Empirical Correction Factors Research Articles

Extensive reference set and refined computational protocol for calculations of 57Fe Mössbauer parameters.

Mössbauer spectroscopy is a powerful technique for probing the local electronic structure of iron compounds, because it reports in an element-selective manner on both the oxidation state and coordination environment of the Fe ion. Computational prediction of the two main Mössbauer parameters, isomer shift (δ) and quadrupole splitting (ΔEQ), has long been targeted by quantum chemical studies, and useful protocols based on density functional theory have been proposed. Here we present an extensive curated reference set of Fe compounds that is considerably larger and more diverse than literature precedents. We make a distinction between low-temperature and high-temperature experimental subgroups. This set is employed for optimizing a refined computational protocol utilizing the scalar version of the exact 2-component (X2C) Hamiltonian with the finite nucleus approximation. Attention is devoted to having an accurate and flexible all-electron basis set for Fe. We assess the performance of several DFT methods that cover all representative families and rungs of functionals and find that hybrid functionals with ca. 25-30% exact exchange offer the best accuracy for isomer shifts. The work establishes a refined general protocol of wide applicability that achieves good performance for the prediction of isomer shifts in a wider variety of systems than before, but the limitations of DFT for quadrupole splittings are also highlighted. Finally, comparison of calculated values with high-temperature experimental results shows that the use of an empirical correction factor is required to account for the second-order Doppler shift and to achieve the same quality of correlation as with the low-temperature data.

Unified AI-Based Predictive Models for the Ultimate Capacity of Multi-Planar Gapped KK Steel Pipe Joints

The multi-planar steel pipe joints are widely used in communication towers, industrial structures, and offshore platforms. The current design formulas consider this joint as a uniplanar joint and account for the multi-planar effect using empirical correction factors. Recent studies deal with this multi-planar joint as a 3D joint but considering certain loading conditions. Hence, the aim of this research is to develop more general AI-based predictive models for the ultimate capacity of multi-planar gapped KK steel pipe joints, considering both symmetric and asymmetric loading conditions. Three AI techniques were applied to a database of previously published works. These techniques are “Genetic Programming” (GP), “Artificial Neural Network” (ANN), and “Evolutionary Polynomial Regression” (EPR). The prediction accuracies of the developed AI models were compared against two previously published formulas. The results indicated that the developed AI models are much more accurate than the previously published formulas. Also, the results showed that both the ANN and EPR models have almost the same level of accuracy (about 92%), but the EPR model has the advantage of presenting a closed-form equation that could be implemented either manually or using software. Doi: 10.28991/CEJ-SP2024-010-07 Full Text: PDF

Three-dimensional flow around and through a porous screen

We investigate the three-dimensional (3-D) flow around and through a porous screen for various porosities at high Reynolds number $Re = {O}(10^4)$ . Historically, the study of this problem has been focused on two-dimensional cases and for screens spanning completely or partially a channel. Since many recent problems have involved a porous object in a 3-D free flow, we present a 3-D model initially based on Koo & James (J. Fluid Mech., vol. 60, 1973, pp. 513–538) and Steiros & Hultmark (J. Fluid Mech., vol. 853, 2018 pp. 1–11) for screens of arbitrary shapes. In addition, we include an empirical viscous correction factor accounting for viscous effects in the vicinity of the screen. We characterize experimentally the aerodynamic drag coefficient for a porous square screen composed of fibres, immersed in a laminar air flow with various solidities and different angles of attack. We test various fibre diameters to explore the effect of the space between the pores on the drag force. Using PIV and hot wire probe measurements, we visualize the flow around and through the screen, and in particular measure the proportion of fluid that is deviated around the screen. The predictions from the model for drag coefficient, flow velocities and streamlines are in good agreement with our experimental results. In particular, we show that local viscous effects are important: at the same solidity and with the same air flow, the drag coefficient and the flow deviations strongly depend on the Reynolds number based on the fibre diameter. The model, taking into account 3-D effects and the shape of the porous screen, and including an empirical viscous correction factor that is valid for fibrous screens may have many applications including the prediction of water collection efficiency for fog harvesters.

