Distribution Curves Research Articles

Radial Vibration Measurement of Rotating Shaft using Constant Density Fringe Pattern and Line Scan Camera

Abstract The radial vibration signals of the rotor can provide abundant information about the health condition of the machine. In this paper, a simple vision-based measurement system is proposed to simultaneously measure two-dimensional displacements in radial directions for the rotating shaft, where the system consists of a constant density fringe pattern (CDFP), a line scan camera (LSC), and a lens. The CDFP should be installed around the surface of the rotating shaft to make the density of the fringe constant along the shaft axis, while the shaft axis is vertical to the optical axis of the LSC but not parallel to the line-array sensor of the LSC. Therefore, the density of the fringe imaged on the LSC is not constant because of the modulation of the circular surface of the shaft, and the distribution of the fringe density on the LSC is a U-shaped curve. Thus, the shaft centreline orbit can be tracked by the lowest point of the density distribution curve (DDC) of the fringe. Then, an efficient and accurate parameterized instantaneous frequency estimation method (PIFEM) is employed to estimate the DDC of the fringe, because the variable density fringe can be regarded as an amplitude-modulated and frequency-modulated nonstationary signal whose instantaneous frequency function is equivalent to the DDC. Experimental results verify the feasibility and effectiveness of the proposed method by comparing it to the eddy current sensors.

Electric Susceptibility at Partial Coverage of a Circular One-Side Access Capacitive Sensor with Rigid Polyurethane Foams

The capability of dielectric measurements was significantly increased with the development of capacitive one-side access physical sensors. Complete samples give no opportunity to study electric susceptibility at a partial coverage of the one-side access sensor’s active area; therefore, partial samples are proposed. The electric susceptibility at the partial coverage of a circular one-side access sensor with cylinders and shells is investigated for polyurethane materials. The implementation of the relative partial susceptibility permitted us to transform the calculated susceptibility data to a common scale of 0.0–1.0 and to outline the main trends for PU materials. The partial susceptibility, relative partial susceptibility, and change rate of relative partial susceptibility exhibited dependence on the coverage coefficient of the sensor’s active area. The overall character of the curves for the change rate of the relative partial susceptibility, characterised by slopes of lines and the ratio of the change rate in the centre and near the gap, corresponds with the character of the surface charge density distribution curves, calculated from mathematical models. The elaborated methods may be useful in the design and optimization of capacitive OSA sensors of other configurations of electrodes, independent of the particular technical solution.

Standard series of transmitting equipment for hydra-jet technology based on dimensionless geometric parameters development

Introduction. The work is devoted to the calculation of series standards for the design of high-pressure transmission devices used in various hydra jet technologies, which will provide the design of these devices based on dimensionless indicators describing the relationship between their geometric and technological parameters.Materials and methods. The methodology includes the use of mathematical models and analytical approaches to assess the influence of various parameters on heat generation processes in equipment, as well as methods for statistical processing of results.Results. A histogram of temperature distribution was constructed and the data was approximated using the distribution curve of temperature values and parametric series were generated for dimensionless parameters depending on various factors such as temperature, pressure, rotational speed and linear speed. It is possible to obtain parametric series for linear dimensions from five temperature ranges and seven standard sizes depending on the pressure and rotation speed of the drill shaft.Discussion and conclusions. The results obtained provide a better definition of the relationships between rotation speed, geometric characteristics and temperature parameters through the use of dimensionless indicators and it is possible to optimize the design of such devices taking into account operating conditions and ensuring increased efficiency.

