Size Distribution Parameters Research Articles

Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetery Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE) satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered backprojection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulated RSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.

Comparison of potato (Solanum tuberosum L.) tuber size distribution fitting methods and evaluation of the relationship between soil properties and estimated distribution parameters

AbstractAccurate estimation of tuber size distribution (TSD) parameters in discretely categorized potato (Solanum tuberosum L) yield samples is desirable for estimating modal tuber sizes, which is fundamental to yield prediction. In the current work, systematic yield digs were conducted on five commercial fields (N = 119) to compare the Weibull, Gamma and Gaussian distribution functions for relative-likelihood-based goodness-of-fit to the observed discrete distributions. Parameters were estimated using maximum likelihood estimation (MLE) for the three distributions but were also derived using the percentiles approach for the Weibull distribution to compare accuracy against the MLE approaches. The relationship between TSD and soil nutrient variability was examined using the best-fitting model's parameters. The percentiles approach had lower overall relative likelihood than the MLE approaches across five locations, but had consistently lower Root Mean Square Error in the marketable tuber size range. Negative relationships were observed between the percentile-based shape parameter and the concentrations of Phosphorus and Nitrogen, with significant (non-zero-overlapping 95% confidence interval) regression coefficients for P (−0.74 ± 0.33 for distribution of proportional tuber numbers and −1.3 ± 0.62 for tuber weights). Stem density was negatively associated with the scale and mode of tuber number (regression coefficients −0.98 ± 0.63 and −1.08 ± 0.78 respectively) and tuber weight (regression coefficients −0.99 ± 0.78 and −1.04 ± 0.69 respectively) distributions. Phosphorus is negatively related to the scale of the tuber-number-based distribution while positively associating with the tuber weight distribution. The results suggest that excess P application was associated with the increase in small tubers that did not contribute significant weight to the final yield.

Machine learning tensile strength and impact toughness of wheat straw reinforced composites

The wheat straw reinforced composite is considered as a “green composite” as it utilizes biodegradable and recyclable food waste materials as reinforcing materials. Mechanical properties, such as tensile strength and impact toughness, are greatly dependent on the composite content and processing parameters. While compression molding is one of popular methods to fabricate the wheat straw/polypropylene composite, experimental trials to achieve targeted mechanical properties can be time-consuming and expensive. In this work, we develop the Gaussian process regression model to present the relationship among the fiber content, processing parameters of the compression molding, and mechanical performance of wheat straw reinforced polypropylene composites. The model achieves a correlation coefficient of 99.13% (95.68%), a root mean square error of 0.0857 (0.4369), and a mean absolute error of 0.0693 (0.3265) for tensile strength (impact toughness). The models are simple and fast to implement, produce predictions with high accuracy, and thus might be considered as efficient tools for mechanical property estimations. Should data become available, the model may be extended to include other descriptors, such as the wheat straw length, size distribution, and chemical treatment parameters.

Ambient aerosol properties in the remote atmosphere from global-scale in situ measurements

Abstract. In situ measurements of aerosol microphysical, chemical, and optical properties were made during global-scale flights from 2016–2018 as part of the Atmospheric Tomography Mission (ATom). The NASA DC-8 aircraft flew from ∼ 84∘ N to ∼ 86∘ S latitude over the Pacific, Atlantic, Arctic, and Southern oceans while profiling nearly continuously between altitudes of ∼ 160 m and ∼ 12 km. These global circuits were made once each season. Particle size distributions measured in the aircraft cabin at dry conditions and with an underwing probe at ambient conditions were combined with bulk and single-particle composition observations and measurements of water vapor, pressure, and temperature to estimate aerosol hygroscopicity and hygroscopic growth factors and calculate size distributions at ambient relative humidity. These reconstructed, composition-resolved ambient size distributions were used to estimate intensive and extensive aerosol properties, including single-scatter albedo, the asymmetry parameter, extinction, absorption, Ångström exponents, and aerosol optical depth (AOD) at several wavelengths, as well as cloud condensation nuclei (CCN) concentrations at fixed supersaturations and lognormal fits to four modes. Dry extinction and absorption were compared with direct in situ measurements, and AOD derived from the extinction profiles was compared with remotely sensed AOD measurements from the ground-based Aerosol Robotic Network (AERONET); this comparison showed no substantial bias. The purpose of this work is to describe the methodology by which ambient aerosol properties are estimated from the in situ measurements, provide statistical descriptions of the aerosol characteristics of different remote air mass types, examine the contributions to AOD from different aerosol types in different air masses, and provide an entry point to the ATom aerosol database. The contributions of different aerosol types (dust, sea salt, biomass burning, etc.) to AOD generally align with expectations based on location of the profiles relative to continental sources of aerosols, with sea salt and aerosol water dominating the column extinction in most remote environments and dust and biomass burning (BB) particles contributing substantially to AOD, especially downwind of the African continent. Contributions of dust and BB aerosols to AOD were also significant in the free troposphere over the North Pacific. Comparisons of lognormally fitted size distribution parameters to values in the Optical Properties of Aerosols and Clouds (OPAC) database commonly used in global models show significant differences in the mean diameters and standard deviations for accumulation-mode particles and coarse-mode dust. In contrast, comparisons of lognormal parameters derived from the ATom data with previously published shipborne measurements in the remote marine boundary layer show general agreement. The dataset resulting from this work can be used to improve global-scale representation of climate-relevant aerosol properties in remote air masses through comparison with output from global models and assumptions used in retrievals of aerosol properties from both ground-based and satellite remote sensing.

