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Waste generation is a part of every technological process, including galvanizing. The presented paper deals with the characterization of flue dust generated in the process of hot-dip galvanizing, and proposes possible methods for zinc recycling. The flue dust is released into the atmosphere as a white fume above the zinc bath, which is caused by the decomposition of ammonium chloride and zinc chloride present in the flux. This dust is classified as hazardous waste and is a material with a particle size below 90 µm. In addition to zinc and iron compounds, it contains water vapor and oils. The presented elemental, phase, and other characteristic methods of flue dust are important for the subsequent selection of a suitable method for processing the material. At present, this waste is not processed separately due to its low production, which is approximately 0.3 kg per 1 tonne of galvanized steel. The proposed hydrometallurgical recycling method enables the processing of flue dust on a small scale and enables the recovery of high-purity zinc in the form of metallic zinc or zinc oxide. [ABSTRACT FROM AUTHOR]

The process of mining produces a large amount of heavy metals and high-sulfate mine water, which is the main factor leading to environmental degradation in the mining area, and the removal of heavy metals and the recovery of sulfate from mine water is a difficult problem faced by mines today. Currently, sulfate is treated as a hazardous substance and is not recycled. In this paper, the precipitation–adsorption bipolar membrane electrodialysis (BMED) multi-technology-coupled recovery of sulfate method was used to treat mine water. The results showed that the coupling technology could remove heavy metals and sulfate in water better, while the sulfate desalination rate was about 96.8%, current efficiency was 54.2%, energy consumption was 0.823 kWh/kg, and the acid production concentration was 0.168 at an electrolyte concentration of 0.1 mol/L, an operating voltage of 12 V, an initial salt concentration of 30 g/L, and a flow rate of 3.5 mL/min. Mechanistic results showed that the precipitation–adsorption method could realize the removal of heavy metals from mine water. The BMED process realized the removal of sulfate and also the recovery of acid. The multi-technology coupling of precipitation–adsorption and bipolar membrane electrodialysis explored in this paper provides a direction for the in-depth treatment of mine water. [ABSTRACT FROM AUTHOR]

Strip shape control is a hotspot and challenge in strip rolling, where the development trend of rolling technology is towards high strength, high toughness, and a large width-to-thickness ratio. The influence of material microstructure evolution on strip shape control is being increasingly emphasized. In this paper, a Nb-Ti microalloyed steel is taken as the research object. Thermodynamic and kinetic models focusing on the precipitation of the austenite phase are established to quantify the precipitation process. A coupled model of rolls and strips is built using ABAQUS 2022 software, where the precipitation strengthening model and high-temperature constitutive model are embedded into the finite element model (FEM) through subroutines. A two-dimensional alternating differential model is employed to acquire real-time temperature differences in the width direction of the strip. The effects of precipitation inclusion and exclusion on the strip crown under different operating conditions are compared and analyzed. The results indicate that as the temperature decreases, the strengthening effect increases, reaching around 40 MPa at temperatures above 1000 °C and 96.6 MPa at 800 °C. Furthermore, the inclusion of crown in the precipitation consideration is more sensitive to overall temperature changes, but as the strip width decreases, the sensitivity of crown to temperature decreases. The research findings of this paper provide guidance for improving strip shape control and reducing abnormalities during the rolling process. [ABSTRACT FROM AUTHOR]

Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model's robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model's superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min. [ABSTRACT FROM AUTHOR]

Rockfalls are incidents of nature that take place when rocks or boulders break from a steep slope and fall to the ground. They can pose considerable threats to buildings placed in high-risk zones. Despite the fact that the impact of a rockfall on a building can cause structural and non-structural damage, few studies have been undertaken to investigate the danger associated with this event. Most of these studies indicated that the risk resulting from rockfall hazards is hard to forecast and assess. A comprehensive quantitative risk assessment approach for rockfalls on buildings is developed and described in this paper and applied for the Mtein village in Mount Lebanon. This method employs a 3D model to simulate the rockfall trajectories using a combination of digital elevation data, field surveys, and orthorectified aerial photographs. The spatial and temporal probability of rockfalls were evaluated using the analysis of historical data in two triggering-factor scenarios: earthquake and precipitation. The findings show that, during the period of 1472 years between the years 551 (the first observed large earthquake in Lebanon) and the current year of the study (2023), the temporal probability will potentially be equal to 0.002 and 0.105 in the cases of earthquake- and rainfall-triggered rockfalls, respectively, while the maximal damage values are expected to be 232 USD and 10,511 USD per year, respectively. The end result is a final map presenting the risk values assigned to each building that could be damaged by rockfalls. [ABSTRACT FROM AUTHOR]

In this paper, a sequence (1979–2022) of a long-term trial established in Lukavec in 1956 (Czech Republic) focusing on the effect of weather, various nitrogen (N) fertilization methods (control, PK, N1PK, N2PK, and N3PK) and preceding crops (cereals, legumes, and oil plants) on winter wheat grain yield is presented. The weather significantly changed at the site of the long-term trial. While the trend in the mean temperature significantly increased, precipitation did not change significantly over the long term. Four relationships between weather and grain yield were evaluated to be significant: (a) the mean temperature in February (r = −0.4) and the precipitation in (b) February (r = −0.4), (c) March (r = −0.4), and (d) May (r = 0.5). The yield trends for all the fertilizer treatments increased, including the unfertilized control. The N3PK treatment provided the highest mean grain yields, while the unfertilized control had the lowest yields. Comparing the preceding crops, the highest yields were harvested when the wheat followed the legumes. On the other hand, the cereals were evaluated as the least suitable preceding crop in terms of grain yield. According to the linear-plateau model, the optimal nitrogen (N) dose for modern wheat varieties, following legumes and under the trial's soil climate conditions, was 131 kg ha−1 N, corresponding to a mean grain yield of 8.2 t ha−1. [ABSTRACT FROM AUTHOR]

Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific basis for water resource management, protection, and planning. Traditional hydrological observation methods, often reliant on experience and statistical methods, are time-consuming and labor-intensive, frequently resulting in predictions of limited accuracy. However, machine learning technologies enhance the efficiency and sustainability of water resource modeling by analyzing extensive hydrogeological data, thereby improving predictions and optimizing water resource utilization and allocation. This review investigates the application of machine learning for predicting various aspects, including precipitation, flood, runoff, soil moisture, evapotranspiration, groundwater level, and water quality. It provides a detailed summary of various algorithms, examines their technical strengths and weaknesses, and discusses their potential applications in water resource modeling. Finally, this paper anticipates future development trends in the application of machine learning to water resource modeling. [ABSTRACT FROM AUTHOR]

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters. [ABSTRACT FROM AUTHOR]

