Fitted Parameter Values Research Articles

Estimation of filling time for compressed hydrogen refueling

In order to facilitate the application of hydrogen energy and ensure its safety, the compressed hydrogen storage tank on board needs to be full of hydrogen gas within 3 minutes. Therefore, to meet this requirement, the effects of refueling parameters on the filling time need to be investigated urgently. For the purpose of solving this issue, a novel analytical solution of filling time is obtained from a lumped parameter model in this paper. According to the equation of state for real gas and dimensionless numbers Nu and Re, the function relationships between the filling time and the refueling parameters are presented. These parameters include initial temperature, initial pressure, inflow temperature, final temperature and final pressure. These equations are used to fit the reference data, the results of fitting show good agreement. Then, the values of fitting parameters are further utilized so as to verify the validity of these formulas. We believe this study can contribute to control the hydrogen filling time and ensure the safety during fast filling process.

Temperature dependence of mobility of conducting polymer polyaniline with secondary dopant

The conductivity σ and carrier density n of the conducting polymer polyaniline were investigated by changing the concentration x of a secondary dopant, meta-cresol. We found that σ changes by four orders of magnitude within the x-range of 1–10%, while n, as estimated from the Hall measurements, shows a weak dependence on x in the region of 2% < x < 50%. These results suggest that σ can be enhanced by the change in the mobility μ. We analyzed the temperature dependence of μ by not only the combination of two different types of scattering mechanism, but also by the polaron hopping model. The experimental data of μ(T) can be explained well by the latter model with reasonable fitting parameter values of a small-polaron binding energy and a longitudinal optical phonon frequency.

Universality of the halo mass function in screened gravity theories

We investigate the efficacy of the halo mass function (HMF) as a probe of f(ℛ), symmetron and Dvali-Gabadadze-Porrati (DGP) gravity. In this regard, we develop an excursion-set method to generalise a range of popular HMF fitting functions from General Relativity (GR) to screened Modified Gravity (MG), considering the HMF dependence on the critical density parameter δc. In particular, we propose a variety of new methods to account for the environmental dependence of chameleon screening and compare their accuracy to existing ones by submitting them to N-body simulation acid tests. Using the nested sampling routine MultiNest, we then examine two propositions: can the MG N-body results be accurately described by a ΛCDM GR HMF, and do MG HMFs display universality. More specifically, the values of the free parameters defining a given HMF can always be determined by fitting N-body simulation data, but the question arises as to the dependency of these values on cosmological parameters and halo finding algorithm in the GR case, and indeed on the gravitational force itself when considering MG theories. We find that haloes extracted from any one of the MG N-body simulations can plausibly be fit by a ΛCDM GR HMF, albeit with unusual best fit parameter values. In other words, despite the MG N-body data failing to support a clear deviation in the functional form of the HMF, it indicates that one needs to carefully establish ΛCDM-expected credible regions for the values of the best fit parameters before attributing any difference in these values to MG. Alternatively, one can ask whether the MG N-body data is compatible with the existence of a truly universal (as in completely independent of the gravity model) HMF. Although we find that some HMFs display more universality than others—in the sense that they exhibit better overlap of their best fit parameters posterior probability distribution functions (PDFs) for different screening models –, the general trend, regardless of the HMF considered, is for DGP HMF parameter PDFs to overlap with those of ΛCDM, symmetron HMF parameter PDFs to overlap with those of |fℛ0|=10−6, and |fℛ0|=10−5 HMF parameter PDFs to remain somewhat distinct from all the others. These results strongly suggest that a truly universal HMF will remain elusive.

Is the Menzerath-Altmann Law Specific to Certain Languages in Certain Registers?

ABSTRACT Since its formulation, the Menzerath-Altmann law (MAL) has gone through continuing validation and development when applied to different languages or different language units. However, whether the MAL still holds true irrespective of spoken or written register remains a controversial issue. This article endeavours to re-examine the MAL by investigating the correlation between the length of English sentences (measured in the number of clauses) and their constituting clause length (measured in the number of words) in both academic spoken and written registers. It is observed that the MAL is valid in both registers. Further, the fitted parameter values of the MAL can serve as good predictors for register differentiation.