Rotated Lorenz Curves of Biological Size Distributions Follow Two Performance Equations

Rotated Lorenz Curves of Biological Size Distributions Follow Two Performance Equations

Breakage Indices for Constitutive Models to Track the Evolution of Particle Crushing Under Continuous Shearing

AbstractResearchers have developed numerous breakage indices, predominantly relying on comparisons between pre- and post-test Grain Size Distribution (GSD) curves determined through conventional sieve analysis. Although these indices enable a precise estimation of particle breakage extent, a significant limitation arises when attempting to integrate them into constitutive models, especially when those models cannot consider GSD as an input. This paper addresses the need for tailored breakage indices designed to suit the specific requirements of different families of constitutive models. The new indices have been developed based on stress and strain tensor invariants or combinations thereof, ensuring the future ease of implementation into various constitutive models. The proposed equations have been validated using five different sets of experiments performed on rockfill material, calcareous, and quartz sands. The comparison between the available experimental data and the estimated degree of particle breakage using the suggested indices demonstrates their adequate performance. The novel indices can be integrated into different constitutive models, including hypoplastic, elastoplastic, and thermodynamically consistent approaches, as well as tested for their practical applicability for boundary value problems.

Phosphorescence of beta irradiated Sr4Al14O25:Eu2+,Dy3+ ─ A persistent luminescence phosphor

Phosphorescence of beta irradiated Sr4Al14O25:Eu2+,Dy3+ has been analysed. The persistent luminescence that defines this phosphor is phosphorescence hence the justification for this study. A set of phosphorescence decay curves were measured at various temperatures Tph between 20 and 352 °C following irradiation to 2 Gy. The residual thermoluminescence (R-TL) was recorded at 1 °C/s after the phosphorescence decay. A conventional TL glow curve recorded at the same rate following irradiation to 2 Gy produces two composite glow peaks P1 and P2 at 63 and 252 °C respectively. The decay curves measured between Tph = 28–60 °C and 200–240 °C associated with peaks P1 and P2 respectively give the values of the activation energy of peaks P1 and P2 as 0.59 ± 0.01 and 0.80 ± 0.04 eV. The effective frequency factors associated with the traps are 6.2 × 109 and 6.4 × 105 s−1 respectively. Peaks P1 and P2 are affected by thermal quenching with activation energy W = 0.69 ± 0.06 eV and 0.66 ± 0.03 eV respectively. The R-TL glow curves show two maxima R1 and R2 at ∼72 and 260 °C respectively. Kinetic analysis of R-TL peak R2 shows a Gaussian distribution of trap energy whereas the same analysis on R-TL peak R1 shows a non-Gaussian distribution of trap energy. The mean values of activation energy corresponding to the respective electron traps of R1 and R2 are estimated to be 0.62 ± 0.07 and 1.04 ± 0.06 eV. For peak R2, the Gaussian distribution curve shows the maximum at ∼1.06 eV which indicates that most electron traps corresponding to peak R2 have this trap depth.

Robotic-assisted free flap harvesting for diverse soft tissue reconstruction: a PRISMA scoping review of clinical outcomes over the last decade.

The aim of our study was to assess the advantages and limitations of robotic technology in diverse reconstructive procedures. A scoping review was conducted in Oct'23, on published studies from 2013 to 2023, focussing on robotic-assisted free flap harvesting. Three databases Ovid-MEDLINE, Scopus, and PubMed were searched. Original research studies reporting robotic-assisted free flap harvest were included. Studies on lesion excision, microvascular anastomosis, local flap harvest, roboticassisted flap inset, review articles, abstract-only studies, non-English documents, and animal studies were excluded from this review. Sixteen studies met the inclusion criteria out of a total of 318, searched initially. These studies included a total of 128 patients, who underwent robotic-assisted free flap harvest for the reconstruction of various defects, with 140 free flaps harvested. The most common flaps harvested by robotic technique were deep inferior epigastric artery perforator (DIEP) flap 120 (85.7%), radial forearm free (RFF) flap 11 (7.9%), latissimus dorsii flap 4 (2.9%), rectus abdominus flap 4 (2.9%), and omental flap 1 (0.7%). Breast reconstruction was the major procedure done i.e. 120 (85.7%) followed by head and neck 11 (7.9%) and limb defects 9 (6.4%) reconstruction procedures. The reported clinical outcomes were acceptable in all the studies with a 99% flap success rate and minimal complications. Variability in operating time was observed depending upon surgical steps undertaken with robotic systems. This scoping review highlights the role of robotic-assisted free flap harvesting in plastic surgery and its potential benefits on clinical outcomes, due to its high precision and minimal invasiveness. However, challenges like cost effectiveness, resource distribution and learning curve are there.