The impact of low-mode symmetry on inertial fusion energy output in the burning plasma state

Indirect Drive Inertial Confinement Fusion Experiments on the National Ignition Facility (NIF) have achieved a burning plasma state with neutron yields exceeding 170 kJ, roughly 3 times the prior record and a necessary stage for igniting plasmas. The results are achieved despite multiple sources of degradations that lead to high variability in performance. Results shown here, for the first time, include an empirical correction factor for mode-2 asymmetry in the burning plasma regime in addition to previously determined corrections for radiative mix and mode-1. Analysis shows that including these three corrections alone accounts for the measured fusion performance variability in the two highest performing experimental campaigns on the NIF to within error. Here we quantify the performance sensitivity to mode-2 symmetry in the burning plasma regime and apply the results, in the form of an empirical correction to a 1D performance model. Furthermore, we find the sensitivity to mode-2 determined through a series of integrated 2D radiation hydrodynamic simulations to be consistent with the experimentally determined sensitivity only when including alpha-heating.

Estimation of Cochlear Frequency Selectivity Using a Convolution Model of Forward-Masked Compound Action Potentials.

Frequency selectivity is a fundamental property of the peripheral auditory system; however, the invasiveness of auditory nerve (AN) experiments limits its study in the human ear. Compound action potentials (CAPs) associated with forward masking have been suggested as an alternative to assess cochlear frequency selectivity. Previous methods relied on an empirical comparison of AN and CAP tuning curves in animal models, arguably not taking full advantage of the information contained in forward-masked CAP waveforms. To improve the estimation of cochlear frequency selectivity based on the CAP, we introduce a convolution model to fit forward-masked CAP waveforms. The model generates masking patterns that, when convolved with a unitary response, can predict the masking of the CAP waveform induced by Gaussian noise maskers. Model parameters, including those characterizing frequency selectivity, are fine-tuned by minimizing waveform prediction errors across numerous masking conditions, yielding robust estimates. The method was applied to click-evoked CAPs at the round window of anesthetized chinchillas using notched-noise maskers with various notch widths and attenuations. The estimated quality factor Q10 as a function of center frequency is shown to closely match the average quality factor obtained from AN fiber tuning curves, without the need for an empirical correction factor. This study establishes a moderately invasive method for estimating cochlear frequency selectivity with potential applicability to other animal species or humans. Beyond the estimation of frequency selectivity, the proposed model proved to be remarkably accurate in fitting forward-masked CAP responses and could be extended to study more complex aspects of cochlear signal processing (e.g., compressive nonlinearities).

Comparison of aerosol spectrometers : accounting for evaporation and sampling losses

Measuring aerosol size distribution with precision is critical to understand the transmission of pathogens causing respiratory illnesses and to identify risk mitigation strategies. It is however a challenging task as the size of pathogen-carrying particles evolves over time due to evaporation. Although measurement techniques well established in the field of aerosol science are often used to characterize bioaerosols, their performance is seldom assessed with respect to evaporation and deposition in sampling lines. Four instruments providing aerosol size distribution were compared using oil and water-based particles. They each rely on different measurement principles: phase doppler anemometry, light scattering, electrical mobility and aerodynamic impaction. Size distributions of oil-based particles showed consistency across different measurement instruments, but significant discrepancies arose for water-based particles undergoing evaporation. These larger differences result from both evaporation and particle deposition in transit between the sampling point and the measurement inside the instrument. Phase doppler anemometry was best suited for precise size distribution measurement, as it eliminates the need for a sampling line, thereby preventing particle loss or evaporation during transit. With this instrument as a reference, empirical correction factors for evaporation and deposition were derived from dimensionless numbers and experimental data, enabling quantitative assessment of bioaerosol size distribution using different instruments. To obtain the size distribution at the source of the aerosol generation, complete drying of a salt solution was performed. Using the complete drying technique and accounting for losses, sampling instruments can reliably provide this critical information and allow for thorough risk assessment in the context of airborne transmission.

