Transport Model Simulations Research Articles

Underappreciated roles of soil nitrogen oxide emissions on global acute health burden

The recognized importance of ambient fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) on human health has prompted the world to enact increasingly strict regulations on anthropogenic nitrogen oxides (NOx) emissions. However, the health concerns from soil NOx, potentially driven by fertilizer input but conventionally categorized as natural sources, remain less studied. Here, we emphasize the underappreciated roles of soil NOx emissions on health burden attributable to short-term PM2.5, O3, and NO2 exposure. Globally, we quantify acute health effects using machine-learning-based daily exposure estimates and identify influences of soil NOx emissions based on chemical transport model simulations. We find that 72.3% of the globe is affected by soil NOx emissions, whose contributions to short-term PM2.5, O3, and NO2 pollution lead to 13.9 (95% Confidence Interval [CI]: 9.1-18.8), 26.0 (18.2-34.2), and 13.9 (10.3-17.5) thousand premature mortality, respectively, in 2019. With distinct variations in regions, seasons, and pollutants, soil NOx-originated air pollution poses a global health concern, particularly for developing regions and intensively agricultural areas. In response to the intensive fertilizer use, South Asia, Southern Sub-Saharan Africa, and Central Europe witness the largest soil NOx-related health burden of up to 1.6 (95% CI: 1.1-2.1) mortality per 100k population. The overall health risk peaks in May, with O3 pollution typically dominating the soil NOx-attributable health burden during warm seasons and NO2 or PM2.5 during cold months. Our study highlights the necessity of dynamically adapted agricultural strategies for health-oriented multi-pollutant control, among which the improved use of synthetic fertilizers deserves priority under the ever-changing climate.

Energy dependence of heavy-ion initial condition in isobar collisions

Collisions of isobar nuclei, those with the same mass number but different structure parameters, provide a new way to probe the initial condition of the heavy ion collisions. Using transport model simulation of 96Ru+96Ru and 96Zr+96Zr collisions at two energies sNN=0.2 TeV and 5.02 TeV, where 96Ru and 96Zr nuclei have significantly different deformations and radial profiles, we identify sources of eccentricities contributing independently to the final state harmonic flow vn. The efficacy for flow generation differs among these sources, and explains the modest energy dependence of the isobar ratios of vn. Additionally, a significant component of vn is found to be uncorrelated with the eccentricity, but is instead generated dynamically during system evoluation. Experimental measurement of these ratios at the LHC energy and comparison with RHIC energy can provide insight into the collision-energy dependence of the initial condition.

Optimization of a Groundwater Pollution Monitoring Well Network Using a Backpropagation Neural Network-Based Model

Selecting representative groundwater monitoring wells in polluted areas is crucial to comprehensively assess groundwater pollution, thereby ensuring effective groundwater remediation. However, numerous factors can affect the effectiveness of groundwater monitoring well network optimizations. A local sensitivity analysis method was used in this study to analyze the hydrogeological parameters of a simulation groundwater solute transport model. The results showed a strong effect of longitudinal dispersion and transverse dispersion on the output results of the simulation model, and a good fit between the backpropagation neural network (BPNN)-based alternative model’s results and those obtained using the solute transport simulation model, accurately reflecting the input and output relationship of the simulation model. The optimized groundwater monitoring layout scheme consisted of four groundwater monitoring wells, namely no. 7, no. 16, no. 23, and no. 24. These wells resulted in a groundwater fluoride pollution rate of 98.44%, which was substantially higher than that obtained using the random layout scheme. In addition, statistical analysis of the fluoride groundwater pollution results obtained using the Monte Carlo random simulation highlighted continuous and high groundwater fluoride levels in the second and third pollution sources and their downstream groundwater. Therefore, more attention should be devoted to these sources to ensure the effective remediation of groundwater pollution in the study area.

