Determination Of Model Parameters Research Articles

Parameters estimation and uncertainty assessment in the transmission dynamics of rabies in humans and dogs

Rabies remains a pressing global public health issue, demanding effective modeling and control strategies. This study focused on developing a mathematical model using ordinary differential equations (ODEs) to estimate parameters and assess uncertainties related to the transmission dynamics of rabies in humans and dogs. To determine model parameters and address uncertainties, next-generation matrices were utilized to calculate the basic reproduction number R0. Furthermore, the Partial Rank Correlation Coefficient was used to identify parameters that significantly influence model outputs. The analysis of equilibrium states revealed that the rabies-free equilibrium is globally asymptotically stable when R0<1, whereas the endemic equilibrium is globally asymptotically stable when R0≥1. To reduce the severity of rabies and align with the Global Rabies Control (GRC) initiative by 2030, the study recommends implementing control strategies targeting indoor domestic dogs.

Hydrological Simulation and Parameter Optimization Based on the Distributed Xin’anjiang Model and the Particle Swarm Optimization Algorithm: A Case Study of Xunhe Watershed in Shandong, China

Hydrological models serve as essential tools in hydrological research, allowing us to address practical hydrological issues. This study focuses on the Xunhe Watershed in Shandong Province, China, constructing a distributed Xin’anjiang hydrological model. Furthermore, traditional manual calibration and automatic calibration using the Particle Swarm Optimization (PSO) algorithm were employed to determine model parameters, followed by hydrological simulations, with the aim of investigating the applicability of the distributed Xin’anjiang model in this watershed. The research findings indicate that the distributed Xin’anjiang model accurately simulates the hydrological processes in the Xunhe Watershed. There is a high level of agreement between the observed data and the simulated results, including key indicators such as peak discharge, runoff volume, and peak time. After optimizing the model parameters using the PSO algorithm, the distributed Xin’anjiang model demonstrates improved simulation performance in the Xunhe Watershed. During the calibration period, the mean relative peak discharge error (RPE) is 4.1%, the mean relative runoff error (RRE) is 4.34%, and the average Nash–Sutcliffe efficiency (NSE) for simulating the flood events is 0.89. During the validation period, the mean RPE is 3.82%, the mean RRE is 6.1%, and the average NSE for the process is 0.83. This indicates that the distributed Xin’anjiang model has good applicability in this watershed, providing a reliable reference for flood control and disaster reduction in the Xunhe Watershed.

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy.

Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

Extending GLUE With Multilevel Methods to Accelerate Statistical Inversion of Hydrological Models

AbstractInverse problems aim at determining model parameters that produce observed data to subsequently understand, predict or manage hydrological or other environmental systems. While statistical inversion is especially popular, its sampling‐based nature often inhibits its application to computationally costly models, which has compromised the use of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology, for example, for spatially distributed (partial) differential equation based models. In this study we introduce multilevel GLUE (MLGLUE), which alleviates the computational burden of statistical inversion by utilizing a hierarchy of model resolutions. Inspired by multilevel Monte Carlo, most parameter samples are evaluated on lower levels with computationally cheap low‐resolution models and only samples associated with a likelihood above a certain threshold are subsequently passed to higher levels with costly high‐resolution models for evaluation. Inferences are made at the level of the highest‐resolution model but substantial computational savings are achieved by discarding samples with low likelihood already on levels with low resolution and low computational cost. Two example inverse problems, using a rainfall‐runoff model and groundwater flow model, demonstrate the substantially increased computational efficiency of MLGLUE compared to GLUE as well as the similarity of inversion results. Findings are furthermore compared to inversion results from Markov‐chain Monte Carlo (MCMC) and multilevel delayed acceptance MCMC, a corresponding multilevel variant, to compare the effects of the multilevel extension. All examples demonstrate the wide‐range suitability of the approach and include guidelines for practical applications.

