Volume Size Research Articles

Characterisation of the heterogeneity of a sand specimen in triaxial compression using x-ray CT and representative elementary volumes

Standard laboratory tests, such as the triaxial test, are often considered to be element tests. But, when observing such a test, it becomes obvious that this assumption of homogeneity is far from accurate. The localisation of strain is often visible to the naked eye and becomes even more obvious when observed on the grain scale. Other variables, such as those describing the soil fabric, are expected to localise as well. In this work, two sand samples are analysed at different loading states regarding the heterogeneity of three soil variables: void ratio, coordination number and contact orientation anisotropy. For this purpose, the size of a Representative Elementary Volume (REV) is determined using three criteria: the convergence of the mean and variance of the variables with increasing element size as well as a χ2-test. The size of the REV is varying depending on the chosen variable but almost the same for the two specimens when related to the mean grain diameter d50. The REV is placed in a regular grid throughout the specimen and the three variables are determined for each REV. The stochastic as well as spatial heterogeneity is identified for each specimen. As one of the samples is analysed for different loading states throughout a triaxial test, the evolution of the soil heterogeneity is identified. A localisation of all three variables can be observed at the end of the triaxial test as well as a strong initial heterogeneity for both sand samples.

WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.

The size of image volumes in connectomics studies now reaches terabyte and often petabyte scales with a great diversity of appearance due to different sample preparation procedures. However, manual annotation of neuronal structures (e.g., synapses) in these huge image volumes is time-consuming, leading to limited labeled training data often smaller than 0.001% of the large-scale image volumes in application. Methods that can utilize in-domain labeled data and generalize to out-of-domain unlabeled data are in urgent need. Although many domain adaptation approaches are proposed to address such issues in the natural image domain, few of them have been evaluated on connectomics data due to a lack of domain adaptation benchmarks. Therefore, to enable developments of domain adaptive synapse detection methods for large-scale connectomics applications, we annotated 14 image volumes from a biologically diverse set of Megaphragma viggianii brain regions originating from three different whole-brain datasets and organized the WASPSYN challenge at ISBI 2023. The annotations include coordinates of pre-synapses and post-synapses in the 3D space, together with their one-to-many connectivity information. This paper describes the dataset, the tasks, the proposed baseline, the evaluation method, and the results of the challenge. Limitations of the challenge and the impact on neuroscience research are also discussed. The challenge is and will continue to be available at https://codalab.lisn.upsaclay.fr/competitions/9169. Successful algorithms that emerge from our challenge may potentially revolutionize real-world connectomics research and further the cause that aims to unravel the complexity of brain structure and function.

A dynamic incentive mechanism for data sharing in manufacturing industry

Data sharing is a critical component in a blockchain traceability platform. Therefore, creating a reasonable incentive mechanism to ensure that all enterprises participate in data sharing is vital for blockchain platforms. Currently, many researchers employ evolutionary game theory to analyze problems related to data sharing. However, evolutionary game theory typically assumes that the population composed of enterprises is mixed uniformly. Enterprises in the manufacturing industry are not uniformly mixed, as they tend to have specific connections with each other due to the size of enterprises and volume of business. Therefore, a networked evolutionary game is introduced to solve this problem. Firstly, an incentive model for enterprises sharing data is established. Then, a scale-free network is employed to simulate the connections between enterprises. To comprehensively consider the individual and group benefits of enterprises in the game, this study designs a strategy update rule for networked evolutionary game based on Discrete Particle Swarm Optimization and Variable Neighborhood Descent algorithm. To tackle the challenge of determining reasonable incentive values in networked evolutionary games, this study proposes a dynamic incentive mechanism based on the Q-Learning algorithm. Finally, the experiments indicate that this method can successfully facilitate the stable involvement of enterprises in data sharing.