Microfluidics to determine the diffusive mass transfer of a low viscosity solvent into a high viscosity hydrocarbon

In this work, a microfluidic platform along with X-ray computerized tomography were employed to analyze diffusive mass transfer of a low viscosity solvent (hexane) into a high viscosity hydrocarbon (bitumen). T-shaped microfluidic channels were fabricated to measure the diffusion coefficient in significantly shorter times and lower sample volume compared with traditional methods. Semitransparent nature of bitumen facilitates the application of light transmission imaging during the time and relating intensities to solvent concentration. Diffusion mass transfer was studied with respect to Fickian and Single-File mass transfer mechanisms and corresponding equation was applied to calculate both constant and concentration dependent diffusion coefficients. The accuracy of Fickian mass transfer mechanism was confirmed with calculating values of fitting parameter (i.e. nw) in addition to superimposition of data for both techniques. The optimum values of constant diffusion coefficient for T-shaped microchannel and X-ray technique were 2 × 10−10 and 1.8 × 10−10 m2·s−1, respectively. Concentration dependent diffusion coefficients ranged from 1 × 10−12 to 3.6 × 10−10 m2·s−1 for the experiments that reveal constant mutual diffusion coefficient assumption can result in significantly high errors particularly at low and high solvent mass fractions.

Parametric Modeling of Electrocardiograms using Particle Swarm optimization.

The electrocardiogram (ECG) is commonly used to monitor or diagnose adverse heart conditions. While general ECG recordings are widely available, parametric ECG models have been proposed to generate ECG-like signals. Such ECG generators can create extended segments of specific beat morphology or cardiac rhythm, especially in disease states, which can be used to validate cardiac devices or evaluate ECG processing algorithms. Furthermore, ifthe parameters can be fit to a variety of ECGs, these models are valuable tools in ECG compression and modeling. In this paper we propose a framework to fit parameter values of an ECG generator such that the generated signal is similar to a reference signal. We first design a parametric ECG generator with relatively minimal assumptions of single beat waveform morphology. We then use Particle Swarm optimization to find ideal values for parameters of our ECG generator which minimize the percent root mean square difference (PRD) between the reference and generated signals. We were able to capture waveform morphologies of normal, idioventricular, and ventricular flutter rhythms with Pearson correlation coefficients above 0.9 between generated and pre-recorded signals from the MIT-BIH database.

Effects of Input Data Content on the Uncertainty of Simulating Water Resources

The widely used, partly-deterministic Soil and Water Assessment Tool (SWAT) requires a large amount of spatial input data, such as a digital elevation model (DEM), land use, and soil maps. Modelers make an effort to apply the most specific data possible for the study area to reflect the heterogeneous characteristics of landscapes. Regional data, especially with fine resolution, is often preferred. However, such data is not always available and can be computationally demanding. Despite being coarser, global data are usually free and available to the public. Previous studies revealed the importance for single investigations of different input maps. However, it remains unknown whether higher-resolution data can lead to reliable results. This study investigates how global and regional input datasets affect parameter uncertainty when estimating river discharges. We analyze eight different setups for the SWAT model for a catchment in Luxembourg, combining different land-use, elevation, and soil input data. The Metropolis–Hasting Markov Chain Monte Carlo (MCMC) algorithm is used to infer posterior model parameter uncertainty. We conclude that our higher resolved DEM improves the general model performance in reproducing low flows by 10%. The less detailed soil-map improved the fit of low flows by 25%. In addition, more detailed land-use maps reduce the bias of the model discharge simulations by 50%. Also, despite presenting similar parameter uncertainty (P-factor ranging from 0.34 to 0.41 and R-factor from 0.41 to 0.45) for all setups, the results show a disparate parameter posterior distribution. This indicates that no assessment of all sources of uncertainty simultaneously is compensated by the fitted parameter values. We conclude that our result can give some guidance for future SWAT applications in the selection of the degree of detail for input data.

Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro.