Failure analysis of Nehbandan granite under various stress states and strain rates using a calibrated Riedel–Hiermaier–Thoma constitutive model

This study presents a comprehensive procedure for determining, calibrating, and validating the Riedel–Hiermaier–Thoma (RHT) material model parameters for granite. The process involves collecting a comprehensive dataset of conventional mechanical tests conducted on various types of granite worldwide. Based on this dataset, one set of RHT material model parameters is determined. Additionally, a specific granite sample from Iran, known as Nehbandan granite, is characterized through physical and mechanical testing to obtain another set of parameters. The challenging task of determining the third set of parameters, which are difficult to obtain analytically and experimentally, is accomplished through a calibration process that iteratively adjusts the parameters based on comparisons between numerical simulation results and experimental data. To validate the determined parameters, a series of tests, including uniaxial compressive strength (UCS), triaxial compressive strength (TCS), Brazilian tensile strength, and dynamic Brazilian using split Hopkinson pressure bar (SHPB) tests, are conducted on the Nehbandan granite. These tests are also simulated using LS-Dyna software, and the numerical simulation results are compared with the corresponding experimental test results. The comparison between the numerical and experimental data serves as a means of validating and verifying the accuracy and reliability of the determined RHT material model parameters for granite. The results demonstrate the successful determination and calibration of the RHT material model parameters for granite. The model exhibits effectiveness in predicting the behavior of granite under various loading conditions. The validation process confirms the accuracy and reliability of the determined parameters through a close agreement between numerical simulations and experimental data. The findings contribute to a better understanding of granite's mechanical response and provide a reliable tool for simulating and predicting its behavior in engineering applications. The validated RHT material model parameters offer a robust framework for accurate numerical simulations, enabling engineers to make informed decisions in rock engineering projects.

Constitutive model of high-temperature rapid fracture of Si3N4 ceramics for engine turbine discs and their pore insensitivity parameters

ABSTRACT The metallic materials used to manufacture turbine components can potentially be replaced with ceramics such as Si3N4, but the stress on turbine discs is difficult to determine experimentally, which hinders the development and optimization of ceramics. The finite element method solves this problem, but it requires an accurate constitutive model and parameters. Existing methods for determining model parameters lack versatility and do not consider the internal pores of ceramics. This work proposes a method for determining the parameters of the high-temperature rapid fracture constitutive model of ceramics with internal pores based on the results of industrial computed tomography (CT) and high-temperature fracture toughness experiments. The constitutive model for a ceramic with internal pores was selected based on the typical service conditions of turbine discs. Industrial CT was used to measure pore information. A finite element preprocessor was developed to create simulated specimens with pores. The high-temperature fracture toughness of the ceramics was measured. Pore insensitivity was the parameter obtained from the high-temperature constitutive model of ceramics with pores using this method. The maximum relative error between the predicted and experimental flexural strengths was 6.8%. It provides a new idea for determining the parameters of constitutive models for materials with pores.

Liquid–Liquid Equilibrium with Ab Initio Molecular Dynamics Simulation and NRTL Parameter Estimation

ABSTRACTIn this study, we propose a method for estimating liquid–liquid equilibrium with ab initio molecular dynamics (MD) simulation. Additionally, we determined the non‐random two‐liquid model parameters for the systems applicable to the extraction design using a commercial software. The minimized energy of separate liquid phases yielded equilibrium data from a more versatile procedure than the existing MD simulation. Although many experimental measurements with the parameters have been published, the parameters are not always compatible with the software. The performances are graphically illustrated for example systems including ionic liquid and deep eutectic solvent, and the results indicated that the proposed procedures of the estimation and the model parameter determination were satisfactory.

Cyclic moment-rotation model for bolted double-angle connections with composite floor systems

This paper presents a simplified moment-rotation model for cyclic response of bolted double-angle beam-to-column connections in composite steel frames with concrete on metal decking floors. The proposed model employs mechanics-based equations to determine model parameters, along with empirical observations from previous studies and data from recent large-scale multi-bay frame experiments. Several design variables and construction details, such as orientation of the metal decking, concrete reinforcement layout, and deck splicing details around the connection, were considered in the proposed model. Comparisons between the connection model and experimental results showed reasonable agreement in moment-resisting capacity up to 8% interstory drift. Notably, the proposed model adequately simulated varying responses based on connection details not captured by existing moment-rotation models. Analyses of 2- and 4-story frames using the proposed model showed up to 1.3 times higher ductility and 47% lower initial rotational stiffness compared to those using the existing ASCE 41 connection models with strengths of 20% and 35% of the plastic moment capacity of the girder. These results indicate the potential overestimation of stiffness and moment-resisting capacity, and the underestimation of ductility when using existing moment-rotation models due to insufficient modeling parameters to represent actual behavior. Therefore, the proposed model demonstrates its applicability in incorporating various design variables and construction details of bolted double-angle connections with composite concrete on metal deck floors. This model can be used to account for the non-negligible strength and stiffness of bolted double-angle connections in steel gravity framing under seismic loads.