Homogenisation method based on energy conservation and independent of boundary conditions

The foundation of homogenisation methods rests on the postulate of Hill–Mandel, describing energy consistency throughout the transition of scales. The consideration of this principle is therefore crucial in the discipline of Digital Rock Physics which focuses on the upscaling of rock properties. For this reason, numerous studies have developed numerical schemes for porous media to enforce the Hill–Mandel condition to be respected. The most common method is to impose specific boundary conditions, such as periodic ones. However, these boundary conditions influence both the effective property and the size of the REV. The recent study of Thovert and Mourzenko (2020) has shown that most boundary conditions still result in the same intrinsic effective physical property if the averaging is applied outside the range of the boundary layer. From this discovery, it becomes logical to question the status of Hill–Mandel postulate in porous media when homogenising away from the boundary. In this contribution, we simulate Stokes flow through random packings of spheres and a range of rock microstructures. For each, we plot the evolution of the ratio micro- vs macro-scale of the energy of the fluid transport outside the boundary layer, for a growing subsample size of porous media. Here, we prove that we naturally find energy consistency across scales when reaching the size of the Representative Elementary Volume (REV), which is a known condition for rigorous upscaling. Furthermore, we show that this index for the energy consistency is a more accurate indicator of REV convergence since the mean value is already known to be unitary.

Surface Characterization Gel Grown Cerium Tartrate Crystals

Cerium tartrate crystals were grown from sodium metasilicate gel and water solutions of tartaric acid and cerium chloride as the reactants. Crystals grown were spherulitic in size. The principle objective of this investigation is to determine the surface area, pore volume and pore size of CeT sample. BET surface area was calculated from the BET plot; pore size distributions were calculated using BJH model. The pore volume was measured at the single point of p/p0 = 0.05. The Adsorption / Desorption Isotherm for cerium tartrate, Pore Size Distribution by BJH Method, Pore Size Distribution by DFT method and Volume Histogram By DFT Method was studied respectively for the CeT sample. The isotherm obtained for the sample demonstrates that it belongs to the type II isotherm.

The bubbly life and death of animal and plant milk foams.

Milk foams are fragile objects, readily prepared for frothy cappuccinos and lattes using bovine milk. However, evolving consumer preferences driven by health, climate change, veganism, and sustainability have created a substantial demand for creating frothy beverages using plant-based milk alternatives or plant milks. In this contribution, we characterize maximum foam volume and half-lifetime as metrics for foamability and foam stability and drainage kinetics of two animal milks (cow and goat) and compared them to those of the six most popular, commercially available plant milks: almond, oat, soy, pea, coconut, and rice. We used three set-ups: an electric frother with cold (10 °C) and hot (65 °C) settings to emulate the real-life application of creating foam for cappuccinos, a commercial device called a dynamic foam analyzer or DFA and fizzics-scope, a bespoke device we built. Fizzics-scope visualizes foam creation, evolution, and destruction using an extended prism-based imaging system facilitating the capture of spatiotemporal variation in foam microstructure over a broader range of heights and liquid fractions. Among the chosen eight milks, oat produces the longest-lasting foams, and rice has the lowest amount and stability of foam. Using the hot settings, animal milks produce more foam volume using an electric frother than the top three plant milks in terms of foamability (oat, pea, and soy). Using the cold settings, oat, soy, and almond outperform cow milk in terms of foam volume and lifetime for foams made with the frother and sparging. Most plant milks have higher viscosity due to added polysaccharide thickeners, and in some, lecithin and saponin can supplement globular proteins as emulsifiers. Our studies combining foam creation by frothing or sparging with imaging protocols to track global foam volume and local bubble size changes present opportunities for contrasting the physicochemical properties and functional attributes of animal and plant-based milk and ingredients for engineering better alternatives.

Removal of eutrophication agents from wastewater using glauconite-based sorbents

Excessive phosphorus and nitrogen in water and sediment may cause eutrophication, which poses a potential risk to drinking water safety and the sustainability of aquatic ecosystems. The research focuses on the removal of phosphates and ammonium ions from aqueous solutions using a new thermally and microwave-treated glauconite. The surface morphology of the samples was studied by SEM. BET surface area, pore volume, and pore size distribution were measured. Adsorption studies were carried out in static and dynamic conditions. The best fit for adsorption of both pollutants is given by the Langmuir-Freundlich and BET models. The calcined sample showed the lowest adsorption capacity for phosphate (1.78 mg/g) but the highest capacity for ammonium (20.67 mg/g). For the microwave-irradiated sample, the adsorption capacity for ammonium increases from 0.723 to 4.37 mg/g, while that for phosphate remains almost at the same level (101.21 mg/g). In dynamic conditions, phosphorus was most efficiently retained by natural glauconite (more than 60% retention rate), and ammonium nitrogen by glauconite that was thermally treated in a muffle furnace (more than 80% retention rate after 3 h).