PurposeThe aim of this study was to develop a statistical model for cell death by irreversible electroporation (IRE) and to show that the statistic model is more accurate than the electric field threshold model in the literature using cervical cancer cells in vitro.MethodsHeLa cell line was cultured and treated with different IRE protocols in order to obtain data for modeling the statistical relationship between the cell death and pulse-setting parameters. In total, 340 in vitro experiments were performed with a commercial IRE pulse system, including a pulse generator and an electric cuvette. Trypan blue staining technique was used to evaluate cell death after 4 hours of incubation following IRE treatment. Peleg-Fermi model was used in the study to build the statistical relationship using the cell viability data obtained from the in vitro experiments. A finite element model of IRE for the electric field distribution was also built. Comparison of ablation zones between the statistical model and electric threshold model (drawn from the finite element model) was used to show the accuracy of the proposed statistical model in the description of the ablation zone and its applicability in different pulse-setting parameters.ResultsThe statistical models describing the relationships between HeLa cell death and pulse length and the number of pulses, respectively, were built. The values of the curve fitting parameters were obtained using the Peleg-Fermi model for the treatment of cervical cancer with IRE. The difference in the ablation zone between the statistical model and the electric threshold model was also illustrated to show the accuracy of the proposed statistical model in the representation of ablation zone in IRE.ConclusionsThis study concluded that: (1) the proposed statistical model accurately described the ablation zone of IRE with cervical cancer cells, and was more accurate compared with the electric field model; (2) the proposed statistical model was able to estimate the value of electric field threshold for the computer simulation of IRE in the treatment of cervical cancer; and (3) the proposed statistical model was able to express the change in ablation zone with the change in pulse-setting parameters.

Mechanistic equivalent circuit modelling of a commercial polymer electrolyte membrane fuel cell

Electrochemical impedance spectroscopy (EIS) has been widely used in the fuel cell field since it allows deconvolving the different physic-chemical processes that affect the fuel cell performance. Typically, EIS spectra are modelled using electric equivalent circuits. In this work, EIS spectra of an individual cell of a commercial PEM fuel cell stack were obtained experimentally. The goal was to obtain a mechanistic electric equivalent circuit in order to model the experimental EIS spectra. A mechanistic electric equivalent circuit is a semiempirical modelling technique which is based on obtaining an equivalent circuit that does not only correctly fit the experimental spectra, but which elements have a mechanistic physical meaning. In order to obtain the aforementioned electric equivalent circuit, 12 different models with defined physical meanings were proposed. These equivalent circuits were fitted to the obtained EIS spectra. A 2 step selection process was performed. In the first step, a group of 4 circuits were preselected out of the initial list of 12, based on general fitting indicators as the determination coefficient and the fitted parameter uncertainty. In the second step, one of the 4 preselected circuits was selected on account of the consistency of the fitted parameter values with the physical meaning of each parameter.

Direct parameter estimation for generalised balanced power diagrams

ABSTRACTThe statistical characterisation and synthetic reproduction of a polycrystalline material's microstructure is assisted by mathematically representing its morphology by a tessellation model. The generalised balanced power diagram (GBPD) is a tessellation model that was shown in previous studies to accurately reproduce the microstructure morphology of various materials by closely matching micrographs obtained through electron microscopy. These studies employed costly optimisation procedures to determine the best-fit model parameters, limiting the scalability of the model. In this work, it is shown that setting the tessellation cell parameters to values such that the shape moments of the corresponding grains are matched results in a quality of fit that is commensurate with optimisation procedures. This fitting approach decouples the interaction among grains when fitting the tessellation parameters and, most notably, provides analytical, closed-form expressions for all the model parameters. The performance of this parameter fitting approach is demonstrated on multiple micrographs of various materials, and it compares similarly to the performance of optimisation procedures reported in recently published literature. As the fitted parameter values are obtained through trivial computations, this approach enables extensive scalability of the GBPD model such that it can be used to represent extremely large characterisation data sets.

A state-space approach to analyze structural uncertainty in physical models

Physics-based computer models, such as fluid flow simulations, seek to approximate the behavior of a real system based on the physical equations that govern the evolution of that system. The model approximation of reality, however, is imperfect because it is subject to uncertainties coming from different sources: finite model resolution, uncertainty in model parameter values, uncertainty in input data such as external forgings, and uncertainty in the structure of the model itself. Many studies to date have considered the effects of parameter and data uncertainty on model outputs, and have offered solutions to obtain the best fitted parameter values for a model. However, much less effort has been devoted to the study of structural uncertainty, which is caused by our incomplete knowledge about the true physical processes, and manifests itself as missing dynamics in the model. This paper seeks to understand structural uncertainty by studying the observable errors, i.e. the discrepancies between the model solutions and measurements of the physical system. The dynamics of these errors is modeled using a state-space approach, which enables one to identify the source of uncertainty and to recognize the missing dynamics inside model. Furthermore, the model solution can be improved by correcting it with the error predicted by the state-space approach. The proposed methodology is applied to two test problems, Lorenz-96 and a stratospheric chemistry model.