Resummation of combined QCD-electroweak effects in Drell Yan lepton-pair production

We consider neutral- and charged-current Drell Yan lepton-pair production at hadron colliders, and include dominant classes of electroweak and mixed QCD-electroweak corrections to all orders in perturbation theory. The accurate description of these physical effects is vital for a precise determination of fundamental Standard Model parameters, such as the W-boson mass and the electroweak mixing angle, as well as for a solid assessment of the associated theoretical uncertainties. Our state-of-the-art resummation reaches next-to-leading-logarithmic accuracy in both the electroweak and the mixed QCD-electroweak perturbative expansions, including constant terms at first order beyond Born level in both couplings, i.e. at order α and αsα. These effects are incorporated on top of QCD predictions at next-to-next-to-next-to-leading-logarithmic accuracy, which include constant terms at third order in the strong coupling. Our results retain, for the first time at this accuracy, full dependence on the kinematics of the final-state leptons, thereby enabling a realistic comparison with experimental analyses at the differential level in presence of fiducial cuts. We present a phenomenological analysis of the impact of electroweak corrections in relevant observables at the LHC. We find visible shape distortions in resummation-dominated kinematical regions with respect to pure-QCD predictions, highlighting the importance of a complete description, not limited to QCD, for precision Drell Yan physics.

Modeling Torsional Stiffness and Damping of Liquid Slosh in Spacecraft Diaphragm Tanks

This study presents a pendulum-based empirical model of liquid slosh in spacecraft diaphragm tanks. Diaphragm torsional stiffness and effective damping are predicted within a range of lateral excitation frequency typical of launch or on-orbit operations. A pendulum-analog model with two primary slosh modes is extracted from diaphragm tank slosh data corresponding to steady-state triaxial force measurements at the support points of the tank under sinusoidal excitation. The approach leads to repeatable and accurate determination of pendulum model parameters. A gradient-based algorithm and a procedure for setting initial conditions for optimal parameter estimation are proposed to predict the liquid slosh forces and torques acting on the tank as frequency response functions of apparent mass and apparent mass moment. The pendulum models were assessed by comparing model-predicted force/torques with measurements, showing good agreement (1–5% prediction error in the time domain) under most test conditions (fill level, excitation amplitude, and frequency). An empirical model of the stiffness and damping is also proposed for the tested range of operational conditions. Because of the nonlinear nature of liquid slosh behavior in a diaphragm tank, both the stiffness and damping are local values for a given set of test conditions.

Advancing HIC method development: Retention-time modeling and tuning selectivity with ternary mobile-phase systems

The use of a ternary mobile-phase system comprising ammonium sulphate, sodium chloride, and phosphate buffer was explored to tune retention and enhance selectivity in hydrophobic interaction chromatography. The accuracy of the linear solvent-strength model to predict protein retention with the ternary mobile-phase system based on isocratic scouting runs is limited, as the extrapolated retention factor at aqueous buffer conditions (k0) cannot be reliably established. The Jandera retention model utilizing a salt concentration averaged retention factor (k¯0) in aqueous buffer for ternary systems overcomes this bottleneck. Gradient retention factors were derived based on isocratic scouting runs after numerical integration of the isocratic Jandera model, leading to retention-time prediction errors below 11 % for linear gradients. Furthermore, an analytical expression was formulated to predict HIC retention for both linear and segmented linear gradients, considering the linear solvent-strength (LSS) model within ternary salt systems, relying on a fixed k0. The approach involved conducting two gradient scouting runs for each of the two binary salt systems to determine model parameters. Retention-time prediction errors for linear gradients were below 12 % for lysozyme and 3 % for trypsinogen and α-chymotrypsinogen A. Finally, the analytical expression for a ternary mobile-phase system was used in combination with a genetic algorithm to tune the HIC selectivity. With an optimized segmented ternary gradient, a critical-pair separation for a mixture of 7 proteins was achieved within 15 min with retention-time prediction errors ranging between 0.7 and 15.7 %.