Microscale modelling of electret filters using disordered 2-D domains

This paper reports on a computational study about the impact of fiber dipole orientation on particle collection efficiency of a bipolarly charged filter. The simulations were carried out using ANSYS software in a series of 2-D geometries comprised of randomly distributed fibers. The simulations were enhanced with in-house subroutines to incorporate Coulomb and dielectrophoretic forces in calculating particle trajectories and thereby simulating filter efficiency. The highest and lowest efficiencies were observed for dipole orientations that were perpendicular and parallel to the airflow direction, respectively. The simulation results were also compared with the predictions of the popular semi-empirical correlations from the literature and good general agreement was observed, without the need for any empirical correction factors. In addition, it was observed that the predictions of the semi-empirical correlations better agreed with the simulation results obtained for media comprised of fibers with random dipole orientations when challenged with neutralized particles.

Modeling of Flash Temperature for Elastic Sliding Contact of Single Micro-Asperity Pair

Abstract The flash temperature in the sliding frictional contact between micro-asperities has an important influence on the frictional characteristics of advanced functional ceramics. In this paper, the elastic sliding frictional contact of a three-dimensional micron/submicron scale asperity pair is considered. A three-dimensional finite element model (FEM) for fully coupled thermal-stress analysis of sliding contact of SiC/Al2O3 asperity pair is developed. An empirical correction factor for contact characteristics is obtained based on the FEM results. The FEM results show that, compared with the Hertz theoretical solution, the contact area becomes smaller and the contact pressure becomes larger in the case of sliding contact with large deformation. The flash temperature has a negative correlation with the composite radius of the asperity pair and a positive correlation with the interference depth and sliding speed. Using Hertz theory, a parabolic distributed heat source, the Fourier heat conduction law, and the newly proposed correction factor, a semi-analytical model of flash temperature during the elastic frictional sliding between two single asperities is established. The relative difference between the flash temperature predicted by the established semi-analytical model and the FEM model is less than 1.2%. The relative difference decreases with the increasing interference depth. This work is a valuable reference for studying the frictional heat-related issues of advanced ceramics.

Modeling liquid–vapor phase change experiments: Cryogenic hydrogen and methane

Mass accommodation coefficients are essential inputs to kinetic models of liquid–vapor phase change, yet after nearly 100 years there remains significant discrepancy in reported values. These discrepancies have been attributed to a wall material or geometric dependency resulting in the need for an empirical correction factors. The lack of experimental results for cryogenic fluids poses a serious impediment to modeling/predicting propellant behavior for long term space missions. Using a combination of neutron imaging experiments and multi-scale modeling, mass accommodation coefficients for liquid hydrogen and methane are determined. When the local variation in thermophysical properties are accounted for, the experimentally derived accommodation coefficients for hydrogen are invariant to container size, material and evaporation rate. The discrepancy in prior measurements of the accommodation coefficient for other fluids can be alleviated by a multi-scale analysis that incorporates local variation in thermophysical properties. The values of accommodation coefficients for hydrogen and methane are consistent with generalized transition state theory. This suggests that a mass accommodation coefficient is a solely a function of the liquid–vapor density ratio, making it a fluid-independent property easily determined without the need for empirical correction factors as reported in previous investigations.

Drug Design and Success of Prospective Mouse In Vitro-In Vivo Extrapolation (IVIVE) for Predictions of Plasma Clearance (CLp) from Hepatocyte Intrinsic Clearance (CLint).