Retrieval of Raindrop Size Distribution Using Dual-Polarized Microwave Signals from LEO Satellites: A Feasibility Study through Simulations.

In this paper, a novel approach for raindrop size distribution retrieval using dual-polarized microwave signals from low Earth orbit satellites is proposed. The feasibility of this approach is studied through modelling and simulating the retrieval system which includes multiple ground receivers equipped with signal-to-noise ratio estimators and a low Earth orbit satellite communicating with the receivers using both vertically and horizontally polarized signals. Our analysis suggests that the dual-polarized links offer the opportunity to estimate two independent raindrop size distribution parameters. To achieve that, the vertical and horizontal polarization attenuations need to be measured at low elevation angles where the difference between them is more distinct. Two synthetic rain fields are generated to test the performance of the retrieval. Simulation results suggest that the specific attenuations for both link types can be retrieved through a least-squares algorithm. They also confirm that the specific attenuation ratio of vertically to horizontally polarized signals can be used to retrieve the slope and intercept parameters of raindrop size distribution.

Modeling Asian Dust Storms Using WRF‐Chem During the DRAGON‐Asia Field Campaign in April 2012

AbstractAsian mineral dust substantially influences air quality as well as weather and climate. It is important to forecast dust storms as a part of air quality modeling to protect public health and minimize the disruption to essential daily routines. In this study, we simulated the dust episodes during the DRAGON‐NE Asia field campaign in April 2012 utilizing the Weather Research and Forecasting model coupled with chemistry (WRF‐Chem) with 5 dust emission options and evaluated the model results with the measurements from multiple instruments including Korean geostationary satellites Geostationary Ocean Color Imager (GOCI) and Meteorological Imager (MI). The model well predicted the dust occurrences, transport, and vertically elevated structure, compared to the satellite aerosol optical depths (AOD), the Aerosol Robotic Network (AERONET) AOD and size distribution parameter Angstrom Exponent (AE), the ground‐based lidar and in‐situ observations. However, the model dust concentration varied depending on the selected dust emission option. The model also did not accurately simulate both AOD and AE. When the model AOD agreed with the AERONET AOD, AE did not agree. In general, the model concentrations were overestimated for large size particles (diameter 6–20 μm) and were underestimated for small size particles (0.5–3.6 μm), compared to the observed aerosol size distributions at surface in Korean Peninsula. Our analysis of the episode suggests that the dust is possibly mixed with the aerosols of anthropogenic origins in the Asian region. Therefore, accurate simulations of both anthropogenic aerosols and dust are helpful for evaluating models in the downwind region of the dust sources.

PSD and Fractal Dimension for flocculation with different parameters and ferric chloride, aluminium polychloride and aluminium sulfate as coagulants

In conventional water treatment, coagulation and flocculation stages play a very important role, once they are related to the success of the subsequent processes. Among the techniques applied to analyze these stages, analysis of images that aims to provide information related to the formed particles, such as parameters of Particle Size Distribution (PSD) and Fractal Dimension (Df), stands out. Thus, this study aimed to compare the evolution of these parameters and the Df along coagulation and flocculation processes, for different chemical coagulants and different conditions. It was verified that the parameter β1 of PSD tends to increase during time, indicating formation of larger particles, until the establishment of its stabilization level. It was also observed that for higher coagulant dosages and, especially, when turbidity in water was higher and Ferric Chloride and Aluminium Polychloride were used, the parameters β1 of PSD, after initial growth stage, decrease for later dynamic stabilization. As for Df, it was concluded that there is an initial tendency of growing, followed by a stabilization of its value during most of the flocculation process, indicating that the structural organization of the floc is not necessarily linked to the variations in its size. These conclusions can help further investigations and studies on coagulation/flocculation processes in order to understand how flocs behave over time, under the different chemicals used.