Soft-rigid granular mixtures: Role of particle shape and rolling resistance in response under compressive loads

Mixtures of recycled tyre aggregates and common granular geo-material such as gravel and sand have been widely used for various applications in geotechnical engineering, such as backfill, lightweight construction geomaterial and pavement subbase layers. The mechanical properties and characteristics of various soft-rigid granular blends has been extensively studied in the past. The main objective of these studies is to determine suitable mix designs for different applications and provide a better understanding of material response under applied loads. Experimental and numerical studies indicate the paramount importance of particle interaction at the microscale on the response of the soft-rigid granular mixtures at the macro scale. The stark contrast in stiffness (or flexibility) of soft tyre particles to rigid sand or gravel particles, means that in the soft-rigid mixtures under shearing or compressive loads, the deformation of soft tyre particles and continuous change of shape and contact area and hence constant evolution of frictional resistance plays an important role in the behaviour of these blends. In the present research mixtures of gravel and tyre particles in a range of volume ratios and size ratios were modelled using DEM (discrete element method) and calibrated to match one-dimensional compressibility experimental data obtained by the team. The effect of the shape of soft particles on the compressive response of soft-rigid granular mixtures is studied through rolling resistance in DEM. The role of rolling friction is studied in detail. Rolling resistance is found to be an important parameter to simulate the behaviour of the particle shape of these mixtures. Microscopic studies like spin analysis and share of contact force is performed to understand the observed response better. However, the increase in rolling resistance value beyond a calibrated value is found to have little impact on the macroscopic behaviour of these mixes.

Bio-inspired synthesis of N-doped TiO2/C nanocrystals using jellyfish mucus with high visible-light photocatalytic efficiency.

Non-metal doping of titanium dioxide (TiO2) has been widely investigated, because it can facilely improve the optical response of TiO2 under visible light excitation in environmental pollution treatments. In the ongoing efforts, however, little consideration has been given to the use of harmful marine organisms as dopants. Here, we employed the natural mucus proteins of the large harmful jellyfish Aurelia coerulea and Nemopilema nomurai, which have frequently bloomed in East Asian marginal seas in recent decades, to synthesize mesoporous nitrogen-doped TiO2 nanocrystals modified with carbon (N-TiO2/C) by a simple hydrothermal method. These nanocrystals were composed of predominantly anatase phase and a small amount of brookite phase TiO2. Their mesoporous structures changed with the variation of the volume ratio of jellyfish mucus added to tetrabutyl titanate (TBT). At the same ratio, larger surface area and pore volume but smaller pore size were observed in N-TiO2/C nanocrystals from N. nomurai rather than A. coerulea. Nitrogen was determinately doped into the lattice of the prepared nanocrystals and the carbon species were modified on their surfaces, which narrowed the band gap, facilitated the separation of photogenerated electron-hole pairs and favored the absorption of visible light, thus improving their visible light photocatalytic activity. The photocatalytic degradation efficiency of Rhodamine B (RhB) under visible light irradiation first increased and then decreased with the gradual increase of the volume ratio of jellyfish mucus proteins to TBT. The maximum reached 97.52% in 20 min from N-TiO2/C nanocrystals synthesized using N. nomurai mucus at the volume ratio of 4 : 1, which showed a remarkably strong visible light absorption, lower band gap energy and smaller electron transfer resistance. These N-TiO2/C nanocrystals also had a relatively stable crystal structure in multiple degradation reactions. The main active species including superoxide radicals (˙O2 -), photogenerated holes (h+) and hydroxyl radicals (˙OH) were found to play a major role in the degradation process of RhB. This study highlights the potential high-value reapplication of harmful jellyfish mucus as a natural organic matrix in fabricating advanced materials with optimized functional properties.