Rainfall analysis and deriving design storm for hydrological modelling of Koyna dam catchment area in Maharashtra state of India

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event.In this study, 40 years (1982–2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series.From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.

Analysis of stream flow and its impact on thermal performance in shell-side of heat exchangers based on flow dead zone

The performance of shell-and-tube heat exchanger (STHE) is primarily determined by different flow paths on the shell-side. The flow path and its impact on the shell-side flow in segmental baffle shell-and-tube heat exchanger with clearance (SC-STHE) is investigated qualitatively and quantitatively, by adopting stream classification and dead zone analysis method. By utilizing Residence Time Distribution (RTD) curves, the influence of different streams on fluid flow and heat transfer is discussed to reveal the intricate interconnections within the shell-side of SC-STHE. Then the cases with baffle-tube clearance (0.2–1.0 mm) and baffle-shell clearance (1.0–5.0 mm) ranges are studied. The study identifies that optimal comprehensive performance is achieved with a baffle-tube clearance of 0.6 mm, resulting in a 3.5 % improvement compared to a clearance of 0.2 mm. An increase of baffle-shell clearance results in a reduction in comprehensive performance by 8.23 % to 19.54 %. The interactions among stream flows and potential mechanisms are discussed by analyzing the influence of each flow path on the flow dead zone volume. It is revealed that the presence of baffle-tube and baffle-shell clearances reduces the volume fraction of flow dead zones compared to structures without clearances. A-stream and E-stream are identified as pivotal, mutually influencing B-stream and C-stream while maintaining relative independence. The result indicates that an increase in baffle-tube clearance results in a 7.60 % expansion of the volume of the dead zone within the B-stream, while in the C-stream, it decreases by 2.58 %. Conversely, an increase in baffle-shell clearance reduces the volume of the dead zone in the B-stream by 5.04 % but increases it in the C-stream by 31.95 %. The flow dead zones are mainly distributed in the B-stream and C-stream regions, and the diversion effect of leakage flows improves the fluid stagnation but also leads to a decrease in turbulence intensity and flow velocity. This study reveals the complex interaction mechanisms among the stream flows, facilitating further analysis and optimization in STHE design.

Experimental Study on the Bond-Slip Behavior of Steel Tube-Coal Gangue Concrete

This study investigated the the bond-slip behavior at the interface between steel tubes and coal gangue concrete, considering the coal gangue coarse aggregate replacement rate, the strength grade of coal gangue concrete, and the bond length as variable parameters. Eleven groups of push out tests were conducted on steel tube coal gangue concrete specimens. The the bond slip curve and the longitudinal strain distribution curve of the steel tubes were obtained, and the effects of these parameters on bond strength were analyzed. The results showed that the load-slip curves at both the loading and free ends of the specimens were similar, with slip occurring earlier at the loading end. The regularity of the test curves in repeated experiments indicated that interfacial bond stress was primarily determined by friction in the later stages. The longitudinal strain of steel tubes was approximately exponentially distributed along their length. The interfacial bond strength increased with the increase of coal gangue aggregate replacement rate and was more pronounced in specimens with higher strength coal gangue concrete. Longer bond lengths resulted in greater bond failure loads, with a lower rate of increase in higher strength coal gangue concrete specimens compared to those with lower strength. Based on the three stage bond stress-slip relationship for steel tube-concrete, a bond-slip constitutive model for steel tube-coal gangue concrete was established. This provided a reference for mechanical analysis and interface performance design of steel tube-coal gangue concrete.