Unveiling the Structural Properties, Optical Behavior, and Thermoelectric Performance of 2D CsSn2Br5 Halide Obtained by Mechanochemistry.

Metal halide perovskites with a two-dimensional structure are utilized in photovoltaics and optoelectronics. High-crystallinity CsSn2Br5 specimens have been synthesized via ball milling. Differential scanning calorimetry curves show melting at 553 K (endothermic) and recrystallization at 516 K (exothermic). Structural analysis using synchrotron X-ray diffraction data, collected from 100 to 373 K, allows for the determination of Debye model parameters. This analysis provides insights into the relative Cs-Br and Sn-Br chemical bonds within the tetragonal structure (space group: I4/mcm), which remains stable throughout the temperature range studied. Combined with neutron data, X-N techniques permit the identification of the Sn2+ lone electron pair (5s2) in the two-dimensional framework, occupying empty space opposite to the four Sn-Br bonds of the pyramidal [SnBr4] coordination polyhedra. Additionally, diffuse reflectance UV-vis spectroscopy unveils an indirect optical gap of approximately ∼3.3 eV, aligning with the calculated value from the B3LYP-DFT method (∼3.2 eV). The material exhibits a positive Seebeck coefficient as high as 6.5 × 104 μV K-1 at 350 K, which evolves down to negative values of -3.0 × 103 μV K-1 at 550 K, surpassing values reported for other halide perovskites. Notably, the thermal conductivity remains exceptionally low, between 0.32 and 0.25 W m-1 K-1.

Определение параметров реологической модели по данным лабораторных исследований

Different types of models are used to study the stress-strain behavior of asphalt concrete mixture during compaction. For modeling it is necessary to know the values of model parameters in the whole range of changes in the characteristics of the compacted material. The aim of the paper is to develop a methodology for determining model parameters based on the results of laboratory creep-recovery testing of asphalt-concrete mixture. In the paper, a model reflecting elastic, visco-elastic and visco-fluid properties of the compacted material is adopted. A differential equation representing the law of behavior of the asphalt-concrete mixture layer under load is obtained. The stages of creep-recovery testing are analytically described, namely: rapid loading with a constant load and deformation under this load; load removal and recovery. Initial conditions for the mentioned stages are determined. Taking into account the initial conditions, analytical expressions of the laws of deformation of the model under the action of a constant load and in the process of recovery are obtained. The methodology of laboratory experiments on creep-recovery is described, according to the results of which the required values of the model parameters with minimum absolute error are obtained. The developed methodology allows to determine the parameters of the model describing the stress-strain behavior of asphalt-concrete mixture of different density and temperature. Consequently, it is possible to simulate the behavior of the asphalt concrete mixture layer at the preliminary, main and final stages of compaction in order to determine the effective operating modes of compaction equipment.

Can the shock wave generated by the thermal runaway of a lithium-metal all-solid-state cell be predicted by material-scale analysis

It is widely believed that all-solid-state batteries would be safer than traditional Li-ion ones. This study develops a thermal runaway model for lithium-metal all-solid-state cells. First, material-scale analysis were carried out to determine model parameters. Then, they were used to simulate the thermal runaway in a closed calorimeter. The initiation temperature, the energy released by the thermal runaway and its duration are consistent with the experimental data. Additionally, the model simulates the overpressure produced by this thermally abused cell in an open system and showing strong correlation with experimental data. After validation, the model was used to predict the thermal runaway of an anode-less lithium-metal all-solid-state battery. Even with the minimum quantity of lithium, the thermal runaway, while reduced, remained significant. Moreover, this work highlights the impact of the oxygen released, its strong reaction with the lithium during TR and the subsequent blast wave overpressure caused by the generated gases.