Reactivated Spent Bleaching Earth as a New Path in Waste Resource Utilization for the Crude Palm Oil Bleaching Process

The palm oil refining process usually uses adsorbents. The commonly used adsorbent is Bleaching Earth. However, this raises a new problem: hazardous waste in the refining process, namely Spent Bleaching Earth (SBE). For this reason, one of which is the utilization of SBE as an adsorbent through a reactivation process. This study aims to determine the characterization of RBE produced from the microwave reactivation process and acid solution as an adsorbent in the palm oil (CPO) bleaching process. The SBE reactivation process was carried out using microwaves and sulphate acid solution at concentrations 3N. RBE characteristics were analyzed using Scanning Electron Microscopy - energy dispersive X-ray spectroscopy (SEM-EDS) and Brunner Emmet Teller (BET) - Barrett-Joyner-Halenda (BJH). The resulting RBE characteristics include surface area, pore volume, and pore size of 436,820 m2/g, 0.544 cc/g, and 2.488 nm, respectively. Patricelli model is more appropriate to use to explain the mechanism of the SBE desorption process using the MAE method with the coefficient of determination value of 0.9931. The palm oil adsorbed using RBE has 10R/20Y/0.9W of color quality, 3.93% free fatty acid number, and 11.61 meq O2/kg peroxide number. In this study, SBE was successfully converted into RBE by microwave reactivation process, and the excellent performance of RBE in palm oil bleaching was verified. This research not only helps to solve the environmental problems in the process of palm oil refining but also provides a new way for waste resource utilization.

Predicting cervical cancer target motion using a multivariate regression model to enable patient selection for adaptive external beam radiotherapy

Background and purposeInterfraction motion during cervical cancer radiotherapy is substantial in some patients, minimal in others. Non-adaptive plans may miss the target and/or unnecessarily irradiate normal tissue. Adaptive radiotherapy leads to superior dose-volume metrics but is resource-intensive. The aim of this study was to predict target motion, enabling patient selection and efficient resource allocation. Materials and methodsForty cervical cancer patients had CT with full-bladder (CT-FB) and empty-bladder (CT-EB) at planning, and daily cone-beam CTs (CBCTs). The low-risk clinical target volume (CTVLR) was contoured. Mean coverage of the daily CTVLR by the CT-FB CTVLR was calculated for each patient. Eighty-three investigated variables included measures of organ geometry, patient, tumour and treatment characteristics. Models were trained on 29 patients (171 fractions). The Two-CT multivariate model could use all available data. The Single-CT multivariate model excluded data from the CT-EB. A univariate model was trained using the distance moved by the uterine fundus tip between CTs, the only method of patient selection found in published cervix plan-of-the-day studies. Models were tested on 11 patients (68 fractions). Accuracy in predicting mean coverage was reported as mean absolute error (MAE), mean squared error (MSE) and R2. ResultsThe Two-CT model was based upon rectal volume, dice similarity coefficient between CT-FB and CT-EB CTVLR, and uterine thickness. The Single-CT model was based upon rectal volume, uterine thickness and tumour size. Both performed better than the univariate model in predicting mean coverage (MAE 7 %, 7 % and 8 %; MSE 82 %2, 65 %2, 110 %2; R2 0.2, 0.4, −0.1). ConclusionUterocervix motion is complex and multifactorial. We present two multivariate models which predicted motion with reasonable accuracy using pre-treatment information, and outperformed the only published method.

Integrated workflow for prediction of organic pore volume in unconventional plays, an example from the Duvernay formation, Canada

Organic pores provide the primary storage space for hydrocarbons in some unconventional plays. However, organic pore volume and pore size distribution data are not routinely collected due to time, labor, and cost. This work presents an efficient workflow for the estimation of organic pore volume in self-sourcing reservoirs using more routinely gathered mineral and geochemical data and machine learning methods. This approach provides comparable results to the analytical approach of using subcritical N2 adsorption, but at significantly reduced cost. The Late Devonian Duvernay Formation of western Canada is used as an example to develop the workflow. This workflow should be adaptable to other locations.This work utilized total organic carbon (TOC), Rock-Eval pyrolysis, and mineral data. Data processing was performed prior to modeling to improve prediction accuracy and precision. Specifically, data transformation, stratification, and stratified three-fold cross validation approaches are used to overcome limitations of small datasets and improve model optimization. Multilinear Regression and Random Forest modeling are benchmarked for prediction optimization. Ensuring that training datasets include end-member data is critical to increase the reliability of model generalization. Stepwise regression and factor significance are used to select important factors in the modeling, observing that not all available data are needed for a meaningful prediction.