A novel method for predicting coarse aggregate particle size distribution based on segment anything model and machine learning

Particle size distribution (PSD) is an important index property of granular materials. The conventional mechanical sieve analysis for PSD determination is labor-intensive, time-consuming, and inefficient. With the development of computer vision, image-based gradation prediction methods gradually emerge. However, previous studies mainly focused on images where individual aggregate particles are separated from each other without overlapping (i.e., not densely packed together), thus limiting their applicability. This study proposed a novel framework to predict the PSD of densely packed coarse aggregate particles, which is based on visual foundation model and machine learning with appropriate feature engineering. First, the segment anything model, which is one of the visual foundation models, was used for the instance segmentation of the densely packed aggregate particles. Then, the feature engineering was implemented with the segmentation result. The major quantitative indicators related to particle sizes were extracted from each mask, such as the area, the diameter of minimum enclosing circle, and the major axes of the equivalent ellipse of particle contours. Subsequently, the cumulative distribution curves of these indicators were plotted, followed by the data sampling operation on these curves to generate the feature vectors. The artificial neural network (ANN) model was then trained for gradation prediction with each of the feature vectors and the data points extracted from PSD curves used as the inputs and data labels, respectively. The model-training dataset consisted of 8160 different sets of digitally generated particle samples with known PSDs. Finally, verification test results of additional five different groups of digital particle samples and real coarse aggregate samples with known PSDs show that the root mean squared error (RMSE) of predicted aggregate sizes is 1.79 mm and 1.86 mm for digital and real aggregate particle samples, respectively. Therefore, the efficacy and feasibility of the proposed method was validated in terms of predicting the PSD of densely packed coarse aggregates from two-dimensional image information. As compared to the Mask RCNN combined with empirical formula of which the RMSE values were 5.12 mm and 5.84 mm for digital and real aggregate particle samples, respectively, the proposed framework demonstrates improved particle segmentation applicability and better PSD prediction accuracy.

Evolution of pore structure and analysis of freeze damage in granite during cyclic freeze-thaw using NMR technique

Understanding the changes in a rock's pore structure and unfrozen water content during the freeze-thaw (F-T) process is crucial for unraveling the F-T damage mechanism of rock masses. This study employs nuclear magnetic resonance (NMR) tests to resolve the pore structure characteristics of granite specimens subjected to varying numbers of F-T cycles (0, 50, 100, and 200 cycles). Throughout the F-T process, unfrozen water (comprising bound water and free water) is quantified through T2 distribution curves, and the freeze-induced strain at different subzero temperatures is investigated. The results reveal that F-T cycles lead to the expansion of pore sizes from small to large, reducing the complexity of the pore structure. Moreover, an increased proportion of meso- and macro-pores accelerates the rate of water-ice phase transition in granite specimens, resulting in intensified freeze damage and greater maximum freeze-induced strain. Additionally, when previously damaged granite is refrozen, the presence of free water induces higher levels of freeze-induced strain. This research comprehensively analyzes the F-T damage process in granite, laying a crucial theoretical foundation for understanding freeze damage mechanisms in rock engineering.

Novel Tools for Single Comparative and Unified Evaluation of Qualitative and Quantitative Bioassays: SS/PV-ROC and SS-J/PV-PSI Index-ROC Curves with Integrated Concentration Distributions, and SS-J/PV-PSI Index Cut-Off Diagrams.