Simulation-based evaluation of road transportation logistics in a dry port with topographic challenges

The extension of existing container terminals or the creation of new ones introduces new logistical challenges, including topographic issues and increased distances between the quays and storage yards located several kilometers away from the quay (dry port). These challenges are complex to evaluate analytically and directly impact the acceleration, deceleration, and average speed of a truck which in turn affect the productivity and synchronization of the overall terminal logistics. This paper proposes a transportation simulation model that incorporates detailed descriptions of the topographical and geometrical restrictions. Our simulation model evaluates various scenarios for container transportation logistics, including varying road design terminals and truck fleet size to enhance productivity. A case study from a potential container terminal on Canada’s St. Lawrence River is used to demonstrate the simulation model. Several scenarios with different designs are tested and the simulation provides numerical results for supporting decision makers.

Impact of chemical aging on pyrogenic carbon colloid facilitated transport and transformation of Cr (VI) in anoxic environments

Frequent wildfires have accumulated the pyrogenic carbon (PyC) colloids in the environment, where they undergo environmental aging processes. The altered properties of aged PyC colloids may affect their ability to facilitate transformation and transport of contaminants in post-fire environments, posing unknown threats to ecological security. This study investigated the effect of chemical aging on the PyC colloid-facilitated transformation and transport of chromium (Cr) using batch experiments, column experiments, and transport model simulations. Results showed that aged PyC colloids exhibited weaker electron-donating capacity, and the reduction of Cr (VI) to Cr (III) decreased from 37.6 % to 13.5 % with the increasing aging time. Although PyC colloid transport increased with aging time, the PyC colloid-facilitated Cr (III) transport decreased because of the weakened reduction of Cr (VI). The transport of PyC colloid-facilitated Cr (III) was weaker at low pH. The reactive solute transport model well simulated the aged PyC colloid-facilitated transformation and transport of Cr (VI). Our findings highlight the significance of aging processes and environmentally relevant conditions in influencing the PyC colloid-facilitated transformation and transport of Cr, which is crucial for assessing risks of wildfire-driven Cr pollution and the potential of PyC for in-situ pollution control.

Capturing Exposure Disparities with Chemical Transport Models: Evaluating the Suitability of Downscaling Using Land Use Regression.

High resolution exposure surfaces are essential to capture disparities in exposure to traffic-related air pollution in urban areas. In this study, we develop an approach to downscale Chemical Transport Model (CTM) simulations to a hyperlocal level (∼100m) in the Greater Toronto Area (GTA) under three scenarios where emissions from cars, trucks and buses are zeroed out, thus capturing the burden of each transportation mode. This proposed approach statistically fuses CTMs with Land-Use Regression using machine learning techniques. With this proposed downscaling approach, changes in air pollutant concentrations under different scenarios are appropriately captured by downscaling factors that are trained to reflect the spatial distribution of emission reductions. Our validation analysis shows that high-resolution models resulted in better performance than coarse models when compared with observations at reference stations. We used this downscaling approach to assess disparities in exposure to nitrogen dioxide (NO2) for populations composed of renters, low-income households, recent immigrants, and visible minorities. Individuals in all four categories were disproportionately exposed to the burden of cars, trucks, and buses. We conducted this analysis at spatial resolutions of 12, 4, 1 km, and 100 m and observed that disparities were significantly underestimated when using coarse spatial resolutions. This reinforces the need for high-spatial resolution exposure surfaces for environmental justice analyses.

Assimilating Satellite-Derived Snow Cover and Albedo Data to Improve 3-D Weather and Photochemical Models

During wintertime temperature inversion episodes, ozone in the Uinta Basin sometimes exceeds the standard of 70 ppb set by the US Environmental Protection Agency. Since ozone formation depends on sunlight, and less sunlight is available during winter, wintertime ozone can only form if snow cover and albedo are high. Researchers have encountered difficulties replicating high albedo values in 3-D weather and photochemical transport model simulations for winter episodes. In this study, a process to assimilate MODIS satellite data into WRF and CAMx models was developed, streamlined, and tested to demonstrate the impacts of data assimilation on the models’ performance. Improvements to the WRF simulation of surface albedo and snow cover were substantial. However, the impact of MODIS data assimilation on WRF performance for other meteorological quantities was minimal, and it had little impact on ozone concentrations in the CAMx photochemical transport model. The contrast between the data assimilation and reference cases was greater for a period with no new snow since albedo appears to decrease too rapidly in default WRF and CAMx configurations. Overall, the improvement from MODIS data assimilation had an observed enhancement in the spatial distribution and temporal evolution of surface characteristics on meteorological quantities and ozone production.