The occurrence of harmful algal blooms (HABs) in coastal and inland waters has a significant impact on societies. This complex biogeophysical phenomenon becomes further complicated due to the impact of climate change. This review summarizes the research performed in recent years in the direction of climate change on three lake parameters, viz. lake temperature, precipitation, runoff, and lake ice, which impacts the lake ecology and, in turn, impacts the HABs. The present paper also reviews the research work related to the relationship between climate change and HABs. The purpose of this study is to provide the researchers with the opportunity to understand the current research in the direction of climate change and HABs so they can contribute effectively to one of the most important phenomena that will severely impact water quality in the future warmer climate, in coastal as well as inland water bodies. Furthermore, this work aims to discuss how HABs will change in the future warmer climate. [ABSTRACT FROM AUTHOR]

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [ABSTRACT FROM AUTHOR]

The capillary barrier is a type of soil cover system commonly used in various geotechnical applications, such as limiting infiltration for slopes or landfills or providing cover for solid waste. It serves to prevent the movement of water through the soil layers by utilizing contrasting particle sizes. This paper focuses on investigating the effect of the granular layer on the performance of a three-layer cover with a capillary barrier, integrating the granular layer within clayey sand. The investigation involved one-dimensional infiltration tests utilizing four uniform granular soils with varying grain sizes. These tests were instrumental in calibrating soil water characteristic curves and hydraulic conductivity curves via back analysis. Subsequently, numerical analyses were conducted using a 15 m long model for each of the four distinct cover types. The results indicated that the fine gravel significantly improved the barrier performance beyond one-dimensional tests, owing to its high permeability and the influence of the slope. After the capillary barrier failure, the intermediate layers transitioned into efficient drainage layers, particularly in the gravel layer with the highest lateral drainage capacity. Clayey sand at the bottom delayed percolation, thereby supporting the conversion of the intermediate layer into an effective drainage component. Overall, the multi-layer system showed superior percolation performance compared to the clayey sand cover lacking a granular layer. [ABSTRACT FROM AUTHOR]

The measurement of global precipitation is important for quantifying and understanding the Earth's systems. While gauges form the basis of conventional measurements, global measurements are only truly possible using satellite observations. Over the last 50–60 years, satellite systems have evolved to provide a comprehensive suite of observing systems, including many sensors that are capable of precipitation retrievals. While much progress has been made in developing and implementing precipitation retrieval schemes, many techniques have concentrated upon retrievals over regions with well-defined precipitation systems, such as the tropics. At higher latitudes, such retrieval schemes are less successful in providing accurate and consistent precipitation estimates, especially due to the large diversity of precipitation regimes. Furthermore, the increasing dominance of snowfall at higher latitudes imposes a number of challenges that require further, urgent work. This paper reviews the state of the current observations and retrieval schemes, highlighting the key factors that need to be addressed to improve the estimation and measurement of precipitation at mid-to-high latitudes. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) run at regional resolution or at a continental scale. Therefore, these results cannot be used directly for local temperatures and precipitation prediction. Downscaling techniques are required to calibrate GCMs. Statistical downscaling models (SDSM) are the most widely used for bias correction of GCMs. However, few studies have compared SDSM with multi-layer perceptron artificial neural networks and in most of these studies, results indicate that SDSM outperform other approaches. This paper investigates an alternative architecture of neural networks, namely the long-short-term memory (LSTM), to forecast two critical climate variables, namely temperature and precipitation, with an application to five climate gauging stations in the Lake Chad Basin. Lake Chad is a data scarce area which has been impacted by severe drought, where water resources have been influenced by climate change and recent agricultural expansion. SDSM was used as the benchmark in this paper for temperature and precipitation downscaling for monthly time–scales weather prediction, using grid resolution GCM output at a 5 degrees latitude × 5 degrees longitude global grid. Three performance indicators were used in this study, namely the root mean square error (RMSE), to measure the sensitivity of the model to outliers, the mean absolute percentage error (MAPE), to estimate the overall performance of the predictions, as well as the Nash Sutcliffe Efficiency (NSE), which is a standard measure used in the field of climate forecasting. Results on the validation set for SDSM and test set for LSTM indicated that LSTM produced better accuracy on average compared to SDSM. For precipitation forecasting, the average RMSE and MAPE for LSTM were 33.21 mm and 24.82% respectively, while the average RMSE and MAPE for SDSM were 53.32 mm and 34.62% respectively. In terms of three year ahead minimum temperature forecasts, LSTM presents an average RMSE of 4.96 degree celsius and an average MAPE of 27.16%, while SDSM presents an average RMSE of 8.58 degree celsius and an average MAPE of 12.83%. For maximum temperatures forecast, LSTM presents an average RMSE of 4.27 degree celsius and an average MAPE of 11.09 percent, while SDSM presents an average RMSE of 9.93 degree celsius and an average RMSE of 12.07%. Given the results, LSTM may be a suitable alternative approach to downscale global climate simulation models' output, to improve water management and long-term temperature and precipitations forecasting at local level. [ABSTRACT FROM AUTHOR]

Hierarchical organic structures have gained vast attention in the past decade owing to their great potential in chemical and medical applications in industries such as the food and pharmaceutical industries. In this paper, the crystallization of L-glu hierarchical spheres using inorganic ions, namely calcium, barium and strontium cations, is described. The anti-solvent precipitation method is used for the spherical crystallization. The L-glu microspheres are characterized using various techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photo-electron microscopy (XPS) and polarized microscopy (POM). It is shown that without additives, L-glu crystallizes as flower-like structures, very different from the hierarchical spheres crystallized with the charged additives. Based on our results, we suggest a mechanism for the hierarchical sphere formation based on the crystallization and self-assembly of L-glu in emulsion droplets using charged additives. [ABSTRACT FROM AUTHOR]

With advances in the development of autonomous vehicles (AVs), more attention has been paid to the effects caused by adverse weather conditions. It is well known that the performance of self-driving vehicles is reduced when they are exposed to stressors that impair visibility or cause water or snow accumulation on sensor surfaces. This paper proposes a model to quantify weather precipitation, such as rain and snow, perceived by moving vehicles based on outdoor data. The modeling covers a wide range of parameters, such as varying the wind direction and realistic particle size distributions. The model allows the calculation of precipitation intensity on inclined surfaces of different orientations and on a circular driving path. The modeling results were partially validated against direct measurements carried out using a test vehicle. The model outputs showed a strong correlation with the experimental data for both rain and snow. Mitigation strategies for heavy precipitation on vehicles can be developed, and correlations between precipitation rate and accumulation level can be traced using the presented analytical model. A dimensional analysis of the problem highlighted the critical parameters that can help the design of future experiments. The obtained results highlight the importance of the angle of the sensing surface for the perceived precipitation level. The proposed model was used to analyze optimal orientations for minimization of the precipitation flux, which can help to determine the positioning of sensors on the surface of autonomous vehicles. [ABSTRACT FROM AUTHOR]