Background: This investigation is both a study of potential non-invasive diagnostic approaches for the bladder cancer biomarker UBC® Rapid test and a study including novel comparative methods for bioassay evaluation and comparison that uses bladder cancer as a useful example. The objective of the paper is not to investigate specific data. It is used only for demonstration, partially to compare ROC methodologies and also to show how both sensitivity/specificity and predictive values can be used in clinical diagnostics and decision making. This study includes ROC curves with integrated cut-off distribution curves for a comparison of sensitivity/specificity (SS) and positive/negative predictive values (PPV/NPV or PV), as well as SS-J index/PV-PSI index-ROC curves and SS-J/PV-PSI index cut-off diagrams (J = Youden, PSI = Predictive Summary Index) for the unified direct comparison of SS-J/PV results achieved via quantitative and/or qualitative bioassays and an identification of optimal separate or unified index cut-off points. Patients and Methods: According to the routine diagnostics, there were 91 patients with confirmed bladder cancer and 1152 patients with no evidence of bladder cancer, leading to a prevalence value of 0.073. This study performed a quantitative investigation of used-up test cassettes from the visual UBC® Rapid qualitative point-of-care assay, which had already been applied in routine diagnostics. Using a photometric reader, quantitative data could also be obtained from the test line of the used cassettes. Interrelations between SS and PV values were evaluated using cumulative distribution analysis (CAD), SS/PV-ROC curves, SS-J/PV-PSI index-ROC curves, and the SS-J/PV-PSI index cut-off diagram. The maximum unified SS-J/PV-PSI index value and its corresponding cut-off value were determined and calculated with the SS-J/PV-PSI index cut-off diagram. Results: The use of SS/PV-ROC curves with integrated cut-off concentration distribution curves provides improved diagnostic information compared to "traditional" ROC curves. The threshold distributions integrated as curves into SS/PV-ROC curves and SS-J/PV-PSI index-ROC curves run in opposite directions. In contrast to the SS-ROC curves, the PV-ROC and the novel PV-PSI index-ROC curves had neither an area under the curve (AUC) nor a range from 0% to 100%. The cut-off level of the qualitative assay was 7.5 µg/L, with a sensitivity of 65.9% and a specificity of 63.3%, and the PPV was 12.4% and the NPV was 95.9%, at a threshold value of 12.5 µg/L. Based on these set concentrations, the reader-based evaluation revealed a graphically estimated 5% increase in sensitivity and a 13% increase in specificity, as compared to the visual qualitative POC test. In the case of predictive values, there was a gain of 8% for PPV and 10% for NPV. The index values and cut-offs were as follows: visual SS-J index, 0.328 and 35 µg/L; visual PV-PSI index, 0.083 and 5.4 µg/L; maximal reader Youden index, 0.0558 and 250 µg/L; and maximal PV-PSI index, 0.459 and 250 µg/L, respectively. The maximum unified SS-J/PV-PSI index value was 0.32, and the cut-off was 43 µg/L. The reciprocal SS-J index correctly detected one out of three patients, while the reciprocal PV-PSI index gave one out of twelve patients a correct diagnosis. Conclusions: ROC curves including cut-off distribution curves supplement the information lost in "traditionally plotted" ROC curves. The novel sets of ROC and index-ROC curves and the new SS/PV index cut-off diagrams enable the simultaneous comparison of sensitivity/specificity and predictive value profiles of diagnostic tools and the identification of optimal cut-off values at maximal index values, even in a unifying SS/PV approach. Because the curves within an SS-J/PV-PSI index cut-off diagram are distributed over the complete cut-off range of a quantitative assay, this field is open for special clinical considerations, with the need to vary the mentioned clinical diagnostic parameters. Complete or partial areas over the x-axis (AOX) can be calculated for summarized quantitative or qualitative effectivity evaluations with respect to single and/or unified SS-J and PV-PSI indices and with respect to single, several, or several unified assays. The SS-J/PV-PSI index-AOX approach is a new tool providing additional joint clinical information, and the reciprocal SS-J indices can predict the number of patients with a correct diagnosis and the number of persons who need to be examined in order to correctly predict a diagnosis of the disease. These methods could be used in applications like medical or plant epidemiology, machine learning algorithms, and neural networks.

Exploration of Fragmentation Mechanisms of Yellow Split Peas during Grinding Using a Multimodal Approach

In the context of food and agro-ecological transitions, the development of food applications based on legume flours and plant proteins requires a mastery of grain milling. While wheat grain milling has been extensively studied and is well-mastered, legume grinding and its underlying mechanisms are still poorly understood. The aim of this work is to contribute to the study of the fragmentation mechanisms of pea grains during grinding. Experiments were carried out on hulled yellow pea grains (Kameleon variety) ground under different conditions using a ball mill (MM400, Retsch®, Haan, Germany) or a micro-cylinder mill. The results showed that the grinding of pea grains, regardless of the type of mill, produced powders characterized by particle size distribution curves with a multimodal shape. The curve analysis was performed according to a simplified deconvolution approach, taking into account different particle populations without diameter overlap. Four particle populations of different sizes were identified and correlated with specific mechanisms governing the grinding of yellow split peas. The physical and biochemical properties of the resulting powders were determined. Taking into account the proportions of the four populations within the powders, the results showed a positive correlation between the volume proportions of very fine (0–10 µm) and fine (10–55 µm) particles within the powders and the starch damage rate and the specific surface area developed, irrespective of the type of mill.