Hepatocyte intrinsic clearance (CLint) and methods of in vitro-in vivo extrapolation (IVIVE) are often used to predict plasma clearance (CLp) in drug discovery. While the prediction success of this approach is dependent on the chemotype, specific molecular properties and drug design features that govern these outcomes are poorly understood. To address this challenge, we investigated the success of prospective mouse CLp IVIVE across 2142 chemically diverse compounds. Dilution scaling, which assumes that the free fraction in hepatocyte incubations (fu,inc) is governed by binding to the 10% of serum in the incubation medium, was used as our default CLp IVIVE approach. Results show that predictions of CLp are better for smaller (molecular weight (MW) < 500 Da), less polar (total polar surface area (TPSA) < 100 Å2, hydrogen bond donor (HBD) ≤1, hydrogen bond acceptor (HBA) ≤ 6), lipophilic (log D > 3), and neutral compounds, with low HBD count playing the key role. If compounds are classified according to their chemical space, predictions were good for compounds resembling central nervous system (CNS) drugs [average absolute fold error (AAFE) of 2.05, average fold error (AFE) of 0.90], moderate for classical druglike compounds (according to Lipinski, Veber, and Ghose guidelines; AAFE of 2.55; AFE of 0.68), and poor for nonclassical "beyond the rule of 5" compounds (AAFE of 3.31; AFE of 0.41). From the perspective of measured druglike properties, predictions of CLp were better for compounds with moderate-to-high hepatocyte CLint (>10 μL/min/106 cells), high passive cellular permeability (Papp > 100 nm/s), and moderate observed CLp (5-50 mL/min/kg). Influences of plasma protein binding (fu,p) and P-glycoprotein (Pgp) apical efflux ratio (AP-ER) were less pronounced. If the extended clearance classification system (ECCS) is applied, predictions were good for class 2 (Papp > 50 nm/s; neutral or basic; AAFE of 2.35; AFE of 0.70) and acceptable for class 1A compounds (AAFE of 2.98; AFE of 0.70). Classes 1B, 3 A/B, and 4 showed poor outcomes (AAFE > 3.80; AFE < 0.60). Functional groups trending toward weaker CLp IVIVE were esters, carbamates, sulfonamides, carboxylic acids, ketones, primary and secondary amines, primary alcohols, oxetanes, and compounds liable to aldehyde oxidase metabolism, likely due to multifactorial reasons. Multivariate analysis showed that multiple properties are relevant, combining together to define the overall success of CLp IVIVE. Our results indicate that the current practice of prospective CLp IVIVE is suitable only for CNS-like compounds and well-behaved classical druglike space (e.g., high permeability or ECCS class 2) without challenging functional groups. Unfortunately, based on existing mouse data, prospective CLp IVIVE for complex and nonclassical chemotypes is poor and hardly better than random guessing. This is likely due to complexities such as extrahepatic metabolism and transporter-mediated disposition which are poorly captured by this methodology. With small-molecule drug discovery increasingly evolving toward nonclassical and complex chemotypes, existing CLp IVIVE methodology will require improvement. While empirical correction factors may bridge the gap in the near future, improved and new in vitro assays, data integration models, and machine learning (ML) methods are increasingly needed to address this challenge and reduce the number of nonclinical pharmacokinetic (PK) studies.

Dissociation Kinetics in Quadrupole Ion Traps: Effective Temperatures under Dipolar DC Collisional Activation Conditions.

Ions stored in an electrodynamic ion trap can be forced from the center of the ion trap to regions of higher radio frequency (RF) electric fields by exposing them to a dipolar DC (DDC) potential applied across opposing electrodes. Such ions absorb power from the trapping RF field, resulting in increased ripple motion at the frequency of the trapping RF. When a bath gas is present, ions undergo energetic collisions that result in "RF-heating" sufficient to induce fragmentation. DDC is therefore a broad-band (i.e., mass-to-charge-independent) means for collisional activation in ion traps with added bath gas. Under appropriate conditions, the internal energy distribution of an ion population undergoing dissociation can be approximated with an effective temperature, Teff. In such cases, it is possible to determine thermal activation parameters, such as Arrhenius activation energies and A-factors, by measuring dissociation kinetics. In this work, the well-studied thermometer ion, protonated leucine enkephalin, was subjected to DDC activation under rapid energy exchange conditions and in two separate bath gases, N2 and Ar, to measure Teff as a function of the ratio of DDC and RF voltages. As a result, an empirically derived calibration was generated to link experimental conditions to Teff. It was also possible to quantitatively evaluate a model described by Tolmachev et al. that can be used to predict Teff. It was found that the model, which was derived under the assumption of an atomic bath gas, accurately predicts Teff when Ar was used as the bath gas but overestimates Teff when N2 was the bath gas. Adjustment of the Tolmachev et al. model for a diatomic gas resulted in an underestimate of Teff. Thus, use of an atomic gas can provide accurate activation parameters, while an empirical correction factor should be used to generate activation parameters using N2.

Maximum steady stress of various cross-section beams under combined loadings during creep

In the simplified method based on stress classification for estimating the stress at the steady stage during creep, an empirical correction factor is needed to account for the relaxation of primary bending stress during creep. An analysis of a rectangular beam subjected to tensile loading and bending moment during creep is carried out to demonstrate the applicability of the Kt, which is the correction factor proposed by the ASME code, in this work. In view of the effects of material creep property and the primary membrane stress on the relaxation of the primary bending stress, a method for accessing the parameter Kt is proposed and validated. The results reveal that the parameter Kt will increase with the tensile loading due to the relaxation of the primary bending stress accelerated by the primary membrane stress. Good agreement between the results of inelastic analysis and the modified method is observed for the beams with different material properties, combined loadings, and cross-section shapes.

