, 293.2 K, and 303.2 K. In these systems, increasing the temperature and the anion molar fraction expanded the biphasic region in the following order: ${\mathrm{C}}_6{\mathrm{H}}_5{\mathrm{O}}_7^{3-}$> ${\mathrm{SO}}_4^{2-}$ > ${ \mathrm{C}}_4{\mathrm{H}}_4{\mathrm{O}}_6^{2-}$. Unlike other studies based on the Hofmeister series, the Gibbs free energy of micellization correlated the anion effect on the biphasic region with the spontaneity of the micelle formation. The water molecules structured around these anions were evaluated according to the shell volume of the immobilized water by electrostriction, volume of water around the hydration shell, Gibbs free energy of hydration, and Gibbs free energy of electrostriction ($\Delta {\mathrm{G}}_{\mathrm{el}12}$). The citrate anion presented a higher $\Delta {\mathrm{G}}_{\mathrm{el}12}$ of −1781.49 kJ mol⁻¹, due to the larger number of electrons around it. In addition, the partition coefficient of the surfactant in the two liquid phases revealed a linear dependence upon the anion mole fractions by following the previous anion sequence and temperature in the phase separation. Full article

In order to improve the precipitation forecast of the next-generation Global Prediction System with the Finite-Volume Cubed-Sphere Dynamical Core in Taiwan’s Central Weather Bureau, this study modified the convective processes in the New Simplified Arakawa-Schubert scheme based on the methodology of scale-aware parameterization developed in Kwon and Hong (2017) and investigated its impacts on a front event, which propagated across Taiwan and produced heavy rainfall in late May of 2020. Results show that the modified scale-aware parameterization has significantly improved the intensity and the spatial distribution of frontal precipitation forecasts due to the proper definition of convective updraft fraction. However, the synoptic-scale features perform a larger warm bias with the modified scale-aware parameterization. Therefore, further modification of the scale-aware capability of convective cloud water detrainment is proposed to reduce the heating from microphysical processes and result in a better overall performance for the medium-range weather forecasts. Full article

The objective of this paper was to estimate soil moisture in pepper crops with drip irrigation in a semi-arid area in the center of Tunisia using synthetic aperture radar (SAR) data. Within this context, the sensitivity of L-band (ALOS-2) in horizontal-horizontal (HH) and horizontal-vertical (HV) polarizations and C-band (Sentinel-1) data in vertical-vertical (VV) and vertical-horizontal (VH) polarizations is examined as a function of soil moisture and vegetation properties using statistical correlations. SAR signals scattered by pepper-covered fields are simulated with a modified version of the water cloud model using L-HH and C-VV data. In spatially heterogeneous soil moisture cases, the total backscattering is the sum of the bare soil contribution weighted by the proportion of bare soil (one-cover fraction) and the vegetation fraction cover contribution. The vegetation fraction contribution is calculated as the volume scattering contribution of the vegetation and underlying soil components attenuated by the vegetation cover. The underlying soil is divided into irrigated and non-irrigated parts owing to the presence of drip irrigation, thus generating different levels of moisture underneath vegetation. Based on signal sensitivity results, the potential of L-HH data to retrieve soil moisture is demonstrated. L-HV data exhibit a higher potential to retrieve vegetation properties regarding a lower potential for soil moisture estimation. After calibration and validation of the proposed model, various simulations are performed to assess the model behavior patterns under different conditions of soil moisture and pepper biophysical properties. The results highlight the potential of the proposed model to simulate a radar signal over heterogeneous soil moisture fields using L-HH and C-VV data. Full article