A Method for Soil Samples Collection during Site Assessment for Aquaculture

Assessment of soil quality is one of the crucial steps during the assessment of a site for aquaculture. However, no clear guidelines are available in literature to guide fish farmers about soil sample collection resulting in a waste of their time and energy. The present study was, therefore, designed to determine the variability of soil characteristics at different sites and give recommendations for sample collection during soil assessment. Two hundred and eighty-six (286) soil samples collected from different subsites of seven sampling sites were analyzed for particle size distribution and chemical parameters. Results showed significant variation in soil separate content at different subsites of a sampling site. At Moza Bahak Maken in district Sargodha, the soil was found to be sandy at one subsite and clayey on the other within 35 acres of land area. Moreover, significant differences in soil quality parameters were also found with varying sampling depths. pH of soil indicated the calcareous nature of the soil in Punjab and outruled the necessity to lime soil. Electrical conductivity measurements showed that soil in the Sargodha division can be characterized as very strongly saline. The study led to the conclusion that sample collection for soil analysis in aquaculture should be based on stratified sampling selecting at least three sampling points from each stratum. Soil samples should be collected in 1 ft. increment from the surface up to the depth that should be 1 ft. deep than the soil depth that will be dug in excavated ponds. Culturable fish/ shrimp species should be selected based on the salinity of soil at the proposed fish pond site.

Fog Measurements with IR Whole Sky Imager and Doppler Lidar, Combined with In Situ Instruments

This study describes comprehensive measurements performed for four consecutive nights during a regional-scale radiation fog event in Israel’s central and southern areas in January 2021. Our data included both in situ measurements of droplets size distribution, visibility range, and meteorological parameters and remote sensing with a thermal IR Whole Sky Imager and a Doppler Lidar. This work is the first extensive field campaign aimed to characterize fog properties in Israel and is a pioneer endeavor that encompasses simultaneous remote sensing measurements and analysis of a fog event with a thermal IR Whole Sky Imager. Radiation fog, as monitored by the sensor’s field of view, reveals three distinctive properties that make it possible to identify it. First, it exhibits an azimuthal symmetrical shape during the buildup phase. Second, the zenith brightness temperature is very close to the ground-level air temperature. Lastly, the rate of increase in cloud cover up to a completely overcast sky is very fast. Additionally, we validated the use of a Doppler Lidar as a tool for monitoring fog by proving that the measured backscatter-attenuation vertical profile agrees with the calculation of the Lidar equation fed with data measured by in situ instruments. It is shown that fog can be monitored by those two, off-the-shelf-stand-off-sensing technologies that were not originally designed for fog purposes. It enables the monitoring of fog properties such as type, evolution with time and vertical depth, and opens the path for future works of studying the different types of fog events.

Characteristics of Raindrop Size Distribution in Typhoon Nida (2016) before and after Landfall in Southern China from 2D Video Disdrometer Data

During the passage of Typhoon Nida, the raindrop size distribution parameters, the raindrop spectra, the shape and slope (μ–Λ) relationship, the radar reflectivity factor, and rain rate (Z–R) relationship were investigated based on a two-dimensional (2D) video disdrometer in Guangdong, China, from August 1 to 2, 2016. Due to the underlying surface difference between the ocean and land, this process was divided into two distinct periods (before landfall and after landfall). The characteristics of raindrop size distribution between the period before landfall and the period after landfall were quite distinct. The period after landfall exhibited higher concentrations of each size bin (particularly small drops) and wider raindrop spectral width than the period before landfall. Compared with the period before landfall, the period after landfall had a higher average mass-weighted mean diameter Dm that was smaller than those of other TCs from the same ocean (the Pacific). The μ–Λ relationship and Z–R relationship in this study were also compared with other TCs from the same ocean (the Pacific). This investigation of the microphysical characteristics of Typhoon Nida before landfall and after landfall may improve radar quantitative precipitation estimation (QPE) products and microphysical schemes by providing useful information.

Dynamics of long-term continuous culture of Limnospira indica in an air-lift photobioreactor.