The casting of metal alloys followed by hot forging is a widely used manufacturing technology to produce a homogeneous microstructure. The combination of mechanical and thermal energy envisages the microstructural properties of metal alloys. In the present investigation, a metal alloy of composition 0.05C-1.52Cu-1.51Mn (in weight %) was cast in an induction furnace using a zirconia crucible. The melt pool was monitored using optical emission spectroscopy (OES) to maintain the desired composition. The as-cast block was then subjected to forging under a pneumatic hammer of 0.5 t capacity so that any casting defects were eliminated. The as-cast block was reheated to a temperature of 1050 °C and held at that temperature for 6 h to homogenize, followed by hammering with a 50% strain using a pneumatic hammer. The microhardness was calculated using a Vickers microhardness testing apparatus. The microstructure characterization of the processed alloy was carried out using an optical microscope, electron backscattered diffraction (EBSD), energy-dispersive X-ray spectroscopy (EDXA), and a transmission electron microscope (TEM). The sample for optical microscopy was cut using a diamond cutter grinding machine and surface polishing was carried out using emery paper. Further, mechanical polishing was performed to prepare the samples for EBSD using a TEGRAPOL polishing machine. The EBSD apparatus was operated at a 20 kV accelerating voltage, 25 mm from the gun, and with a 60 µ aperture size. HKL Technology Channel 5 Software was used for the post-processing of EBSD maps. The procedure of standard polishing for OES and TEM sample preparation was followed. Recrystallization envisages equiaxed grain formation in hot forging; hence, the strain-free grains were observed in the strained matrix. The lower distribution of recrystallized grains indicated that the driving force for recrystallization was not abundant enough to generate a fully recrystallized microstructure. The fractional distribution of the misorientation angle between 15 and 60° confirms the formation of grain boundaries (having a misorientation angle greater than 15°) and dislocations/subgrain/substructures (having a misorientation angle less than 15°). The fraction of misorientation angle distribution was higher between the angles 0.5 and 6.5°; afterwards, it decreased for higher angles. The substructure was observed in the vicinity of grain boundaries. The softening process released certain strains, but still, the dislocation was observed to be deposited mostly in the vicinity of grain boundaries and at the grain interior. The fine precipitates of the microalloying element copper were observed in the range of size in nanometers. However, the densities of these precipitates were limited and most of these precipitates were deposited at the grain interior. The microhardness of 210.8 Hv and mean subgrain size of 1.61 µ were observed the enhanced microhardness was due to the limited recrystallized grains and accumulation of dislocations/subgrain/substructures. [ABSTRACT FROM AUTHOR]

This paper reports the results of an investigation into the influence of precipitation and air temperature on the efficiency of pollutant removal processes and effluent pollutant concentrations in a one-stage constructed wetland with subsurface vertical flow. We studied an on-site constructed wetland system that used Phragmites australis for the treatment of domestic wastewater. The system was located in central Europe, in the south-east of Poland, in a temperate climate zone with transitional features. Physico-chemical analyses of influent and effluent wastewater, as well as measurements of precipitation and air temperature were carried out in the years 2001–2010. It was shown that the pollutant removal efficiency of the treatment plant was significantly higher in the growing season than outside the growing season (the mean efficiency is usually a few percent higher but generally this parameter is highly varied). This indicated that temperature determined the efficiency of the wastewater treatment. We found that the amount of precipitation affected the concentration of pollutants in the effluent. The more rainfall there was, the lower the content of pollutants in the effluent from the treatment plant, which demonstrated that rainwater diluted the concentrations of pollutants in the treated wastewater—thus improving the efficiency of the wastewater treatment plant. [ABSTRACT FROM AUTHOR]

The morphologies and sizes of TiN inclusions in gear steel 20CrMnTi have a significant impact on its service performance. This paper selects rare earth Ce to modify TiN inclusions in 20CrMnTi. The inclusions are analyzed by SEM (scanning electron microscope), EBSD (electron back-scattered diffraction), EDS (energy disperse spectroscopy), and OTS statistical software, and Thermo-Calc software is used to calculate the inclusion formations. The inclusions of MgAlO4-Ce and CeAlO3 can be formed when rare earth Ce is added into 20CrMnTi, which becomes TiN nucleation core after precipitation. Without the addition of rare earth Ce, square TiN inclusions ranging from 2 to 5 μm account for 60% of the total inclusions in 20CrMnTi. After adding rare earth Ce, the TiN inclusions in 20CrMnTiCe account for 36.7% of the total inclusions. Due to the new phase formations of MgAlO4-TiN and CeAlO3-TiN with sizes less than 2 μm, the titanium-containing inclusions are refined. Fatigue tests are conducted on the steels before and after the addition of Ce. The average fatigue lives of 20CrMnTi do not reach 107 times, and the deviations between the maximum and minimum fatigue lives are great. Large-sized TiN are the main inclusions that affect the fatigue performance of 20CrMnTi. The average fatigue lives of 20CrMnTiCe exceed 107 times, and the deviations of the fatigue lives are smaller than those of 20CrMnTi. [ABSTRACT FROM AUTHOR]

In the context of anomalous global climate change and the frequent occurrence of droughts and floods, studying trends in the conversion rate between precipitable water vapor (PWV) and actual precipitation in a certain region can help in analyzing the causes of these natural disasters. This paper examines the variation trend in the conversion rate between PWV and actual precipitation on a monthly scale in Hubei from 1960 to 2020. To estimate historical PWV data, we propose a new method for estimating PWV using water vapor pressure based on the RF algorithm. The new method was evaluated by radiosonde data and improved the accuracy by 1 mm over the traditional method in Hubei. Based on this method, we extrapolate the monthly average PWV in Hubei from 1960 to 2020 and analyze the conversion rate between PWV and precipitation during this period. Our results showed that there was no obvious cyclical pattern in the conversion rate in either the longitude or latitude directions. In Hubei, where the topography varies significantly in the longitude direction, the conversion rate is influenced by topography, with the smallest conversion rate being in the transition zone between the mountainous region of western Hubei and the Jianghan Plain. In the latitudinal direction, the conversion rate decreases with increasing latitude. [ABSTRACT FROM AUTHOR]