Adipocytokines and Inflammation in Patients and a Gerbil Model: Implications for Obesity-Related and Nonobese Diabetes.

Background: Obesity is a predisposing risk factor for type 2 diabetes mellitus (T2DM). Actually, not only obese/overweight but also nonobese/lean individuals may be prone to T2DM. This study is aimed at identifying the contribution of adipose tissue to the development of nonobese diabetes (NOD) and obese diabetes (OD). Methods: Serum samples from the nonobese nondiabetes (NOND, n = 47, age = 46.8 ± 8.4, BMI ≤ 23.9 kg/m2) controls, NOD (n = 48, age = 50.7 ± 6.5, BMI ≤ 23.9 kg/m2) and OD (n = 65, age = 49.8 ± 10.2, BMI ≥ 28 kg/m2) patients were utilized to measure the expression of metabolic indicators, adipocytokines, inflammatory factors. Different adipose depots from offspring with corresponding blood glucose and obesity levels of a spontaneously diabetic gerbil line with various degrees of diabetic penetrance and body weights were examined for adipocytokines and inflammation factors detected by ELISA and western blot. Adipose tissue volume and fat cell size of the gerbils were evaluated by magnetic resonance imaging and immunohistochemistry, respectively. Results: The study yielded four key findings. Firstly, in comparison to the NOD group, the OD group exhibited more severe insulin resistance (IR) and metabolic dysfunction in both patients and gerbils, attributed to higher visceral adipose tissue mass and larger fat cell sizes. Secondly, in gerbils, gonadal fat deposition was linked to obesity development, whereas kidney fat deposition correlated with obesity and diabetes occurrence. Thirdly, in both patients and gerbils, the interplay between adiponectin and leptin levels in serum may significantly influence the development of obesity and diabetes. Lastly, heightened expression of MCP3 in gerbils' kidney adipose tissue may serve as a pivotal factor in initiating obesity-associated diabetes. Conclusions: Our study, which may be considered a pilot investigation, suggests that the interaction of adipocytokines and inflammation factors in different adipose depots could play diverse roles in the development of diabetes or obesity.

Evaluation of Nitrogen-Doped Adsorbents Based on Reduced Graphene Oxide as Platforms for CO2 Capture

CO2 emissions into the atmosphere have been rapidly rising due to human activities, resulting in the escalation of global warming. To mitigate climate change, it is imperative to develop materials for CO2 capture with high CO2 capacity and low production costs. Herein, we developed a facile method to obtain adsorbents based on reduced graphene oxide (rGO) sheets, NrGO(1 - X)700, where X represents the mass of diethylenetriamine (DETA) (X = 1, 2 and 4 g) used in the preparation. The materials NrGO(1 - 1)700, NrGO (1 - 2)700, and NrGO(1 - 4)700 were obtained from graphene oxide dispersions, followed by DETA impregnation and chemical activation with K2CO3. N2 isotherms demonstrated that the materials simultaneously presented micro and mesopores with similar values of specific surface area (280.16 to 310.32 m2 g-1), pore volume (0.26 to 0.28 cm3 g-1) and pore size (3.78 to 3.80 nm). CO2 sorption experiments revealed that the material NrGO(1 - 4)700, containing the highest amount of pyridinic, graphitic, and amino nitrogen functionalities, showed the best CO2 adsorption capacity. Diffuse reflectance Fourier transformed infrared spectroscopy experiments indicated stronger solid-gas interactions for NrGO(1 - 4)700 than for the other materials.