SummaryMELiSSA (Microecological Life Support System Alternative) is a developing technology for regenerative life support to enable long‐term human missions in Space and has developed a demonstration Pilot Plant. One of the components of the MELiSSA Pilot Plant system is an 83L external loop air‐lift photobioreactor (PBR) where Limnospira indica (previously named Arthrospira sp. PC8005) is axenically cultivated in a continuous operation mode for long‐periods. Its mission is to provide O2 and consume CO2 while producing edible material. Biological and process characterization of this PBR is performed by analysing the effect of two main variables, dilution rate (D) and PFD (Photon Flux Density) illumination. A maximum oxygen productivity (rO2) of 1.35 mmol l−1 h−1 is obtained at a D of 0.025 h−1 and PFD of 930 µmol m−2 s−1. Photoinhibition can occur when a 1 g l−1 cell density culture is exposed to PFD higher than 1700 µmol m−2 s−1. This process is reversible if the illumination is returned to dim light (150 µmol m−2 s−1), proving the cell adaptability and capacity to respond at different illumination conditions. Influence of light intensity in cell composition is also described. Specific photon flux density (qPFD) has a direct effect on phycobiliproteins and chlorophyll content causing a decrease of 62.5% and 47.8%, respectively, when qPFD increases from 6.1 to 19.2 µmol g−1 s−1. The same trend is observed for proteins and the opposite for carbohydrate content. Morphological and spiral structural features of L. indica are studied by confocal microscopy, and size distribution parameters are quantified. A direct effect between trichome width and CDW/OD ratio is observed. Changes in size distribution are not correlated with environmental factors, further confirms the adaptation capacity of the cells. The systematic analysis performed provides valuable insights to understand the key performance criteria of continuous culture in air‐lift PBRs.

Validation of Ice Cloud Microphysical Properties Retrieval Using a Markov Chain Monte Carlo Algorithm

AbstractThe Markov chain Monte Carlo (MCMC) algorithm has been used for retrieving ice cloud microphysical properties in this paper. The retrieval data include effective radius (re), ice water content (IWC), number density (N0), and distribution width parameter (w).First we examine the algorithm feasibility using simulated W‐band radar reflectivity. The retrievals locate in a solution space around the exact results. Two methods are applied to produce a unique solution with maximum likelihood function, that is, the mean value of all acceptable sets of parameters in the chain and the first convergence sample. The results of the second method have a better performance compared with that of the first method. The algorithm has better performance when one particle size distribution (PSD) parameter is known than that when three PSD parameters are unknown.Then we apply the algorithm for CloudSat Cloud Profiling Radar (CPR) observations. Four habits, including column, plate, bullet rosette and sphere, are considered to analyze the influence on the retrieval accuracy. The averaged deviation ofres andIWCs obtained from MCMC algorithm among different habit assumptions has a maximum of about 10% and 5%, respectively. It appears clearly that the MCMC algorithm retrieval for short hexagonal column (HEXS) are the closest to that of the official products (2B‐CWC‐RO), while thick hexagonal plate (HEXF) has the largest bias. Retrievedre,IWC,N0, andwfrom radar reflectivity are in reasonable agreement with 2B‐CWC‐RO product, which indicate that the MCMC algorithm can produce reliable cloud properties from radar observations.

Vertical profile of aerosol characteristics including activation over a rain shadow region in India

Unique airborne observations of aerosol size spectral and chemical characteristics over the peninsular Indian region are illustrated in this case study. Multimodal lognormal distributions were required to fit the observed in situ aerosol size distribution. The aerosol composition and mixing state was deduced from the single-particle analyses of aerosols using the transmission electron microscope and soot photometer coupled with satellite retrieved aerosol classification, and back trajectory analyses. Organic carbon was the most prominent aerosol type found at all altitudes. Refractory black carbon aerosols which constituted about 10–12% of the aerosols in the boundary layer were primarily internally mixed with both inorganic and organic coating. Other major aerosol types were dust and sea salt, with the latter primarily found below 2 km. Further, the cloud forming ability of in-situ aerosols is tested through a cloud condensation nuclei closure analysis. The effective hygroscopicity decreased above cloud base due to the absence of sea salt aerosols. The change in large-scale winds with altitude affected the aerosol composition and hygroscopicity. The multimodal aerosol size distribution and hygroscopicity parameter (κ = 0.18) obtained for the cloud base aerosols over the rain shadow region are useful for studying aerosol-cloud interactions using regional cloud-resolving models.