Synthesis, investigation of temperature and salt resistant polyacrylamide microspheres used for deep sealing and profile control and function strengthening mechanism

AbstractBased on the requirements of deep sealing and profile control for the excellent temperature and salt resistance on polyacrylamide microspheres, the Poly‐AM/AMPS was prepared depends on aqueous solution polymerization method to improving oil and gas recovery efficiency in low‐permeability and heterogeneous reservoirs resulted by water channeling. The key technical parameters were established through single‐factor experimental methods, and the chemical structure was studied by infrared spectrum analysis (FTIR), energy spectrum analysis, and x‐ray diffraction analysis, and then the thermal stability was investigated depends on the thermogravimetric (TG) and differential thermogravimetric (DTG) distribution curves, moreover, the particle size and distribution, microstructure, and surface morphology were further studied. As a result, the results confirmed that the molecular structure of Poly‐AM/AMPS meets the expected design, and the quality retention rate at 800°C is 17.4%, the median particle size of Poly‐AM/AMPS particles is 35.88 μm, and the particle size distribution range is about 1.94–497.8 μm. Further, the Poly‐AM/AMPS was modified by maleic anhydride, sodium styrenesulfonate, and dimethyl diallyl ammonium chloride through conventional functional strengthening and modification, modified by nano‐SiO2, GO, and S‐CaCO3 through nano‐functional strengthening and modification. Additionally, the functional strengthening and modification mechanism was studied depends on the FTIR, TG, and DTG methods.

Enhancing parameter calibration for micro-simulation models: Investigating improvement methods

Calibrating microscopic traffic simulation models is a prerequisite for simulation applications. This study proposes three novel methods to improve the accuracy and interpretability of the calibration model. The proposed approach involves selecting the calibration parameter, refining the model parameter system, and optimizing the calibration results. The first method expands the single-point mean into a multi-point distribution. The cumulative distribution curve of delay was selected as the calibration parameter. The second method divides the parameter system into global and local parameters. Global parameters were calibrated using NGSIM measured data, and local parameters were calibrated through intelligent algorithms. The third method proposes a methodology of parameter clustering recursion based on the genetic algorithm results, with information entropy selected as the analysis index. To evaluate the effectiveness of the proposed optimization methods, this study used NGSIM trajectory data as a case study. Eight simulation schemes based on the three optimization methods were designed, and simulation experiments were conducted using the VISSIM platform. The results show that the accuracy of the multi-point distribution calibration and parameter value optimization method is significantly higher than the default method. Additionally, the optimization method with calibration of both global and local parameters was more consistent with actual driving characteristics. This study provides a theoretical foundation for improving the practical application of traffic simulation technology, which has significant implications for transportation planning and management.

NMR-based pore water distribution characteristics of silty clay during the soil compaction, saturation, and drying processes

The pore water distribution (PWD) of soil provides key information about soil shear strength, hydraulic conductivity, and water-retention ability. The PWD characteristics of the soil depend on the specimen preparation conditions (i.e., the variations in initial water content or compaction degree) and drying-wetting processes, which were investigated by using the nuclear magnetic resonance (NMR) technique. The NMR T2 spectrum is mathematically transformed into the PWD curve to more accurately quantify the variations in pore water content stored with pores of different radii. The pore water in silty clay can be categorized into strongly bound water, intra-aggregate pore water, and inter-aggregate pore water, which are identified by the pore radius of <0.05 μm, 0.05-1.0 μm and >1.0 μm, respectively. The effects of compaction degree and initial water content on the PWD of the soil exhibit distinctions. For unsaturated compacted specimens, the PWDs remain unaffected by changes in compaction degree, while an increase in initial water content promotes the formation of clay aggregates, thereby increasing the maximum water-holding pore radius and the intra-aggregate pore water content. For saturated compacted specimens, the inter-aggregate and intra-aggregate pore water content increases with a decrease in the compaction degree, while the changes in the PWD shape from unimodal to bimodal with an increase in the initial water content. During the soil drying process, inter-aggregate pore water is rapidly drained, the intra-aggregate dominant pore water content increases first and then decreases, and the strongly bound water content remains constant. The relationship between the cumulative pore water distribution curve and the soil-water characteristic curve (SWCC) can be established through the Young-Laplace theory. The SWCC can be well predicted by using the envelope of the cumulative pore water distribution curves during soil drying.