More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload. This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments. From the pre-COVID-19 pandemic year (May 2019 to February 2020) to the most recent study year (April 2022 to March 2023), the average time PCPs spent in the EHR per 8 hours of scheduled clinic appointments increased (+28.4 minutes, 7.8%), as did time in orders (+23.1 minutes, 58.9%), inbox (+14.0 minutes, 24.4%), chart review (+7.2 minutes, 13.0%), notes (+2.9 minutes, 2.3%), outside scheduled hours on days with scheduled appointments (+6.4 minutes, 8.2%), and on unscheduled days (+13.6 minutes, 19.9%). Primary care physicians received more patient medical advice requests (+5.4 messages, 55.5%) and prescription messages (+2.3, 19.5%) per 8 hours of scheduled clinic appointments, but fewer patient calls (-2.8, -10.5%) and results messages (-0.3, -2.7%). While total time in the EHR continued to increase in the final study year (+7.7 minutes, 2.0%), inbox time decreased slightly from the year prior (-2.2 minutes, -3.0%). Primary care physicians' average aFTE decreased 5.2% from 0.66 to 0.63 over 4 years. Primary care physicians' time in the EHR continues to grow. While PCPs' inbox time may be stabilizing, it is still substantially higher than pre-pandemic levels. It is imperative health systems develop strategies to change the EHR workload trajectory to minimize PCPs' occupational stress and mitigate unnecessary reductions in effective physician workforce resulting from the increased EHR burden.

Sex Differences in Presentation, Treatment, and Survival in Patients Receiving Palliative (Chemo)Radiotherapy for Non-Small Cell Lung Cancer.

The aim of this study was to analyze sex differences in a real-world cohort of patients who received palliative thoracic radiotherapy or chemoradiotherapy for non-small cell lung cancer. Retrospectively, baseline, treatment, toxicity, and survival data from a single institution were analyzed. The study included 181 patients (82 females, 99 males). Despite borderline significant differences in disease presentation (T and N stage), final assignment to stage II, III or IV was similar. The same was true for target volume size. Neither radiotherapy parameters nor systemic treatment approaches were significantly different. Toxicity profiles and survival were similar too. Less than 1 out of 3 patients experienced high-grade toxicity, largely esophagitis. Median survival was 8.1 (males) versus 7.8 months (females) and the corresponding 2-year survival rates were 16 and 15%, respectively (p=0.78). Relevant sex differences were not observed in this study of common radiotherapy regimes such as 10 fractions of 3 Gy or 15 fractions of 2.8 Gy, the latter often combined with carboplatin/vinorelbine chemotherapy.

A Regional Aerosol Model for the Middle Urals Based on CALIPSO Measurements

The present work aims to develop a regional Middle Urals Aerosol model (MUrA model) based on the joint analysis of long-term ground-based photometric measurements of the Aerosol Robotic NETwork (AERONET) and the results of lidar measurements of the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite relying on information on the air trajectories at different altitudes calculated using the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory model) software package. The MUrA model contains parameters of normalized volume size distributions (NVSDs) characterizing the tropospheric aerosol subtypes detected by the CALIPSO satellite. When comparing the MUrA model with the global CALIPSO Aerosol Model (CAMel), we found significant differences in NVSDs for elevated smoke and clean continental aerosol types. NVSDs for dust and polluted continental/smoke aerosol types in the global and regional models differ much less. The total volumes of aerosol particles along the atmospheric column reconstructed from satellite measurements of the attenuation coefficient at a wavelength of 532 nm based on the regional MUrA model and global CAMel are compared with the AERONET inversion data. The mean bias error for the regional model is 0.016 μm3/μm2, and 0.043 μm3/μm2 for the global model.

20 years of columnar aerosol properties at Valencia area (Eastern Spain) by ground-based sun-photometry