A simple approximation for the drift rates of rotating polygons on a free fluid surface

We report on laboratory experiments investigating the dynamics of a free fluid surface in a cylindrical tank with a rotating bottom plate. The shear instability in the system creates polygonal structures, which propagate around the domain, along the fixed vertical sidewalls. We analyze the wavelengths and drift rates of these patterns, which are known from previous literature to be created by a complex interplay between centrifugal effects and gravity wave propagation in this unique geometry. We find that with an empirical correction factor, the drift rates of the polygonal vortices can be approximated fairly well by a surprisingly simple formula derived from the dispersion relation of linear gravity waves using easily observable parameters.

The influence of model assumptions in a hybrid prediction tool for railway induced vibration

Within the SILVARSTAR project, a user-friendly frequency-based hybrid prediction tool is developed to assess the environmental impact of railway induced vibration. This will be implemented in the existing noise mapping software IMMI. The vibration level in a building in each frequency band is expressed as the product of source, propagation and receiver terms. A hybrid approach is used that combines experimental data with numerical predictions, providing increased flexibility and applicability. The train and track properties can be selected from a database or as numerical values. The user can select soil impedance and transfer functions from a database, pre-computed for a wide range of parameters with the MOTIV and TRAFFIC models. An experimental database of force densities, transfer functions, free field vibration and input parameters is also integrated into the new tool. The building response is estimated by means of empirical correction factors. Assumptions within the modelling approach can influence the prediction accuracy and the present paper aims to quantify these. We focus on the influence of train speed and soil properties on the compliance of the track-soil system, the dynamic axle loads, and the free field response, as well as on the load transfer between track and soil.

Evaluation of random-vibration procedures to estimate response spectral ordinates on soft soil sites from fourier amplitude spectra

This study evaluates Random-Vibration Procedures (RVP) to estimate 5% damped response spectra of ground motions recorded on soft soil sites from Fourier Amplitude Spectra (FAS). The study makes use of 136 ground motions recorded in the soft soil Mexico City region during two recent large magnitude earthquakes. Seven different RVP are considered in this investigation consisting of four peak factor models, three strong ground motion duration models, and four non-stationary empirical correction factors. Spectral ordinates computed through conventional time integration were compared to approximate spectral ordinates computed using the FAS of the recorded acceleration time series in combination with RVP. A statistical error analysis was then conducted to determine how effective the various RVP were at estimating the exact pseudo-acceleration response spectra computed with response history analyses. It is found that most RVP commonly used today produce significant systematic overestimations of spectral ordinates at the fundamental mode of the soil deposit. Modifications to durations are proposed to be used in conjunction with various peak factors to reduce overestimations at the site period.

A Compact Current-Transfer Model in Resonant-Tunneling Structures with Consideration of Interelectronic Interaction

A compact analytical model of current transfer was developed to estimate the characteristics of heterostructured devices. The absence of empirical correction factors and the explicit accounting of the interelectronic interaction differentiates it from previous similar models. The model obtains an estimates of the electron density in the quantum well of the heterostructural channel and applies a self-consistent correction for resonance levels. It also provides accuracy in the positive differential resistance region of the I–V characteristics in the AlGaAs structures, with an average relative error not exceeding 2%. The time complexity of the calculations of the I–V characteristics using this model is several orders of magnitude less than that of calculations using ab initio models. Its high accuracy and low temporal complexity of calculations of I–V characteristics allow this model to be integrated in systems for the design and calculation of reliability indicators for devices, including terahertz devices.