Toward Low‐Latency Estimation of Atmospheric CO2 Growth Rates Using Satellite Observations: Evaluating Sampling Errors of Satellite and In Situ Observing Approaches

AbstractThe atmospheric CO2 growth rate is a fundamental measure of climate forcing. NOAA's growth rate estimates, derived from in situ observations at the marine boundary layer (MBL), serve as the benchmark in policy and science. However, NOAA's MBL‐based method encounters challenges in accurately estimating the whole‐atmosphere CO2 growth rate at sub‐annual scales. Here we introduce the Growth Rate from Satellite Observations (GRESO) method as a complementary approach to estimate the whole‐atmosphere CO2 growth rate utilizing satellite data. Satellite CO2 observations offer extensive atmospheric coverage that extends the capability of the current NOAA benchmark. We assess the sampling errors of the GRESO and NOAA methods using 10 atmospheric transport model simulations. The simulations generate synthetic OCO‐2 satellite and NOAA MBL data for calculating CO2 growth rates, which are compared against the global sum of carbon fluxes used as model inputs. We find good performance for the NOAA method (R = 0.93, RMSE = 0.12 ppm year−1 or 0.25 PgC year−1). GRESO demonstrates lower sampling errors (R = 1.00; RMSE = 0.04 ppm year−1 or 0.09 PgC year−1). Additionally, GRESO shows better performance at monthly scales than the NOAA method (R = 0.76 vs. 0.47, respectively). Due to CO2's atmospheric longevity, the NOAA method accurately captures growth rates over 5‐year intervals. GRESO's robustness across partial coverage configurations (ocean or land data) shows that satellites can be promising tools for low‐latency CO2 growth rate information, provided the systematic biases are minimized using in situ observations. Along with accurate and calibrated NOAA in situ data, satellite‐derived growth rates can provide information about the global carbon cycle at sub‐annual scales.

Can we reach consensus on the dominant sulfate formation pathway in China's haze?

Atmospheric sulfate aerosols contribute significantly to air pollution and climate change. Sulfate formation mechanisms during winter haze events in northern China have recently received considerable attention, with more than 10 studies published in high-impact journals. However, the conclusions from in-field measurements, laboratory studies, and numerical simulations are inconsistent and even contradictory. Here, we propose a physically based yet simple method to clarify the debate on the dominant sulfate formation pathway. Based on the hazes evolving in the synoptic scale, first, a characteristic sulfate formation rate is derived using the Eulerian mass conservation equation constrained by in situ observations. Then, this characteristic value is treated as a guideline to determine the dominant sulfate formation pathway with a 0D chemical box model. Our observation-derived results establish a linkage between studies from laboratory experiments and chemical transport model simulations. A convergent understanding could therefore be reached on sulfate formation mechanisms in China's wintertime haze. This method is universal and can be applied to various haze conditions and different secondary products.

Activity-based and agent-based transport model of Melbourne: an open multi-modal transport simulation model for Greater Melbourne

Activity- and agent-based models for simulating transport systems have attracted significant attention in recent years. However, building these types of models at a city-wide level and including motorized (i.e. cars and public transport) and non-motorized (i.e. walk and bicycle) modes of transport is a complicated and involved task. This paper presents an open workflow for creating large-scale multi-modal agent-based transport simulation models. The workflow brings together a number of external tools, for example, an activity-based demand generation tool and a road network generation tool, and a set of tools developed for the agent-based model parameter estimation, calibration, and simulation post-processing. We used this workflow to create an activity- and agent-based model for Melbourne and compared the output of the simulation model with observations from the real world in terms of mode share, road volume, travel time, and travel distance. Through these comparisons, we showed that our model is suitable for studying mode choice and road usage behavior of travelers. The calibrated model could be used to test road network change interventions. In addition, a similar workflow can be applied for building simulation models for other cities or could be expanded to include more complicated travel behaviors.