The consistency of hydrological process modeling depends on reliable parameters and available long-term gauge data, which are frequently restricted within the Dead Sea/Jordan regions. This paper proposes a novel method of utilizing six satellite-based and reanalysis precipitation datasets, which are assessed, evaluated, and corrected, particularly for the cases of ungauged basins and poorly monitored regions, for the first time. Due to natural processes, catchments fluctuate dramatically annually and seasonally, making this a challenge. This variability, which is significantly impacted by topo-geomorphological and climatic variables within the basins themselves, leads to increased uncertainty in models and significant restrictions in terms of runoff forecasting. However, quality evaluations and bias corrections should be conducted before the application of satellite data. Moreover, the hydrological HEC-HMS model was utilized to predict the runoff under different loss methods. Furthermore, this loss method was used with an integrated model that might be efficiently employed when designing hydraulic structures requiring high reliability in predicting peak flows. The models' performance was evaluated using R-squared (R2), the root mean square error (RMSE), the mean absolute error (MAE), and Nash–Sutcliffe efficiency (NSE). In addition, these statistical metrics were implemented to quantitatively evaluate the data quality based on the observed data collected between 2015 and 2020. The results show that AgERA5 exhibited better agreement with the gauge precipitation data than other reanalysis precipitation and satellite-based datasets. The results demonstrate that the data quality of these products could be affected by observational bias, the spatial scale, and the retrieval method. Moreover, the SC loss method demonstrated satisfactory values for the R2, RMSE, NSE, and bias compared to the IC and GA loss, indicating its effectiveness in predicting peak flows and designing hydraulic structures that require high reliability. Overall, the study suggests that AgERA5 can provide better precipitation estimates for hydrological modeling in the Dead Sea region in Jordan. Moreover, integrating the SC, IC, and GA loss methods in hydraulic structure design can enhance prediction accuracy and reliability. [ABSTRACT FROM AUTHOR]

In the present study, the damage mechanisms that cause premature failure of sapphire water jet orifices were analyzed using a combined experimental and finite element modeling (FEM) approach. Depending on the operating behavior and local conditions, the service life of orifices for high-pressure water jet cutting often deviates considerably from the manufacturer's specifications. Literature states a typical service life of 50 to 100 h, while in some cases, premature failure after a few hours or even minutes of operation can be observed. The focus of this paper is on the interaction of particles that impact the orifice surface but also the effect of faulty orifice assembly is taken into account. To estimate the risk of failure, the stress distribution in critical parts of the orifice were calculated via FEM, which is fed with experimental data. The modified Mohr failure criterion was then used to evaluate the stress distributions with respect to the possible failure of the orifice jewel. The results revealed that the risk of damage caused by excessive assembly preload forces is marginal. The stress caused by the impact of particles of different sizes is up to four orders of magnitude higher than the stress caused by assembly forces and is therefore identified as the main risk for orifices to fail prematurely. Experimental data shows mainly particles of calcium carbonate and iron–aluminum silicates, which are compounds that originate from the process water itself. It is demonstrated that particles are more critical than formerly assumed in the literature. This paper identifies particles with a diameter of more than 10 µm as critical when there are no other loads present. In operation, even particles as small as 2 µm in diameter can cause damage to the orifice jewel. To prevent premature orifice failure due to foreign particles, water filtration with a 2 µm mesh is recommended, while future research needs to focus on the interior cutting head design to prevent precipitation from the process water. [ABSTRACT FROM AUTHOR]

The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble means typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security. [ABSTRACT FROM AUTHOR]

This paper aims to study the path oscillations of single, spherical water droplets levitated in a wind tunnel to better comprehend the mechanical motion of small raindrops. The observations were carried out in the Mainz vertical wind tunnel. The discrete, fast Fourier transform was used to determine the oscillatory frequencies of the droplet paths, and the Hilbert transform was applied to analyze their instantaneous frequency stability. Both transversal and streamwise components of the path oscillations are described with typical frequencies of several tens of Hertz. The studied oscillations elongate the paths, reduce the terminal velocity of the smallest droplets, and make the rain droplet fall in a non-uniform motion even after reaching terminal velocity. The terminal velocity can be considered as physically having been reached if our proposed practical criterion is satisfied. From a fluid mechanics perspective, the paper fills an experimental gap in the studies of the paths oscillations of single, liquid spheres of microscopic sizes at low Bond numbers <1 and relatively low Reynolds numbers ~102. [ABSTRACT FROM AUTHOR]

Knowledge of how the isotopic composition (i.e., δ2H, δ18O and 3H) of precipitation changes within an individual catchment allows the origins of surface and groundwater to be differentiated and the dynamic characteristics of water within individual water bodies to be traced. This paper presents the Slovenian Network of Isotopes in Precipitation (SLONIP), a research platform that has been operating since April 2020. The SLONIP platform currently contains 2572 isotope data points of monthly composite precipitation from eight locations obtained from various investigations performed since 1981. It also provides information about a sample's location, analysis, and links to the relevant scientific papers. It also presents the data in numerical and graphical form, including monthly, seasonal, and annual means and local meteoric water lines, all calculated using a Python code made freely available on GitHub. The platform provides essential information for geographically, climatologically, and geologically diverse regions like Slovenia and can help improve our understanding of the water cycle on a local and regional scale. [ABSTRACT FROM AUTHOR]

Although heat-treatable Al-Zn-Mg-Cu alloys are widely used in aerospace industries, distortion and cracks exist due to the residual stress during quenching. Understanding the flow stress behavior and numerically modeling the process is the key to predicting the residual stress. This paper investigated the flow stress behavior of the as-quenched 7050 alloy at strain rates from 0.1 s−1 to 1 s−1, temperatures between 423 K and 723 K, and cooling rates from 0.1 K/s to 10 K/s. The experimental results showed that the strain rate, cooling rate, and temperature have effects on the flow stress value, except for the cooling rates at a temperature of 423 K or 723 K. The kinetics model was used to obtain the precipitate features, i.e., precipitate size and volume fraction. Then, a physical constitutive model based on the evolution of immobile dislocation, solutes, and precipitates was developed. The predicted flow stresses showed good agreement with the experimental data. The findings of this work expand the knowledge on the as-quenched flow behavior of Al-Zn-Mg-Cu alloys, improving the prediction accuracy of residual stress by FEM. [ABSTRACT FROM AUTHOR]

In this paper, the high strength and lightweight Al–Cu–Li alloy (AA2099) is considered in as-built and preheated conditions (440 °C, 460 °C, 480 °C, 500 °C, and 520 °C). The purpose of this study is to investigate the influence of laser powder bed fusion (LPBF) in situ preheating on precipitation microstructure, mechanical and corrosive properties of LPBF-printed AA2099 alloy compared to the conventionally processed and heat-treated (T83) alloy. It is shown that precipitations evolve with increasing preheating temperatures from predominantly globular Cu-rich phases at lower temperatures (as-built, 440 °C) to more plate and rod-like precipitates (460 °C, 480 °C, 500 °C and 520 °C). Attendant increase with increasing preheating temperatures are the amount of low melting Cu-rich phases and precipitation-free zones (PFZ). Hardness of preheated LPBF samples peaks at 480 °C (93.6 HV0.1), and declines afterwards, although inferior to the T83 alloy (168.6 HV0.1). Preheated sample (500 °C) shows superior elongation (14.1%) compared to the T83 (11.3%) but falls short in tensile and yield strength properties. Potentiodynamic polarization results also show that increasing preheating temperature increases the corrosion current density (Icorr) and corrosion rate. Indicated by the lower oxide resistance (Rox), the Cu-rich phases compromise the integrity of the oxide layer. [ABSTRACT FROM AUTHOR]