Estimation of Open Channel Flow Parameters by Using Genetic Algorithm

The present study involves estimation of open channel flow parameters having different bed materials invoking data of Gradual Varied Flow (GVF). Use of GVF data facilitates estimation of flow parameters. The necessary data base was generated by conducting laboratory. In the present study, the efficacy of the Genetic Algorithm (GA) optimization technique is assessed in estimation of open channel flow parameters from the collected experimental data. Computer codes are developed to obtain optimal flow parameters Optimization Technique. Applicability, adequacy and robustness of the developed code are tested using sets of theoretical data generated by experimental work. A simulation model was developed to compute GVF depths at preselected discrete sections for given downstream head and discharge rate. This model is linked to an optimizer to estimate optimal value of decision variables. The proposed model is employed to a set of laboratory data for three bed materials. Application of proposed model reveals that optimal value of fitting parameter ranges from 1.42 to 1.48 as the material gets finer and optimal decision variable ranges from 0.015 to 0.024. The optimal estimates of Manning’s n of three different bed conditions of experimental channel appear to be higher than the corresponding reported/Strickler’s estimates.

Predicting the NHL playoffs with PageRank

AbstractApplying Google’s PageRank model to sports is a popular concept in contemporary sports ranking. However, there is limited evidence that rankings generated with PageRank models do well at predicting the winners of playoffs series. In this paper, we use a PageRank model to predict the outcomes of the 2008–2016 NHL playoffs. Unlike previous studies that use a uniform personalization vector, we incorporate Corsi statistics into a personalization vector, use a nine-fold cross validation to identify tuning parameters, and evaluate the prediction accuracy of the tuned model. We found our ratings had a 70% accuracy for predicting the outcome of playoff series, outperforming the Colley, Massey, Bradley-Terry, Maher, and Generalized Markov models by 5%. The implication of our results is that fitting parameter values and adding a personalization vector can lead to improved performance when using PageRank models.

Long-term resilient behaviour of thawed saturated silty clay under repeated cyclic loading: experimental evidence and evolution model

In seasonally frozen regions, subgrade soils are not only being subjected to large numbers of repeated cyclic loading at a stress level lower than shear strength, but also suffer from the effect of freeze–thaw cycles, which could make the long-term resilient behaviours of subgrade soils as important as the short-term resilient behaviours determined by standard test procedures. In this study, three series of undrained cyclic tri-axial tests were performed to investigate the evolution of the resilient modulus for thawed saturated silty clay during the long-term repeated cyclic loading. Effects of the freeze–thaw cycles, cyclic stress amplitude, confining pressure and loading frequency were considered. Based on the experimental evidences, it was found that the normalised resilient modulus decreases with an increase in the number of freeze–thaw cycles, cyclic stress amplitude and number of loading cycles, respectively, but increases with an increase in confining pressure and increasing loading frequency. An evolution model, which considers the effects of these five influencing factors together with the values of fitting parameters, was established and validated. The proposed model can be used for predicting the evolution of resilient modulus for thawed saturated subgrade clays under the long-term repeated traffic loading, and assist in evaluating the long-term deformation of pavement in seasonally frozen regions.

Constraints on spatially oscillating sub-mm forces from the Stanford Optically Levitated Microsphere Experiment data

A recent analysis by one of the authors\cite{Perivolaropoulos:2016ucs} has indicated the presence of a $2\sigma$ signal of spatially oscillating new force residuals in the torsion balance data of the Washington experiment. We extend that study and analyse the data of the Stanford Optically Levitated Microsphere Experiment (SOLME) \cite{Rider:2016xaq} (kindly provided by the authors of \cite{Rider:2016xaq}) searching for sub-mm spatially oscillating new force signals. We find a statistically significant oscillating signal for a force residual of the form $F(z)=\alpha \; cos(\frac{2\pi}{\lambda}\; z +c)$ where $z$ is the distance between the macroscopic interacting masses (levitated microsphere and cantilever). The best fit parameter values are $\alpha=(1.1 \pm 0.4)\times 10^{-17}N$, $\lambda=(35.2\pm 0.6)\mu m$. Monte Carlo simulation of the SOLME data under the assumption of zero force residuals has indicated that the statistical significance of this signal is at about $2\sigma$ level. Private communication with members of the SOLME group has indicated that this previously unnoticed signal is most probably due to a systematic effect (diffraction of non-Gaussian tails of the laser beam). Thus it can only be useful as an upper bound of the amplitude of new spatially oscillating forces on sub-mm scales. Assuming gravitational origin emerging from a fundamental modification of the Newtonian potential of the form $V_{eff}(r)=-G\frac{M}{r}(1+\alpha_O \cos(\frac{2\pi}{\lambda}\; r+\theta))\equiv V_{N}(r)+V_{osc}(r)$, we evaluate the source integral and obtain a bound $\alpha_O < 10^7$ for $\lambda \simeq 35 \mu m$. Thus, we get no useful constraints on the modified gravity parameter $\alpha_O$. However, the constraints on the general phenomenological parameter $\alpha$ can be useful in constraining other fifth force models related to dark energy (chameleon oscillating potentials etc).