Charge transport dynamics and emission response in quantum-dot light-emitting diodes for next-generation high-speed displays

Inorganic quantum-dot light-emitting diodes (QD-LEDs) have gained significant attention as optoelectronic devices for next-generation display systems due to their superior colour properties. A comprehensive understanding of the charge transport dynamics and transient emission responses of the QD-LED is crucial to achieving high motion picture quality next-generation QD-LED display systems. In this study, we investigated the transient emission response of QD-LED devices through an advanced charge transport simulation model tailored to the quantum-dots (QDs). The dynamic response of the QD-LED devices is evaluated using the time-resolved electroluminescence measurement method for both cadmium-based and cadmium-free red, green, and blue QD-LEDs. The QD-LED devices exhibit notable emission drops during pulse voltage application. The charge transport simulation quantitatively reveals that the on and off switching speeds and the emission drops are intricately influenced by the electron and hole injection balance and a combination of carrier recombination factors within the QD layer. The charge transport simulation also shows that space-charge accumulation, due to the combined effects of charge imbalance and Auger recombination, quantitatively explains a potential device degradation mechanism. Therefore, the QD-specified charge transport model provides a crucial approach in designing and optimizing QD-LED devices for next-generation high-speed QD-LED displays with ultimate colour quality and long lifetimes.

Interpreting Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite observations of the diurnal variation in nitrogen dioxide (NO2) over East Asia

Abstract. Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx, but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO2 reflects a dynamic balance between emission and chemical loss.

Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities.

Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

Method for determining the Schottky injection barrier at the interface of a metal electrode with insulating oil or pressboard

The Schottky injection barrier plays a crucial role in determining the charge movement and migration process, yet its electric field and temperature properties remain unclear. The precise determination of the Schottky injection barrier value is essential for understanding the charge migration dynamics at the interface between the metal electrode and the oil-pressboard insulating medium. This study introduces a computational approach to determine the Schottky injection barrier, derived from classical Schottky emission theory. The methodology employed in this research aligns with previous studies, utilizing the Schottky emission current mechanism to describe steady-state conduction current. Results indicate that the Schottky injection barrier increases with temperature, with a 17.09% rise for oil-electrode and an 8.3% increase for pressboard-electrode in the temperature range of 299 K–353 K. These temperature-dependent variations are attributed to the negative temperature dependence of the Fermi energy levels of the metal electrodes. Furthermore, the impact of electric field strength on the Schottky injection barrier is found to be minimal. By developing a bipolar charge transport simulation model and validating the injection barrier for 0.5 mm oil-immersed pressboard, this study confirms the accuracy of the calculated Schottky injection barrier. The insights provided in this research could aid in simulating charge transport and analyzing charge characteristics in oil-paper/pressboard insulation systems.

Proposal of a Transport Planning Model for the Removal of Quarry Stone Using a Simulation