In this paper, the creep deformation behavior, microstructure evolution, and damage mechanism of Super304H oxide dispersion strengthened (ODS) steel have been systematically investigated at 650 °C. The creep behavior of the ODS steel could be understood by virtue of a dislocation creep deformation mechanism. Interrupted creep experiments under 100 MPa were conducted to further study the microstructure evolution during long-term creep deformation. The grains began to refine at the initial stage, and some M23C6 phases were observed at grain boundaries, which enhanced the microhardness during the first creep stage. Along with creep, both Y2O3 and Cu-rich precipitates exhibited good coherence with the matrix. The Y2O3 precipitates showed better thermal stability than the Cu-rich phase. During the second creep stage, some cavities emerged around the M23C6 phase and at grain boundaries. The cavities gradually developed into significant cracks, causing the steel to fracture. The creep damage due to cavity growth could be determined according to the creep damage tolerance factor value. [ABSTRACT FROM AUTHOR]

The paper compares precipitation measurements from the Stratus manual rain gauge from the CoCoRaHS network and two Davis Vantage Vue and Davis Vantage Pro 2A rain gauges with the Hellmann rain gauge. Comparative measurements were made on a specially prepared experimental plot. The statistical calculations took into account 15 full months in the period from 1 October 2019, to 31 December 2020. In order to estimate the differences in measurements between amateur rain gauges and the Hellmann rain gauge, two statistics were calculated: the mean square error (MSE) and the mean absolute error (MAE). In order to present formal and more detailed differences in measurements between amateur rain gauges and the Hellmann rain gauge, analyses were performed using a linear regression model. The general form of the tested models was presented. The procedure for estimating the parameters of the models and the method of comparing the fit of the models to the data were described, and the rain gauge whose measurements were most closely related to the measurements of the Hellmann rain gauge was indicated. The study showed that the higher price of amateur rain gauges does not mean higher quality. The study showed that the Stratus rain gauge was the best at recording daily precipitation totals. The Davis Vantage Pro 2A rain gauge recorded daily precipitation sums with less accuracy. The Davis Vantage Vue rain gauge, despite being located on the roof, recorded similar rainfall totals as the Hellmann rain gauge. It was found that, despite the different construction and measurement methods, the precipitation measurement data from the Stratus rain gauge and the Davis Vantage Vue rain gauge are suitable both for climate monitoring and for use, after applying quality control, in NMHS networks. [ABSTRACT FROM AUTHOR]

Especially in recent years, the study of landslide phenomena is considered as very important because of the effects of climate change. The aim of this paper is to examine the stability of the slope located in Miacher Nagar village along the Hunza River (HR), using the Limit Equilibrium Method (LEM). The Miacher slope rises to a height of 900 m from the foot of the Hunza River and has a base angle of 50 degrees. Meta-sediments and quaternary recent glaciated deposits make up the majority of the slope's composition. The slope movement of Miacher was first triggered in 1995, and was further triggered in 2010 and 2013. The slope was geologically, geomorphologically, geotechnically and geochemically investigated as well as modeled by Slope/w to determine the safety factor. Soil samples were analyzed for their geotechnical, geological and geomorphological properties. The Limit Equilibrium Method (LEM) was employed in this study to analyze the Factor of Safety (FOS) of the slope, based on assumptions of the Morgenstern and Price, Ordinary, Janbu and Bishop Methods, using the Slope/w software. Various factors, including pore water pressure, unit weight, cohesion, angle of internal friction and overburden, were examined by analyzing different scenarios. The findings showed that an increase in cohesion and angle of internal friction resulted in an increase in FOS, whereas an increase in unit weight and overburden caused a decrease in FOS. The influence of pore water pressure was positive to a certain extent, but a further increase led to a significant reduction in FOS. The results showed that the Miacher slope is currently stable, as all FOS values were greater than one, based on the existing strength parameters and simulated results obtained using Slope/w. [ABSTRACT FROM AUTHOR]

Fe-Mn-Si-based shape memory alloys (SMAs) have been extensively investigated since 1982 for various useful properties that enhance the development of different applications such as anti-seismic dampers for very tall buildings, pipe joints, or rail fasteners. In particular, the Fe-28Mn-6Si-5Cr (mass. %) alloy has been mainly used in vibration mitigation or self-adjustable axial displacement applications. Dynamic mechanical analysis (DMA), performed by strain sweeps (SS), enables the monitoring of the evolution of storage modulus and internal friction variations with increasing strain amplitudes at different constant frequencies and temperatures. Thus, applying dynamic bending with various frequencies and amplitudes that actually represents an isothermal mechanical treatment. In the present paper, an Fe-28Mn-6 Si-5Cr (mass. %) SMA was cast by ingot metallurgy, hot-rolled, and water quenched in order to obtain thermally induced martensite and avoid the occurrence of cooling cracks. The influence of the holding time, between 2 and 10 h, at 1050 °C and the effects of DMA-SS performed at three different frequencies were analyzed by a differential scanning calorimetry, an X-ray diffraction, and a scanning electron and atomic force microscopy. The effects of the holding time and mechanical treatment on the structure and morphology of martensite plates were corroborated with the results of the thermal analysis. [ABSTRACT FROM AUTHOR]

This research is devoted to the determination of hidden dependencies between the flow of particles that come from the Sun and precipitation-induced floods in the United Kingdom (UK). The analysis covers 20 flood events during the period from October 2001 to December 2019. The parameters of solar activity were used as model input data, while precipitations data in the period 10 days before and during each flood event were used as model output. The time lag of 0–9 days was taken into account in the research. Correlation analysis was conducted to determine the degree of randomness for the time series of input and output parameters. For establishing a potential causative link, machine learning classification predictive modeling was applied. Two approaches, the decision tree, and the random forest were used. We analyzed the accuracy of classification models forecast from 0 to 9 days in advance. It was found that the most important factors for flood forecasting are proton density with a time lag of 9, differential proton flux in the range of 310–580 keV, and ion temperature. Research in this paper has shown that the decision tree model is more accurate and adequate in predicting the appearance of precipitation-induced floods up to 9 days ahead with an accuracy of 91%. The results of this study confirmed that by increasing technical capabilities, using improved machine learning techniques and large data sets, it is possible to improve the understanding of the physical link between the solar wind and tropospheric weather and help improve severe weather forecasting. [ABSTRACT FROM AUTHOR]