Lifetime assessment of deep-sea manned cabin with PMMA pressure-resistant hull prior to micro-cracks

Fully-transparent cabin type, utilized in manned submersibles, is typically constructed using viscoelastic PMMA (polymethyl methacrylate) material. Accurate fatigue life assessment of manned cabin is of paramount importance to ensure structural safety. In this study, a calculation process for evaluating the fatigue life of PMMA manned cabins based on a continuum damage mechanics model combined with the viscoelastic constitutive relationship of the PMMA material in response to the absence of related specification is proposed. Fatigue tests of PMMA material are performed for determination of damage evolution model parameters and the calculation process is validated by the fatigue test data. Tailored subroutines are then developed by using ABAQUS software tool, respectively for structural analysis of a typical manned cabin with PMMA pressure-resistant hull, openings, hatches and penetration plates and simulating trapezoidal loading history acting on manned cabin. Subroutine coupling is accordingly employed to conduct parametric analysis on fatigue crack initiation life of the fully-transparent manned cabin with consideration of different outside pressure level and operation time and valuable results are obtained for identifying key areas of concern. This study intends to contribute to further cabins safety enhancement, as well as to design optimization and fatigue analysis of underwater structures involving PMMA materials.

Crystal plasticity modeling and analysis for the transition from intergranular to transgranular failure in nickel-based alloy Inconel 740H at elevated temperature

The precipitation-strengthened Nickel-based alloy Inconel® 740H® (IN740H) exhibits increased ductility at higher applied strain rates during quasi-static tensile tests at an elevated temperature of 760 °C. The examination of fracture surfaces in this context reveals a noteworthy transition of underlying fracture mechanisms from transgranular to intergranular fracture as the applied strain rate decreases from 1×10−3/s to 0.83×10−4/s. To thoroughly understand the mechanical response of IN740H under these conditions, this study develops a crystal plasticity finite element (CPFE) model. This model incorporates various deformation mechanisms including dislocation slips, climb, and grain boundary sliding, which are relevant to the test conditions. The model is calibrated using data from both tensile tests at different strain rates and creep tests across a broad stress range at 760 °C, enabling the accurate determination of model parameters for each mechanism. Simulation results well captured the experimental observations of different failure modes. At higher strain rates, the model shows a dominance of dislocation slip leading to heterogeneous plastic deformation and formation of transgranular shear bands causing the failure, while at lower strain rates, an increased activity of grain boundary sliding causes grain boundaries crack leading to intergranular failure.

Modeling of the resensitization effect on carbon-ion radiotherapy for stage I non-small cell lung cancer

Objective. To investigate the effect of redistribution and reoxygenation on the 3-year tumor control probability (TCP) of patients with stage I non-small cell lung cancer (NSCLC) treated with carbon-ion radiotherapy. Approach. A meta-analysis of published clinical data of 233 NSCLC patients treated by carbon-ion radiotherapy under 18-, 9-, 4-, and single-fraction schedules was conducted. The linear-quadratic (LQ)-based cell-survival model incorporating the radiobiological 5Rs, radiosensitivity, repopulation, repair, redistribution, and reoxygenation, was developed to reproduce the clinical TCP data. Redistribution and reoxygenation were regarded together as a single phenomenon and termed ‘resensitization’ in the model. The optimum interval time between fractions was investigated for each fraction schedule using the determined model parameters. Main results. The clinical TCP data for 18-, 9-, and 4-fraction schedules were reasonably reproduced by the model without the resensitization effect, whereas its incorporation was essential to reproduce the TCP data for all fraction schedules including the single fraction. The curative dose for the single-fraction schedule was estimated to be 49.0 Gy (RBE), which corresponds to the clinically adopted dose prescription of 50.0 Gy (RBE). For 18-, 9-, and 4-fraction schedules, a 2-to-3-day interval is required to maximize the resensitization effect during the time interval. In contrast, the single-fraction schedule cannot benefit from the resensitization effect, and the shorter treatment time is preferable to reduce the effect of sub-lethal damage repair during the treatment. Significance. The LQ-based cell-survival model incorporating the radiobiological 5Rs was developed and used to evaluate the effect of the resensitization on clinical results of NSCLC patients treated with hypo-fractionated carbon-ion radiotherapy. The incorporation of the resensitization into the cell-survival model improves the reproducibility to the clinical TCP data. A shorter treatment time is preferable in the single-fraction schedule, while a 2-to-3-day interval between fractions is preferable in the multi-fraction schedules for effective treatments.