This article describes a transport planning model which applies a simulation to support decision-making in quarry operations. The analysis of the transport system was used as input for creating the model and the subsequent research. There are five loading points in the quarry from which, according to the plan, the quarry stone is transported to the crusher, where it proceeds for further processing. The required daily capacity of the downstream technological line is 3800 t/day. Based on the analysis, it was found that it was impossible to fulfill this requirement from the two loading points which were the furthest from the unloading point. For this reason, two simulation models of the transport system were created. The first simulation model is a transport system (loading, removal and dumping of quarry stone) from one loading point. Simulation experiments were performed on this model for all loading points. The findings from the analysis confirmed the results of the simulation experiments. Subsequently, a model of the combined quarry stone removal from two loading points was proposed. The model was designed for two variants of dividing the work shift into two work sections. In the model, which had a tabular form, the combinations of loading points and values of the minimum number of unloaded cars for stone removal were suitable to ensure its necessary daily capacity. The last part of this research was expanding the original model with an additional loading point. Several experiments were performed on this model. The aim of these experiments was to verify the combinations of loading points presented in the proposed model and the combinations of unsatisfactory loading points. Based on the research results, the transport planning model and simulation models are suitable additional tools for the decision-making process in removing quarry stone.

Satellite-based analysis of top of atmosphere shortwave radiative forcing trend induced by biomass burning aerosols over South-Eastern Atlantic

This study investigates long-term changes in the shortwave direct aerosol radiative effect (DARE) at the top of the atmosphere (TOA) induced by biomass burning aerosol (BBA) transported from southern Africa to the south-eastern Atlantic (SEA) stratocumulus region during extended fire seasons. The evolution since 2002 of aerosol, cloud properties, and TOA shortwave outgoing radiation from advanced passive satellite sensors are presented, as well as the observational trend in clear-sky DAREclr and the retrieval trend in all-sky DAREall. Supplemented by chemical transport model simulations, we estimate that DAREclr has become more negative (−0.09 ± 0.06 W m−2 yr−1) due to increased aerosol presence in SEA. Meanwhile, DAREall has become more positive ( + 0.04 ± 0.15 W m−2 yr−1) due to aerosols in cloudy sky regions. This study reveals satellite capabilities in capturing complex BBA-cloud-solar radiation interactions for accurate radiative forcing estimates and projections.

Soil and unsaturated zone as a long-term source for pesticide metabolites in groundwater

Pesticide metabolites are frequently detected in groundwater, often exceeding the concentrations of their parent pesticides. Ceasing the application of certain pesticides has often not led to the expected decrease in metabolite concentrations in groundwater, which is potentially caused by residues in soil. Whereas pesticide residues in soils are well-documented, there are only few studies about metabolite residues. We investigated if the soil/unsaturated zone can act as a long-term source for metabolites in groundwater by combining soil analysis, groundwater analysis and numerical modelling. The field study focused on the herbicide chloridazon (CLZ) and its frequently detected metabolites desphenyl-chloridazon (DPC) and methyl-desphenyl-chloridazon (MDPC) while in the model additional pesticides and metabolites were considered. In soil samples from an agricultural area, where the last CLZ application was 5 to 10 years ago, we observed 10 times (DPC: 0.22 – 7.4 µg kg−1) and 6 times (MDPC: 0.12 – 3.1 µg kg−1) higher metabolite concentrations compared to CLZ (< 0.050 – 1.0 µg kg−1). Calculations suggested that the majority of the metabolites (DPC: 63 - 96%, MDPC: 74 – 97%) were sorbed despite their lower sorption tendency. The metabolite retention was in particular related to the organic carbon content. The calculated pore water concentrations were highest in the deepest part of the soil profile (75 – 100 cm) with median concentrations of 3.6 and 1.7 µg L−1 for DPC and MDPC, respectively. The groundwater concentrations of DPC and MDPC were 3 to 3.5 times higher in monitoring wells downgradient from the agricultural zone than upgradient of it. This increase highlights the potential of soil and unsaturated zone as a long-term metabolite source after the application stop of pesticides, consistent with the calculated elevated pore water concentrations. Numerical flow and transport model simulations suggested that this input from soil and unsaturated zone can cause elevated metabolite concentrations (> 0.1 µg L−1) in groundwater over more than one decade. The study highlights that soil and unsaturated zone can act as a long-term source of pesticide metabolites even if they have much higher mobility than the parent compound.