Quantitative precipitation estimation (QPE) plays an important role in meteorology and hydrology. Currently, multichannel Doppler radar image is used for QPE based on some traditional methods like the Z − R relationship, which struggles to capture the complicated non-linear spatial relationship. Encouraged by the great success of using Deep Learning (DL) segmentation networks in medical science and remoting sensing, a UNet-based network named Reweighted Regression Encoder–Decoder Net (RRED-Net) is proposed for QPE in this paper, which can learn more complex non-linear information from the training data. Firstly, wavelet transform (WT) is introduced to alleviate the noise in radar images. Secondly, a wider receptive field is obtained by taking advantage of attention mechanisms. Moreover, a new Regression Focal Loss is proposed to handle the imbalance problem caused by the extreme long-tailed distribution in precipitation. Finally, an efficient feature selection strategy is designed to avoid exhaustion experiments. Extensive experiments on 465 real processes data demonstrate that the superiority of our proposed RRED-Net not only in the threat score (TS) in the severe precipitation (from 17.6% to 39.6%, ≥20 mm/h) but also the root mean square error (RMSE) comparing to the traditional Z-R relationship-based method (from 2.93 mm/h to 2.58 mm/h, ≥20 mm/h), baseline models and other DL segmentation models. [ABSTRACT FROM AUTHOR]

Hydropower plays an essential role in Europe's energy transition and can serve as an important factor in the stability of the electricity system. This is even more crucial in areas that rely strongly on renewable energy production, for instance, solar and wind power, as for example the Peloponnese and the Ionian islands in Greece. To safeguard hydropower's contribution to total energy production, an accurate prediction of the annual precipitation is required. Valuable tools to obtain accurate predictions of future observations are firstly a series of sophisticated data preprocessing techniques and secondly the use of advanced machine learning algorithms. In the present paper, a complete procedure is proposed to obtain accurate predictions of meteorological data, such as precipitation. This procedure is applied to the Greek automated weather stations network, operated by the National Observatory of Athens, in the Peloponnese and the Ionian islands in Greece. The proposed prediction algorithm successfully identified the climatic zones based on their different geographic and climatic characteristics for most meteorological stations, resulting in realistic precipitation predictions. For some stations, the algorithm underestimated the annual total precipitation, a weakness also reported by other research works. [ABSTRACT FROM AUTHOR]

The cyclic stability of superelasticity in compression in [001]B2-oriented Ti49.3Ni50.7 single crystals is considered in this paper. The crystals were aged at 823 K for 1.0 h in air and helium. It has been experimentally shown that a two-layered surface thin film, consisting of a Ni-free oxide layer and a Ni-rich sublayer, appears after the oxidation at 823 K in air. The surface layers have a weak effect on the forward B2-R-B19' martensitic transformation temperatures: TR temperature increases by 4 K; Ms and Mf temperatures decrease by 6 K. The oxide layer does not affect either the superelasticity response during fatigue tests or the temperatures of reverse B19'-B2 martensitic transformation. The cracking of the surface oxide layer during fatigue tests was not found in [001]B2-oriented single crystals aged in air. This is contributed by the relaxation of internal stresses. Such internal stresses are caused by both the formation of an oxide layer during aging and the matrix deformation at the stress-induced martensitic transformation. The main relaxation mechanisms of the internal stresses are the oriented growth of Ti3Ni4 precipitation near a thin surface film at aging in air, the formation of dislocations near the precipitation-matrix interface and a fine twinned B19'-martensite at fatigue tests. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the annual precipitation observed by a network of 30 rain gauges in Iraq over a 65-year period (1941–2005). The simulated precipitation from 18 climate models in the CMIP5 project is investigated over the same area and time window. The Mann–Kendall test is used to assess the strength and the significance of the trends (if any) in both the simulations and the observations. Several exploratory techniques are used to identify the similarity (or disagreement) in the probability distributions that are fitted to both datasets. While the results show that large biases exist in the projected rainfall data compared with the observation, a clear agreement is also observed between the observed and modelled annual precipitation time series with respect to the direction of the trends of annual precipitation over the period. [ABSTRACT FROM AUTHOR]

Climate change is one of the most pressing issues of our time. Rising temperatures, changing precipitation and more weather extremes pose risks to local societies worldwide. Yet, climate change is most often presented and reported on a global or national scale. This paper aims to analyze the key aspects of climate change on the local scale by assessing temporal and spatial changes in temperature and precipitation in the Westfjords in north-western Iceland and evaluate their impacts on the region's livability. Existing temperature and precipitation data were used to model trends in climate change at an unprecedented resolution. The results show that the period of 2001–2020 was warmer than the 1961–1990 reference period in almost every month of every year, and that warming was more pronounced in the winter months. Furthermore, precipitation increased during 1991–2020 period compared to 1961–1990. These detected local patterns confirm some of the major predictions about climate change on the global scale. Considering the impact of climate change at the local level is critical, as it allows the community to envisage their future and provides better possibilities to mitigate, prepare for or adapt to the predicted changes. [ABSTRACT FROM AUTHOR]

While scientists generally generate new projections with the newest models, the paper suggested the use of past projections as a different approach which could be explored and then complement classical approaches. With the idea that today is yesterday's future, a set of past Intergovernmental Panel on Climate Change (IPCC) climate projections (first-AR1, second-AR2 and third-AR3 assessment reports) were compared to gauge-based observations of the last three decades (1990–2016). Why would someone need to check previous models and scenarios when the new ones are currently available? Some in-depth discussion points were raised to answer that question. Monthly and annual precipitation and temperatures were analyzed over West Africa, divided into 3 climatic sub-regions. The results revealed that observed differences are greater at higher latitudes and are strongly scenario dependent. The Business-as-Usual scenario (few or no steps are taken to limit greenhouse gas emissions) appeared to be closest to the observations. The AR1 projections were shown to be disconnected from the observations. AR2 exhibited the best performance, and AR3 presented higher uncertainties in the northern areas. The relative importance and potential implications of the differences between projections and observations on society were appreciated with regard to certain climate and weather-related factors that could greatly influence sustainable development in the region, such as water resources management, agriculture practices and yields, health conditions, and fishery management. Finally, some recommendations to policy and decision makers were given as well as further research topics for the scientific community. [ABSTRACT FROM AUTHOR]