Experimental Investigation of Hysteretic Dynamic Capillarity Effect in Unsaturated Flow.

The difference between average pressures of two immiscible fluids is commonly assumed to be the same as macroscopic capillary pressure, which is considered to be a function of saturation only. However, under transient conditions, a dependence of this pressure difference on the time rate of saturation change has been observed by many researchers. This is commonly referred to as dynamic capillarity effect. As a first‐order approximation, the dynamic term is assumed to be linearly dependent on the time rate of change of saturation, through a material coefficient denoted by τ. In this study, a series of laboratory experiments were carried out to quantify the dynamic capillarity effect in an unsaturated sandy soil. Primary, main, and scanning drainage experiments, under both static and dynamic conditions, were performed on a sandy soil in a small cell. The value of the dynamic capillarity coefficient τ was calculated from the air‐water pressure differences and average saturation values during static and dynamic drainage experiments. We found a dependence of τ on saturation, which showed a similar trend for all drainage conditions. However, at any given saturation, the value of τ for primary drainage was larger than the value for main drainage and that was in turn larger than the value for scanning drainage. Each data set was fit a simple log‐linear equation, with different values of fitting parameters. This nonuniqueness of the relationship between τ and saturation and possible causes is discussed.

Analysis of pp and p̄p elastic scatterings based on theoretical bounds in high-energy physics: An update

In a previous work a novel parametrization was proposed for the [Formula: see text] and [Formula: see text] total cross-sections. Here, results are presented for the updated analysis with taking into account the recent data from accelerator experiments as well as from cosmic ray measurements. The analytic parametrizations suggested within axiomatic quantum field theory (AQFT) provide the quantitative description of energy dependence of global scattering observables with robust values of fit parameters. Based on the fit results the estimations are derived for the total cross-section and the [Formula: see text] parameter in elastic [Formula: see text] scattering at various [Formula: see text] up to energy frontier [Formula: see text] PeV which can be useful for present and future hadron colliders as well as for cosmic ray measurements at ultra-high energies.

A new approach to the analysis of thermoluminescence glow-curve of TLD-600 dosimeters following Am-241 alpha particles irradiation.

A new approach to the analysis of thermoluminescence (TL) glow-curves of LiF:Mg, Ti (TLD-600) following alpha particles irradiation has been presented using general expressions derived from the one-trap-one recombination (OTOR)-level model. It has been found that the results of the deconvolution in the case of using these expressions are different from the case of using the other TL expressions, especially for the high-temperature region. The advantage of using the OTOR expressions is that, unlike the usual analysis, a good fit and reasonable kinetic parameter values could be obtained with a lower number of deconvoluted peaks. The kinetic parameters and the dosimetric properties of each peak have been investigated over different absorbed doses and new findings have been found. Improvement of the accuracy and the precision of the dose measurements at low-dose levels has been achieved using the glow-curve deconvolution algorithm. In addition, theoretical interpretations of some observed behaviors have been presented using the interactive multiple trap system model.