Investigating Zonal Asymmetries in Stratospheric Ozone Trends From Satellite Limb Observations and a Chemical Transport Model

AbstractThis study investigates the origin of a zonal asymmetry in stratospheric ozone trends at northern high latitudes, identified in satellite limb observations over the past two decades. We use a merged data set consisting of ozone profiles retrieved at the University of Bremen from SCIAMACHY and OMPS‐LP measurements to derive ozone trends. We also use TOMCAT chemical transport model (CTM) simulations, forced by ERA5 reanalyses, to investigate the factors that drive the asymmetry observed in the long‐term changes. By studying seasonally and longitudinally resolved observation‐based ozone trends, we find, especially during spring, a well‐pronounced asymmetry at polar latitudes with values up to +6 % per decade over Greenland and −5 % per decade over western Russia. The control CTM simulation agrees well with these observed trends, whereas sensitivity simulations indicate that chemical mechanisms involved in the production and removal of ozone, or their changes, are unlikely to explain the observed behavior. The decomposition of TOMCAT ozone time series and ERA5 geopotential height into the first two wavenumber components shows a clear correlation between the two variables in the middle stratosphere and demonstrates a weakening and a shift in the wavenumber‐1 planetary wave activity over the past two decades. Finally, the analysis of the polar vortex position and strength points to a decadal oscillation with a reversal pattern at the beginning of the century. The same is found in the ozone trend asymmetry. This further stresses the link between changes in the polar vortex position and the identified ozone trend pattern.

New constraints on Triton’s atmosphere from the 6 October 2022 stellar occultation

The atmosphere of Triton was probed directly by observing a ground-based stellar occultation on 6 October 2022. This rare event yielded 23 positive light curves collected from 13 separate observation stations contributing to our campaign. The significance of this event lies in its potential to directly validate the modest pressure fluctuation on Triton, a phenomenon not definitively verified by previous observations, including only five stellar occultations, and the Voyager 2 radio occultation in 1989. Using an approach consistent with a comparable study, we precisely determined a surface pressure of 14.07−0.13+0.21 μbar in 2022. This new pressure rules out any significant monotonic variation in pressure between 2017 and 2022 through direct observations, as it is in alignment with the 2017 value. Additionally, both the pressures in 2017 and 2022 align with the 1989 value. This provides further support for the conclusion drawn from the previous volatile transport model simulation, which is consistent with the observed alignment between the pressures in 1989 and 2017; that is to say, the pressure fluctuation is modest. Moreover, this conclusion suggests the existence of a northern polar cap extended down to at least 45°N–60°N and the presence of nitrogen between 30°S and 0°.

Numerical simulation and experimental study of hole cleaning

Insufficient hole cleaning causes tool wear and reduces drilling efficiency. Existing evaluation methods and models are limited. In this study, a universal method is proposed to assess hole cleaning efficiency (HCE). A coupled computational fluid dynamics and discrete element method (CFD-DEM) numerical model for non-Newtonian fluid simulation of cuttings transport is developed. The influence of various factors on HCE was analyzed from an energy and particle collision perspective, with a particular focus on the mechanisms of fluid viscosity and rate of penetration (ROP) on cuttings settling. Results show that increased fluid viscosity improves HCE, while excessive viscosity negatively affects it. Higher ROP results in increased solid particle concentration and collision probability, leading to energy loss and reduced efficiency. Lower HCE was observed when the inclination deviated from the vertical. The HCE can be significantly improved by increasing the fluid velocity and reducing the eccentricity. A comprehensive prediction model for HCE is established using Design of Experiment (DOE), dimensional analysis, and nonlinear regression. This model incorporates a generalized fluid apparent viscosity, taking into account the impact of each rheological parameter. Additionally, it can be applied to predict hole cleanliness in both Newtonian and non-Newtonian fluids. By comparing the experimental results of hole cleanliness in three distinct fluids, the regression model yielded reliable predictive results. The findings enhance understanding regarding how fluid properties and the ROP affect cuttings transport and enable precise and convenient prediction and optimization of hole cleaning efficiency.