Spatiotemporal distribution of veterinary and human drugs and its predictability in Japanese catchments

Little is known about the predictability of mass flows of veterinary drugs in Asian catchments, where effluent from livestock farms is a major source. We therefore conducted this study to understand the applicability and limitations of a population-based emission model, which assumed usage of veterinary and human drugs to be evenly distributed over the national livestock or human population throughout the year, and sources to be effluent discharges at livestock farms, households, and sewage treatment plants in Japanese catchments. We monitored five veterinary drugs (lincomycin, sulfamonomethoxine, tiamulin, tylosin, and tilmicosin), two human and livestock drugs (sulfamethoxazole and trimethoprim), two human drugs (carbamazepine and clarithromycin), and a metabolite (sulfapyridine) of a human drug once a month over 2 years in eight Japanese rivers which have active livestock farming in their catchments. Mass flows of carbamazepine and sulfapyridine were stable, while those of veterinary drugs fluctuated widely, especially sulfamonomethoxine and tilmicosin, whose 25 %–100 % ranges averaged 1.5 and 1.2 log units, respectively, attributable mainly to their usage patterns. The model accurately predicted mean mass flows of carbamazepine in the rivers with errors of <±0.3 log unit. Although it slightly to moderately overestimated those of the other four human-related compounds, the incorporation of an empirical correction factor, determined to minimize mean absolute error (MAE) among the rivers, substantially lowered their MAEs to <0.23 log units. However, the MAEs of the five veterinary drugs were as high as 0.42 (sulfamonomethoxine) to 0.60 (tiamulin) log units even with the coefficient, likely due mainly to the spatial distribution of their usage per capita. So as not to overlook spatiotemporal elevation of risks of veterinary drugs, a stochastic method should be applied in their management. This is the first study to assess the use of spatiotemporal homogeneity in usage per capita of veterinary drugs in Asian catchments.

Comparison of radio propagation models in five LTE coverage cells in Riobamba

This article makes a comparative analysis of the power intensity levels measured with the Network Cell Info Lite application and the performance of the different Log-Normal, Okumura Hata, COST 231, Wolfish Bertoni and SUI propagation models in the Frequency Band 4G LTE. The study was carried out in 5 LTE coverage cells located in the southern area of ​​the City of Riobamba and the model that best fits each cell is limited using absolute error analysis, obtaining an empirical correction factor for the proposed models. For the analysis of the absolute error, 3 measurement campaigns were carried out with 50 samples where the mean value was obtained. The analysis carried out will be suspended because the Log-Normal model is the one that best fits the Riobamba environment considering that it is a residential area, and that the power levels vary from (-80 dBm to -106 dBm) and that the coverage areas were determined up to 200m.

Comparison of radio propagation models in five LTE coverage cells in Riobamba

This article performs a comparative analysis of the power intensity levels measured with the Network Cell Info Lite application and the performance of the different propagation models: Log-Normal, Okumura Hata, COST 231, Walfish Bertoni, and SUI in the 4G LTE Frequency Band. The study was conducted in five LTE coverage cells located in the southern area of the city of Riobamba. The model that best fits each cell was chosen by means of absolute error analysis, thus obtaining an empirical correction factor for the proposed models. For the analysis of the absolute error, three measurement campaigns were carried out with 50 samples where the mean value was obtained. After applying the aforementioned models, the Log-Normal model yielded the most favorable results, being the one that achieved the best adaptation in Riobamba, since the power levels vary in the range (-80; -106) dBm at a coverage area not exceeding 200m.

An energy-dependent electro-thermal response model of CUORE cryogenic calorimeter

The Cryogenic Underground Observatory for Rare Events (CUORE) is the most sensitive experiment searching for neutrinoless double-beta decay (0νββ) in 130Te. CUORE uses a cryogenic array of 988 TeO2 calorimeters operated at ∼10 mK with a total mass of 741 kg. To further increase the sensitivity, the detector response must be well understood. Here, we present a non-linear thermal model for the CUORE experiment on a detector-by-detector basis. We have examined both equilibrium and dynamic electro-thermal models of detectors by numerically fitting non-linear differential equations to the detector data of a subset of CUORE channels which are well characterized and representative of all channels. We demonstrate that the hot-electron effect and electric-field dependence of resistance in NTD-Ge thermistors alone are inadequate to describe our detectors' energy-dependent pulse shapes. We introduce an empirical second-order correction factor in the exponential temperature dependence of the thermistor, which produces excellent agreement with energy-dependent pulse shape data up to 6 MeV. We also present a noise analysis using the fitted thermal parameters and show that the intrinsic thermal noise is negligible compared to the observed noise for our detectors.