An Electrochemical-Thermal Coupling Model Based on Two-Factor Parameter Modification for Lithium-Ion Battery

Abstract The accurate establishment of battery model can improve the design reliability and reduce the design risk, which provides an important basis for the research of battery. First, the key parameters of the Li-ion battery model are identified by the least square method based on the full-battery equivalent circuit model of the single-particle impedance spectrum, and the diffusion coefficient and exchange current density under different temperatures and SOC conditions are calculated. At the same time, the one-dimensional thermal rate model is used as the heat source of the three-dimensional model, and the mean temperature T of the three-dimensional model is calculated by using Fourier's law, and T is fed back to the one-dimensional model as the key parameter to modify the conductivity, diffusion coefficient, and exchange current density, and a semi-empirical electrochemical-thermal coupling model with two-factor parameter modification is established. Finally, the model is verified by the temperature field distribution and discharge voltage curve at different discharge rates. The maximum temperature difference is less than 3.1 °C, and the maximum voltage difference error is less than 0.131 V. The results show that the improved model can accurately reflect the influence of temperature on the model parameters, and has high accuracy in the estimation of battery terminal voltage and SOC.

Estimating the costs of managed aquifer recharge under uncertainty with examples for town water supply in regional Australia

HighlightsCost distribution curves for well injection and infiltration basin recharge schemes.Probabilistic, time-varying, coupled water balance and net present value modelling.Disaggregated capital and operating expenses and global sensitivity analyses.Examples for increasing regional area town water security in Australia’s Murray Darling Basin.

Joint EURADOS-EANM initiative for an advanced computational framework for the assessment of external dose rates from nuclear medicine patients

Abstract Background In order to ensure adequate radiation protection of critical groups such as staff, caregivers and the general public coming into proximity of nuclear medicine (NM) patients, it is necessary to consider the impact of the radiation emitted by the patients during their stay at the hospital or after leaving the hospital. Current risk assessments are based on ambient dose rate measurements in a single position at a specified distance from the patient and carried out at several time points after administration of the radiopharmaceutical to estimate the whole-body retention. The limitations of such an approach are addressed in this study by developing and validating a more advanced computational dosimetry approach using Monte Carlo (MC) simulations in combination with flexible and realistic computational phantoms and time activity distribution curves from reference biokinetic models. Results Measurements of the ambient dose rate equivalent Ḣ*(10) at 1 m from the NM patient have been successfully compared against MC simulations with 5 different codes using the ICRP adult reference computational voxel phantoms, for typical clinical procedures with 99mTc-HDP/MDP, 18FDG and Na131I. All measurement data fall in the 95% confidence intervals, determined for the average simulated results. Moreover, the different MC codes (MCNP-X, PHITS, GATE, GEANT4, TRIPOLI-4®) have been compared for a more realistic scenario where the effective dose rate Ė of an exposed individual was determined in positions facing and aside the patient model at 30 cm, 50 cm and 100 cm. The variation between codes was lower than 8% for all the radiopharmaceuticals at 1 m, and varied from 5 to 16% for the face-to face and side-by-side configuration at 30 cm and 50 cm. A sensitivity study on the influence of patient model morphology demonstrated that the relative standard deviation of Ḣ*(10) at 1 m for the range of included patient models remained under 16% for time points up to 120 min post administration. Conclusions The validated computational approach will be further used for the evaluation of effective dose rates per unit administered activity for a variety of close-contact configurations and a range of radiopharmaceuticals as part of risk assessment studies. Together with the choice of appropriate dose constraints this would facilitate the setting of release criteria and patient restrictions.