The effect of deep cryogenic treatment (DCT) on the artificial ageing kinetics of a SiC particles reinforced aluminum alloy composite (SiCp-Al) is experimentally studied in this paper. The evolutions of both macro-properties (i.e., yield strength and ultimate tensile strength) and microstructures (precipitates) have been investigated by a set of hardness tests, tensile tests, and microstructural observations (scanning electron microscope, SEM and transmission electron microscope, TEM) for a SiCp-Al composite material with conventional heat treatment (solution heat treatment + quenching + artificial ageing, CHT) or DCT (solution heat treatment + quenching + deep cryogenic + artificial ageing). The results show that SiCp could significantly accelerate the ageing kinetics of the composites. Meanwhile, compared with CHT conditions, DCT can further improve the yield strength (YS) and ultimate tensile strength (UTS) of the composite materials after artificial ageing. The microstructures show that DCT induces the generation of more thinner θ ′ precipitates homogeneously distributed in the grains during artificial ageing compared with corresponding CHT conditions. A quantified analysis has been performed based on the microstructural data, and the calculated results further support the indication that the strengthening effect in DCT compared with CHT is mainly contributed by corresponding precipitation behavior. [ABSTRACT FROM AUTHOR]

This paper presents Cr(III) removal from nickel sulfate waste solutions as a pretreatment step for the modification of hydrogen storage alloys. Adsorption with two cation exchange resins, Dowex G26 (strongly acidic) and MAC-3 (weakly acidic), and precipitation with various solutions were chosen as simple operations for Cr(III) removal from waste solutions. The adsorption of Cr(III) was investigated for both model and real waste nickel solutions. Dowex G26 appeared to be more efficient in Cr(III) removal (RCr(III) from 43 to 80%) than MAC-3 (RCr(III) from 40 to 53%). However, the adsorption from multi-component solutions (presence of Co(II), Ni(II) and Cr(III)) showed no selectivity in Cr(III) adsorption in comparison to those of Co(II) and Ni(II). Cr(III), Ni(II) and Co(II) were removed at a comparable level (30–36%) from a three-component solution of 10 g/dm3 of each metal ion, and a 56–72% removal of these ions was achieved from the real solution. Therefore, the precipitation of Cr(III) was carried out from a real waste nickel solution to compare its performance with adsorption. The best precipitation solution appeared to be 3 and 30% NaOH due to the quantitative precipitation of Cr(OH)3 at pH 5 and relatively small co-precipitation of Ni(II) and Co(II) hydroxides (PCo(II) = 20–52%, PNi(II) = 0–54%). Based on the results of the research, it can be concluded that precipitation with a NaOH solution is an efficient pretreatment operation of an electrolyte for further steps of the hydrometallurgical process of nickel electrodeposition and appears to be more selective in the elimination of Cr(III) than adsorption with Dowex G26 resin. [ABSTRACT FROM AUTHOR]

The Grain for Green Project (GGP) has considerably improved the vegetation cover of the Loess Plateau, as well as changed the carbon and water coupling process of local vegetation to a certain extent. Water use efficiency (WUE) is a crucial measure for evaluating ecosystem responses to global climate change and is a key indicator of the carbon–water coupling between terrestrial ecosystems and the environment. A comprehensive understanding of the impact of vegetation reconstruction on WUE on the Loess Plateau is of great significance to the vegetation growth and contribution to sustainable of the Loess Plateau. In recent years, scholars have gained a more comprehensive understanding of the distribution and drivers of WUE on the Loess Plateau. However, through the study of carbon and water coupling in the Loess Plateau, it is found that the effects of different vegetation restoration levels on WUE are still to be studied in depth in terms of spatial and temporal heterogeneity and long timeseries. In this paper, we analyzed the trends of Normalized Difference vegetation cover (NDVI) and WUE from 2001 to 2010 and 2011 to 2020, respectively, to research at the WUE of the vegetation in this area in relation to vegetation restoration. It was found that the Loess Plateau's vegetation WUE rose from 2001 to 2020 at a rate of 0.023 g C kg−1 H2O per year, and that the increase from 2011 to 2020 was more significant than the growth from 2000 to 2010. The Loess Plateau's area with a growing trend in vegetation water use rate increased from 77.12% in 2001–2010 to 88.63% in 2011–2020, with the majority of the increased area occurring in the northeastern Inner Mongolia region. After 20 years of the reforestation project, the area where NDVI and WUE increased simultaneously accounted for 71.54% of the Loess Plateau, the area where NDVI increased but WUE decreased accounted for 10.95% of the Loess Plateau, and the area where NDVI increased but WUE decreased accounted for 7.15% of the Loess Plateau. The correlation between temperature precipitation and WUE was not significant for the whole Loess Plateau, further indicating that the increase in vegetation cover was the main reason for the increase in vegetation water efficiency. Therefore, the effect of vegetation cover on WUE should be fully considered when vegetation restoration is carried out on the Loess Plateau. [ABSTRACT FROM AUTHOR]

This paper introduces the Method of Microwave Rainfall Normalization (MMN) for the Global Satellite Mapping of Precipitation (GSMaP) algorithm in its latest version (V05, algorithm version 8), released in December 2021. The method aims to mitigate the discrepancy of GSMaP rainfall estimates among passive microwave (PMW) imagers/sounders (MWIs/MWSs) due to differences in sensor specifications and retrieval algorithms. The basic idea of the MMN module is to calibrate target PMW sensors with reference sensors (the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI)) using the cumulative distribution function (CDF) of the rain rate. Differences between the CDF and normalization table for MWSs are greater than MWIs due to different rain retrieval algorithms. More (less) MWS rainfall is detected over the ocean (land) than GMI rainfall. Matchup rainfall data between GMI and a target PMW sensor are compared to evaluate MMN performance. The monthly mean rainfall and mean bias error were improved for almost all PMW sensors. This study leaves open the possibility for further inter-calibration and improvement of rain detection and heavy rainfall retrievals. [ABSTRACT FROM AUTHOR]

Water pollution is a severe health concern. Several studies have recently demonstrated the efficacy of various approaches for treating wastewater from anthropogenic activities. Wastewater treatment is an artificial procedure that removes contaminants and impurities from wastewater or sewage before discharging the effluent back into the environment. It can also be recycled by being further treated or polished to provide safe quality water for use, such as potable water. Municipal and industrial wastewater treatment systems are designed to create effluent discharged to the surrounding environments and must comply with various authorities' environmental discharge quality rules. An effective, low-cost, environmentally friendly, and long-term wastewater treatment system is critical to protecting our unique and finite water supplies. Moreover, this paper discusses water pollution classification and the three traditional treatment methods of precipitation/encapsulation, adsorption, and membrane technologies, such as electrodialysis, nanofiltration, reverse osmosis, and other artificial intelligence technology. The treatment performances in terms of application and variables have been fully addressed. The ultimate purpose of wastewater treatment is to protect the environment that is compatible with public health and socioeconomic considerations. Realization of the nature of wastewater is the guiding concept for designing a practical and advanced treatment technology to assure the treated wastewater's productivity, safety, and quality. [ABSTRACT FROM AUTHOR]