Minimization of a ship's magnetic signature under external field conditions using a multi-dipole model

The paper addresses the innovative issue of minimizing the ship's magnetic signature under any external field conditions, i.e., for arbitrary values of ambient field modulus and magnetic inclination. Varying values of the external field, depending on the current geographical location, affect only the induced part of ship's magnetization. A practical problem in minimizing the ship signature is separating permanent magnetization from induced magnetization. When the ship position changes, a signature measurement has to be made under new magnetic field conditions to update the currents in the coils. This is impractical or even difficult to do (due to the need for a measuring ground), so there is a need to predict the ship's magnetization value in arbitrary geographical location conditions based on the reference signature determined on the measuring ground. In particular, the model predicting the signatures at a new geographical location must be able to separate the two types of magnetization, as permanent magnetization is independent of external conditions. In this paper, a FEM model of the vessel is first embedded in an external field and permanent magnetization is simulated using DC coils placed inside the model. Then, using the previously developed rules for data acquisition and determination of model parameters, a multi-dipole model is synthesized in which the induced and permanent parts are separated. The multi-dipole model thus developed has been successfully confronted with the initial model in FEM environment. The separation of permanent and induced magnetization allows the latter to be scaled according to new values of the external field. In the paper, the situation of determining a signature at one geographical position and its projection onto two other positions is analyzed. Having determined the signature with a high degree of accuracy anywhere in the world, it is possible to perform classical signature minimization by determining DC currents in coils placed inside the ship's hull. The paper also analyzes the effectiveness of ship's signature minimization and the influence of ship's course on the signature value. The advantage of the method presented in this paper is an integrated approach to the issue of scaling and minimization of ship magnetic signature, which has not been presented in the literature on such a scale before.

Three-Water Differential Parallel Conductivity Saturation Model of Low-Permeability Tight Oil and Gas Reservoirs

Addressing the poor performance of existing logging saturation models in low-permeability tight sandstone reservoirs and the challenges in determining model parameters, this study investigates the pore structure and fluid occurrence state of such reservoirs through petrophysical experiments and digital rock visualization simulations. The aim is to uncover new insights into fluid occurrence state and electrical conduction properties and subsequently develop a low-permeability tight sandstone reservoir saturation model with easily determinable parameters. This model is suitable for practical oilfield exploration and development applications with high evaluation accuracy. The research findings reveal that such reservoirs comprise three types of formation water: strongly bound water, weakly bound water, and free water. These types are found in non-connected micropores, poorly connected mesopores where fluid flow occurs when the pressure differential exceeds the critical value, and well-connected macropores. Furthermore, the three types of formation water demonstrate variations in their electrical conduction contributions. By inversely solving rock electrical experiment data, it was determined that for a single sample, the overall cementation index is the highest, followed by the cementation index of pore throats containing strongly bound water, and the lowest for the pore throats with free water. Building on the aforementioned insights, this study develops a parallel electrical pore cementation index term, ϕm′, to account for the differences among the three types of water and introduces a parallel electrical saturation model suitable for logging evaluation of low-permeability tight oil and gas reservoirs. This model demonstrated positive application effects in the logging evaluation of low-permeability tight gas reservoirs in a specific basin in the Chinese offshore area, thereby confirming the advantages of its application.

An Algorithm for Soft Sensor Development for a Class of Processes with Distinct Operating Conditions.

Soft sensors are increasingly being used to provide important information about production processes that is otherwise only available through off-line laboratory analysis. However, usually, they are developed for a specific application, for which thorough process analysis is performed to provide information for the appropriate selection of model type and model structure. Wide industrial application of soft sensors, however, requires a method for soft sensor development that has a high level of automatism and is applicable to a significant number of industrial processes. A class of processes that is very common in the industry are processes with distinct operating conditions. In this paper, an algorithm that is suitable for the development of soft sensors for this class of processes is presented. The algorithm possesses a high level of automatism, as it requires minimal user engagement regarding the structure of the model, which makes it suitable for implementation as a customary industrial solution. The algorithm is based on a radial basis function artificial neural network, and it enables the automatic selection of the model structure and the determination of model parameters, only based on the training data set. The testing of the presented algorithm is done on the cement production process, since it represents a process with distinct operating conditions. The results of the test show that, besides providing a high level of automatism in model development, the presented algorithm generates a soft sensor with high estimation performance.