Estimating Size and Number Density of Three-Dimensional Particles Using Truncated Cross-Sectional Data

Abstract The need for estimating three-dimensional (3D) information based on two-dimensional (2D) images has been increasing in numerous fields. It is essential in quality assessment, quality control, and process optimization. However, all the existing methods have not considered the data truncation issue, which is commonly faced in metrology. This paper proposes a new statistical approach to infer size distribution and volume number density (VND) of 3D particles based on 2D cross-sectional images with data truncation considered. In order to estimate the size distribution, a linkage is established between 3D particles and 2D observations with the existence of data truncation. Subsequently, this paper derives the likelihood function of 2D observations and an efficient Monte Carlo expectation-maximization algorithm is developed to estimate the parameters of size distribution. In addition, an explicit relationship between the 3D and 2D particle number densities is established and leveraged to estimate the VND and volume fraction. The effectiveness of the proposed method is demonstrated through both simulation study and real case studies in metal additive manufacturing and metal-matrix nanocomposites manufacturing.

Time-Resolved Laser-Induced Incandescence Measurements on Aerosolized Nickel Nanoparticles.

This work presents the first quantitative analysis of time-resolved laser-induced incandescence (TiRe-LII) measurements on aerosolized nickel nanoparticles in several gases and over a range of laser fluences. A measurement model composed of spectroscopic and heat transfer submodels is used to recover the particle size distribution parameters and the thermal accommodation coefficient (TAC). A qualitative analysis of the results reveals evidence of nonincandescent laser-induced emission temporally aligned with the laser pulse, and more laser energy is absorbed than can be accounted for from the modeled spectral absorption cross section of the nanoparticles. The TiRe-LII inferred particle size parameters were generally consistent with values found from ex situ transmission electron microscopy (TEM) analysis. The TACs for nickel nanoparticles in polyatomic gases were larger than those in monoatomic gases, which may indicate chemisorption.

Four new planetesimals around typical and pre-main-sequence stars (PLATYPUS) debris discs at 8.8 mm

ABSTRACT Millimetre continuum observations of debris discs can provide insights into the physical and dynamical properties of the unseen planetesimals that these discs host. The material properties and collisional models of planetesimals leave their signature on the grain size distribution, which can be traced through the millimetre spectral index. We present 8.8 mm observations of the debris discs HD 48370, CPD-72 2713, HD 131488, and HD 32297 using the Australian Telescope Compact Array (ATCA) as part of the PLanetesimals Around TYpical Pre-main-seqUence Stars (PLATYPUS) survey. We detect all four targets with a characteristic beam size of 5 arcsec and derive a grain size distribution parameter that is consistent with collisional cascade models and theoretical predictions for parent planetesimal bodies where binding is dominated by self-gravity. We combine our sample with 19 other millimetre-wavelength-detected debris discs from the literature and calculate a weighted mean grain size power-law index that is close to analytical predictions for a classical steady-state collisional cascade model. We suggest the possibility of two distributions of q in our debris disc sample; a broad distribution (where q ∼ 3.2–3.7) for ‘typical’ debris discs (gas-poor/non-detection), and a narrow distribution (where q < 3.2) for bright gas-rich discs. Or alternatively, we suggest that there exists an observational bias between the grain size distribution parameter and absolute flux that may be attributed to the detection rates of faint debris discs at $\rm \sim$cm wavelengths.

Efficacy of a portable, moderate-resolution, fast-scanning differential mobility analyzer for ambient aerosol size distribution measurements

Abstract. Ambient aerosol size distributions obtained with a compact scanning mobility analyzer, the “Spider” differential mobility analyzer (DMA), are compared to those obtained with a conventional mobility analyzer, with specific attention to the effect of mobility resolution on the measured size distribution parameters. The Spider is a 12 cm diameter radial differential mobility analyzer that spans the 10–500 nm size range with 30 s mobility scans. It achieves its compact size by operating at a nominal mobility resolution R=3 (sheath flow = 0.9 L min−1; aerosol flow = 0.3 L min−1) in place of the higher ratio of sheath flow to aerosol flow commonly used. The question addressed here is whether the lower resolution is sufficient to capture key characteristics of ambient aerosol size distributions. The Spider, operated at R=3 with 30 s up- and downscans, was co-located with a TSI 3081 long-column mobility analyzer, operated at R=10 with a 360 s sampling duty cycle. Ambient aerosol data were collected over 26 consecutive days of continuous operation, in Pasadena, CA. Over the 17–500 nm size range, the two instruments exhibit excellent correlation in the total particle number concentrations and geometric mean diameters, with regression slopes of 1.13 and 1.00, respectively. Our results suggest that particle sizing at a lower resolution than typically employed may be sufficient to obtain key properties of ambient size distributions, at least for these two moments of the size distribution. Moreover, it enables better counting statistics, as the wider transfer function for a given aerosol flow rate results in a higher counting rate.