Precipitation is among the most important meteorological variables for, e.g., meteorological, hydrological, water management and climate studies. In recent years, non-catching precipitation gauges are increasingly adopted in meteorological networks. Despite such growing diffusion, calibration procedures and associated uncertainty budget are not yet standardized or prescribed in best practice documents and standards. This paper reports a metrological study aimed at proposing calibration procedures and completing the uncertainty budgets, to make non-catching precipitation gauge measurements traceable to primary standards. The study is based on the preliminary characterization of different rain drop generators, specifically developed for the investigation. Characterization of different models of non-catching rain gauges is also included. [ABSTRACT FROM AUTHOR]

Southwest Asia has different climate types including arid, semiarid, Mediterranean, and temperate regions. Due to the complex interactions among components of the Earth system, forecasting precipitation is a difficult task in such large regions. The aim of this paper is to propose a learning approach, based on artificial neural network (ANN) and random forest (RF) algorithms for post-processing the output of forecasting models, in order to provide a multi-model ensemble forecasting of monthly precipitation in southwest Asia. For this purpose, four forecasting models, including GEM-NEMO, NASA-GEOSS2S, CanCM4i, and COLA-RSMAS-CCSM4, included in the North American multi-model ensemble (NMME) project, are considered for the ensemble algorithms. Since each model has nine different lead times, a total of 108 different ANN and RF models are trained for each month of the year. To train the proposed ANN an RF models, the ERA5 reanalysis dataset is employed. To compare the performance of the proposed algorithms, four performance evaluation criteria are calculated for each model. The results indicate that the performance of the ANN and RF post-processing is better than that of the individual NMME models. Moreover, RF outperformed ANN for all lead times and months of the year. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

Multi-stage heat treatment is an important method to improve the mechanical properties of Al-Si-Cu-Mg aluminum alloys. In this paper, the multi-stage heat treatment was carried out for the Cd-free and Cd-containing alloys. The experimental results show that the addition of Cd promoted the precipitation of Q″ and θ″, which led to the formation of a large number of fine, dispersed precipitates and a higher yield strength (YS) and ultimate tensile strength (UTS) for the Cd-containing alloys. The addition of Cd also altered the optimal heat treatment parameters. For the Cd-free alloys, the Cu-rich phase fully dissolved after three-stage heat treatment, and the YS and UTS of the three-stage heat-treated alloys were higher than their two-stage heat-treated counterparts. For the Cd-containing alloys, the three-stage heat treatment led to the precipitation of Cd-rich low melting point phases, caused defects, and reduced the mechanical properties of the alloy. The size and volume fractions of the precipitates were significantly less than those of the alloys after two-stage heat treatment and the strength of the alloys decreased. Therefore, the solution time should be strictly controlled for Cd-containing Al-Si-Cu-Mg alloys. [ABSTRACT FROM AUTHOR]

In August-September 2021, the western Pacific subtropical high (WPSH) showed significant anomalies, with some areas between the Yangtze and Yellow River basins in China suffering from heavy rainfall and flooding, while extreme heat occurred in Southern China. Using the 6 h reanalysis data of NCEP/NCAR and the daily precipitation observation data, this paper studied the abnormal characteristics and the thermal mechanism of the three-dimensional ridge of the WPSH during the seasonal transition from late summer to early autumn in August-September 2021, and explored its connection with the precipitation in the areas between the Yangtze and Yellow River basins in China during the same period. The results showed that, in August-September 2021, the three-dimensional ridge of the WPSH appeared to be southward at the lower troposphere and tilted northward with height. According to the diagnosis of the atmospheric heat source, it was found that the center of atmospheric cold source in the low latitudes at 850 hPa enhanced the surface high pressure, corresponding to the WPSH ridge shifting southward at the lower troposphere, which led to more water vapor convergence and more precipitation between the Yangtze and Yellow River basins. The latent heat of condensation released by the increased precipitation between the Yangtze and Yellow River basins in China heated the middle and upper troposphere, increasing the intensity of the high pressure in the upper troposphere, corresponding to the WPSH ridge northward at the upper troposphere. This anomalous tilt of the WPSH ridge in August-September 2021 and the intense precipitation processes between the Yangtze and Yellow River basins in China during the same period established a reciprocal feedback mechanism through diabatic heating. Further studies also showed that the anomalous tilt of the WPSH ridge is one of the important modes of its three-dimensional structural anomalies, and that, in years when the ridge tilts from south to north with height anomalously in August-September, the areas between the Yangtze and Yellow River basins are characterized by high precipitation. [ABSTRACT FROM AUTHOR]

A Cu-Ni-Si alloy containing (Ni + Si) ≥ 5 wt.%, with the addition of Cr, is fabricated by HCCM continuous casting and two steps of aging treatment. The evolution of the microstructures and precipitations, as well as the effect of Cr atoms, is studied in this paper. An excellent combination of mechanical property (hardness HV 250–270) and electrical conductivity (46–47 %IACS) is obtained by the first step aging at 500 °C for 0.25 h and the second step aging at 450 °C for 1 h. The cold rolling and aging process are directly conducted on the solution treated specimens fabricated by HCCM continuous casting process without hot deformation, since the excellent homogeneity of matrix is obtained by solution treatment with δ-Ni2Si precipitates dissolved. It is found that the formation of discontinuous precipitation is suppressed by the formation of Cr3Si cores of 5–10 nm before the formation δ-Ni2Si. Then, the nucleation and growth of δ-Ni2Si precipitates occurs around the boundaries of these Cr3Si cores, leading to an enhanced nucleation rate. This study provides a promising direction for the design and optimization of Cu-Ni-Si alloys based on the further understanding of the effect of the addition of Cr. [ABSTRACT FROM AUTHOR]

This paper describes the initial results of precipitation estimates from the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter-wave Sounder (TMS) using the Precipitation Retrieval and Profiling Scheme (PRPS). The TROPICS mission consists of a Pathfinder CubeSat and a constellation of six CubeSats, providing a low-cost solution to the frequent sampling of precipitation systems across the Tropics. The TMS instrument is a 12-channel cross-track scanning radiometer operating at frequencies of 91.655 to 204.8 GHz, providing similar resolutions to current passive microwave sounding instruments. These retrievals showcase the potential of the TMS instrument for precipitation retrievals. The PRPS has been modified for use with the TMS using a database based upon observations from current sounding sensors. The results shown here represent the initial postlaunch version of the retrieval scheme, as analyzed for the Pathfinder CubeSat launched on 30 June 2021. In terms of monthly precipitation estimates, the results fall within the mission specifications and are similar in performance to retrievals from other sounding instruments. At the instantaneous scale, the results are very promising. [ABSTRACT FROM AUTHOR]

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49-76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50-76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784-1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731-1269 mm), while the valley gauge adjustments were 􀀀4% to 1% (􀀀39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites. [ABSTRACT FROM AUTHOR]