In this paper, a climatological study focused on the analysis of atmospheric aerosols properties over Burjassot and Aras de los Olmos AERONET sites, located at Eastern Spain, is performed. Computed mean values for Aerosol Optical Depth (AOD440), Ångström exponent (α440−870) and columnar water vapor (w) in Burjassot (Aras de los Olmos) are 0.19±0.08 (0.10±0.02), 1.21±0.16 (1.18±0.25) and 1.87±0.68cm (0.94±0.10cm), respectively. From the monthly statistics of w and AOD, it is concluded that summer months are characterised by higher humidity and turbidity, being the latter favoured by particle stagnation, recirculation, secondary aerosol formation, hygroscopic processes and North African dust intrusions. Regarding the volume size distribution, well developed fine and coarse modes are found in summer. On the other hand, the spectral dependence of the asymmetry parameter (g) describes a decrease in λ up to 870nm, and then a slight increase due to the influence of dust particles. The computed mean values for the asymmetry parameter (g440) are 0.700±0.013 (0.709±0.016) for Burjassot (Aras de los Olmos). With respect to the Single Scattering Albedo (SSA) and the complex refractive index, an additional analysis using Level 1.5 data is performed, as relatively few data points pass the filters imposed by the Level 2.0 conditions. In the case of SSA, which is found to be larger in spring and summer months, the obtained mean annual values at 440nm are 0.94±0.03 (0.95±0.03) for Burjassot (Aras de los Olmos). Finally, regarding the complex refractive index, the mean values of the real part (m440) are 1.50±0.03 (1.49±0.03), and for the imaginary part (∣k440∣) are 0.007±0.004 (0.004±0.003) in Burjassot (Aras de los Olmos). The present study is complemented with three analyses based on the distinction between the different aerosol types. To begin with, these are classified according to their nature, being the most abundant continental clean aerosols. Next, Gobbi diagrams are plotted for both sites, depicting a clustered region of coarse aerosols, as well as particle growth traces. Finally, the different air masses affecting the measurement sites are studied, reaching to the conclusion that these originated in the European and the African continents are the most turbid ones. To conclude this study, a seasonal Mann-Kendall test is applied to AOD, α, w and SSA measurements in order to study possible trends. Hence, a statistically significant (>80%) decreasing trend in AOD is observed for most months; whereas α, w and SSA do not show statistically significant long-term trends, only for a few months of the year.

Electric machine sizing consideration for ePumps in mobile hydraulics

AbstractEnvironmental concerns have pushed toward electrified technologies for off‐road vehicle actuations that can lower greenhouse gas emissions and reduce energy consumption. Replacing a central diesel engine with a dedicated electric machine (EM) as a prime mover for the hydraulic supply offers several opportunities for so‐called ePumps (aka electric‐driven pumps) to maximize energy efficiency and limit the usage of electric materials. This paper discusses the impact of different choices for the ePumps architecture (i.e., fixed vs. variable displacement pump; variable speed vs. fixed speed electrical machine), and on their main design parameters in terms of size and efficiency. Although the procedure followed in the study could be extended to different types of electric and hydraulic units, the paper particularly considers ePumps based on permanent magnet synchronous machines combined with axial piston machines. The importance of properly considering the ePump drive cycle and its cooling requirements is taken into account while addressing energy efficiency, mass, and overall compactness of the solution. The results show that an ePump based on a variable displacement pump, when compared to fixed displacement ePumps, reduces the electrical machine size both in volume and mass up to 40%, when the high‐pressure demand is not combined with high flow rate demand, thus decreasing the cost of the EM. In all drive cycles, the variable speed EM–fixed displacement pump architecture has a higher efficiency, ranging from 1% to 5%, compared to the case of fixed speed EM–variable displacement pump. Finally, the paper compares the advantages and shortcomings of each ePump architecture presented, based on representative drive cycles.

Experimental study on dribbling characteristics of gasoline/biodiesel blends after the end-of-injection

The effects of biodiesel addition on gasoline fuel dribbling process and characteristics after the end-of-injection (EOI) were investigated in a constant volume chamber at different injection pressures and ambient temperatures. The fuel dribbling process was recorded with high spatial and time resolution by using the microscopic shadow imaging technique, and the corresponding dribble velocity, dribble volume and droplet size were extracted. The results showed that the fuel dribbling experienced four typical morphological structures (spray-like, membrane-type, ligament-type, droplets) after the EOI under all the tested conditions. Additionally, increased biodiesel proportion in the blends caused decreased dribble velocity, longer dribbling duration, and increased droplet size, indicating deteriorated breakup and atomization processes of the dribbling flow. Moreover, the higher injection pressure increased the dribble amount but reduced the dribbling duration and droplet size. The increased ambient temperature caused faster evaporation of the dribbling fuel, resulting in a significant decrease in the dribble size. So, these two strategies were believed to be overall favorable to restrain the adverse effect on gasoline fuel dribbling characteristics caused by the addition of biodiesel.