The Effect of Humidity on the Atomization Process and Structure of Nanopowder Designed for Extinguishment.

Increasingly, firefighting aerosols are being used to extinguish fires. It is assumed that the extinguishing mechanism involves breaking the chain of physicochemical reactions occurring during combustion by binding free radicals at ignition. The radicals are most likely formed from the transformation of water molecules, with the active surfaces of aerosol micro- or even nanoparticles. The aerosol extinguishing method is very effective even though it does not reduce oxygen levels in the air. In contrast to typical extinguishing powders, the aerosol leaves a trace amount of pollutants and, above all, does not adversely affect the environment by depleting the ozone layer and increasing greenhouse effects. Depending on how the firefighting generators are released, the aerosol can act locally or volumetrically, but depending on environmental conditions, its effectiveness can be variable. The article presents the influence of environmental humidity on the atomization of aerosol nanosize, which confirms the radical combustion mechanism. This paper presents the effect of environmental humidity on the atomization of aerosol superfine (nano) particles. The main focus was on the grain distribution and its effect on the surface activity of the FP-40C type firefighting aerosol. Changes in the characteristic parameters of the particle size distribution of RRSB (Rosin-Rammler-Sperling-Bennet) are presented.

Soil burrow characterization by 3D image analysis: Prediction of macroinvertebrate groups from biopore size distribution parameters

Although scientific literature focuses mainly on earthworms, all soil macroinvertebrates play an important role in modifying the architecture of the soil pore space and, in turn, in soil functions. Notwithstanding the fact that non-invasive technology, such as X-ray tomography, has long been used to differentiate non-biopores from biopores, it is still difficult to distinguish the specific contribution different macroinvertebrates make to the soil biopore system. Unlike the object-based image analysis approach, when applied to a soil pore system, mathematical morphology permits the user to obtain a very accurate pore size distribution consistent with the physical principle of water retention. The aim of this work was to evaluate the potential of the parameters of this kind of biopore size distribution to differentiate between the burrows of five different macroinvertebrate groups, namely Earthworms, Millipedes juliform, Centipedes, Campodeiform larvae and Elateriform larvae, inoculated into repacked soil mesocosms and incubated (14 days) in the field from where the soil animals were originally collected.A two-fold approach was proposed in this work so as to obtain parameters by both pore size population distributions and Weibull modelling of the cumulative distributions. Then a predictive discriminant analysis was performed on selected parameters by using macroinvertebrate groups as grouping variables and a very good prediction was obtained in both cases. The most useful parameters were the skewness and FFT indices in the first case and the shape parameter α of the Weibull model along with its RMSE in the second one. In addition, topological characterization was performed on gallery-shaped biopores. Vertical deviation was the only parameter that was independent of the individual body size and showed the statistically significant lowest value for the earthworms. The experiment and analyses performed in this work to explore the connection between macroinvertebrate groups and the corresponding biopore size distributions may represent a suitable methodological approach to performing a general investigation into the relationships between soil management and its impact on the system of soil macropores.

Physical Modelling of the Slow Voltage Relaxation Phenomenon in Lithium-Ion Batteries

In the lithium-ion battery literature, discharges followed by a relaxation to equilibrium are frequently used to validate models and their parametrizations. Good agreement with experiment during discharge is possible using a pseudo-two-dimensional model such as the Doyle-Fuller-Newman (DFN) model. The relaxation portion, however, is typically not well-reproduced, with the relaxation in experiments occurring much more slowly than in models. In this study, using a model that includes a size distribution of the active material particles, we give a physical explanation for the slow relaxation phenomenon. This model, the Many-Particle-DFN (MP-DFN), is compared against discharge and relaxation data from the literature, and optimal fits of the size distribution parameters (mean and variance), as well as solid-state diffusivities, are found using numerical optimization. The voltage after relaxation is captured by careful choice of the current cutoff time, allowing a single set of physical parameters to be used for all C-rates, in contrast to previous studies. We find that the MP-DFN can accurately reproduce the slow relaxation, across a range of C-rates, whereas the DFN cannot. Size distributions allow for greater internal heterogeneities, giving a natural origin of slower relaxation timescales that may be relevant in other, as yet explained, battery behavior.