18 F-fluoromisonidazole uptake in advanced stage non-small cell lung cancer: A voxel-by-voxel PET kinetics study.

PurposeThe aim of this study was to determine the relative abilities of compartment models to describe time‐courses of 18F‐fluoromisonidazole (FMISO) uptake in tumor voxels of patients with non‐small cell lung cancer (NSCLC) imaged using dynamic positron emission tomography. Also to use fits of the best‐performing model to investigate changes in fitted rate‐constants with distance from the tumor edge.MethodsReversible and irreversible two‐ and three‐tissue compartment models were fitted to 24 662 individual voxel time activity curves (TACs) obtained from tumors in nine patients, each imaged twice. Descriptions of the TACs provided by the models were compared using the Akaike and Bayesian information criteria (AIC and BIC).Two different models (two‐ and three‐tissue) were fitted to 30 measured voxel TACs to provide ground‐truth TACs for a statistical simulation study. Appropriately scaled noise was added to each of the resulting ground‐truth TACs, generating 1000 simulated noisy TACs for each ground‐truth TAC. The simulation study was carried out to provide estimates of the accuracy and precision with which parameter values are determined, the estimates being obtained for both assumptions about the ground‐truth kinetics.A BIC clustering technique was used to group the fitted rate‐constants, taking into consideration the underlying uncertainties on the fitted rate‐constants. Voxels were also categorized according to their distance from the tumor edge.ResultsFor uptake time‐courses of individual voxels an irreversible two‐tissue compartment model was found to be most precise. The simulation study indicated that this model had a one standard deviation precision of 39% for tumor fractional blood volumes and 37% for the FMISO binding rate‐constant.Weighted means of fitted FMISO binding rate‐constants of voxels in all tumors rose significantly with increasing distance from the tumor edge, whereas fitted fractional blood volumes fell significantly. When grouped using the BIC clustering, many centrally located voxels had high‐fitted FMISO binding rate‐constants and low rate‐constants for tracer flow between the vasculature and tumor, both indicative of hypoxia. Nevertheless, many of these voxels had tumor‐to‐blood (TBR) values lower than the 1.4 level commonly expected for hypoxic tissues, possibly due to the low rate‐constants for tracer flow between the vasculature and tumor cells in these voxels.ConclusionsTime‐courses of FMISO uptake in NSCLC tumor voxels are best analyzed using an irreversible two‐tissue compartment model, fits of which provide more precise parameter values than those of a three‐tissue model. Changes in fitted model parameter values indicate that levels of hypoxia rise with increasing distance from tumor edges.The average FMISO binding rate‐constant is higher for voxels in tumor centers than in the next tumor layer out, but the average value of the more simplistic TBR metric is lower in tumor centers. For both metrics, higher values might be considered indicative of hypoxia, and the mismatch in this case is likely to be due to poor perfusion at the tumor center. Kinetics analysis of dynamic PET images may therefore provide more accurate measures of the hypoxic status of such regions than the simpler TBR metric, a hypothesis we are presently exploring in a study of tumor imaging versus histopathology.

Improving the estimation of complete field soil water characteristic curves through field monitoring data

In this work, Soil Water Characteristic Curves (SWCCs) were reconstructed through simultaneous field measurements of soil pore water pressure and water content. The objective was to evaluate whether field-based monitoring can allow for the improvement of the accuracy in SWCCs estimation with respect to the use of laboratory techniques. Moreover, field assessment of SWCCs allowed to: a) quantify the hydrological hysteresis affecting SWCCs through field data; b) analyze the effect of different temporal resolution of field measures; c) highlight the differences in SWCCs reconstructed for a particular soil during different hydrological years; d) evaluate the reliability of field reconstructed SWCCs, by the comparison between assessed and measured trends of a component of the soil water balance. These aspects were fundamental for assessing the reliability of the field reconstructed SWCCs. Field data at two Italian test-sites were measured. These test-sites were used to evaluate the goodness of field reconstructed SWCCs for soils characterized by different geomorphological, geological, physical and pedological features. Field measured or laboratory measured SWCCs data of 5 soil horizons (3 in a predominantly silty soil, 2 in a predominantly clayey one) were fitted by Van Genuchten model. Different field drying and wetting periods were identified, based on monthly meteorological conditions, in terms of rainfall and evapotranspiration amounts, of different cycles. This method allowed for a correct discrimination of the main drying and the main wetting paths from field data related and for a more reliable quantification of soil hydrological properties with respect to laboratory methodologies. Particular patterns of changes in SWCCs forms along depth could be also identified. Field SWCCs estimation is not affected by the temporal resolution of the acquisition (hours or days), as testified by similar values of Van Genuchten equation fitting parameters. Instead, hourly data may offer a clearer vision of the drying and wetting paths, due to the highest number of experimental data points. Moreover, in temperate climate situations as those of the test-sites, main drying curves and main wetting curves of a particular soil were substantially similar also for different hydrological cycles with peculiar meteorological conditions. SWCCs parameters were implemented in a numerical code (HYDRUS-1D) to simulate soil water storage for different soil horizons. Field reconstructed SWCCs allowed for simulating with a higher precision these trends, confirming the reliability of the reconstructed field curves by a quantitative point of view. Moreover, best results were obtained considering hysteresis in the modeling.