Parameterization Procedure Research Articles

An Improved Mathematical Model Derivation Based on Circuitry Approach for Crystalline Silicon Photovoltaic Module

This paper revises the five-parameter model, an approach that contributes the fundamental knowledge on performing accurate mathematical modelling for most of the commercially-available photovoltaic cells. However, such model can be further improved in order to increase the modelling accuracy while reducing the required modelling parameters at the same time. Improvement is made through formula derivation for photo-generated current and diode saturation current, while the remaining parameters (series resistance, shunt resistance, and diode ideality factor) remained un-managed for the parameterisation procedure. The derivations presented in this paper are direct, yet such procedures are frequently overlooked by others. The comparison between conventional and proposed modelling methods is presented. The methodology of this work is presented through MATLAB script demonstrated on the measured field data for 70W mono and poly-crystalline silicon photovoltaic modules. The performed methodology justifies that formula derivation can be applied for photo-generated and diode saturation current parameters that originated from five-parameter model. Such approach simplifies the works of parameterising the theoretical model matches with the experimental I-V curve. Generally, the work of this paper contributes to the mathematical modelling of photovoltaic module, simulation of experimental I-V curve result, and interactive education tool.

Beyond forest succession: A gap model to study ecosystem functioning and tree community composition under climate change

Abstract Climate change impacts forest functioning and dynamics, and large uncertainties remain regarding the interactions between species composition, demographic processes and environmental drivers. There are few robust tools available to link these processes, which precludes accurate projections and recommendations for long‐term forest management. Forest gap models present a balance between complexity and generality and are widely used in predictive forest ecology. However, their relevance to tackle questions about the links between species composition, climate and forest functioning is unclear. In this regard, demonstrating the ability of gap models to predict the growth of forest stands at the annual parameterization scale resolution—representing a sensitive and integrated signal of tree functioning and mortality risk—appears as a fundamental step. In this study, we aimed at assessing the ability of a gap model to accurately predict forest growth in the short term and potential community composition in the long term, across a wide range of species and environmental conditions. To do so, we present the gap model ForCEEPS, calibrated using an original parameterization procedure for the main tree species in France. ForCEEPS was shown to satisfactorily predict forest annual growth (averaged over a few years) at the plot level from mountain to Mediterranean climates, regardless of the species. Such an accuracy was not gained at the cost of losing precision for long‐term predictions, as the model showed a strong ability to predict potential community compositions. The mechanistic relevance of ForCEEPS parameterization was explored by showing the congruence between the values of key model parameter and species functional traits. We further showed that accounting for the spatial configuration of crowns within forest stands, the effects of climatic constraints and the variability of shade tolerances in the species community are all crucial to better predict short‐term productivity with gap models. Synthesis. The dual ability of predicting short‐term functioning and long‐term community composition, as well as the balance between generality and realism (i.e. predicting accuracy) of the new generation of gap models may open great perspectives for the exploration of the biodiversity–ecosystem functioning relationships, species coexistence mechanisms and the impacts of climate change on forest ecosystems. A free Plain Language Summary can be found within the Supporting Information of this article.

A Bayes-inspired theory for optimally building an efficient coarse-grained folding force field.

Because of their potential utility in predicting conformational changes and assessing folding dynamics, coarse-grained (CG) RNA folding models are appealing for rapid characterization of RNA molecules. Previously, we reported the iterative simulated RNA reference state (IsRNA) method for parameterizing a CG force field for RNA folding, which consecutively updates the simulation force field to reflect marginal distributions of folding coordinates in the structure database and extract various energy terms. While the IsRNA model was validated by showing close agreement between the IsRNA-simulated and experimentally observed distributions, here, we expand our theoretical understanding of the model and, in doing so, improve the parameterization process to optimize the subset of included folding coordinates, which leads to accelerated simulations. Using statistical mechanical theory, we analyze the underlying, Bayesian concept that drives parameterization of the energy function, providing a general method for developing predictive, knowledge-based, polymer force fields on the basis of limited data. Furthermore, we propose an optimal parameterization procedure, based on the principal of maximum entropy.

The optimal detuning approach based centralized control design for MIMO processes

This manuscript introduces an optimal detuning approach for designing a centralized PI control system for multi-input multi-output (MIMO) processes. Based on the approach, two multivariable PI controller designs are proposed in this manuscript. The proposed approach formulates the centralized PI controller design problem in an optimization framework and transforms it into an equivalent detuning parameter(s) design problem. While the centralized controller design with the proposed 1-Optimal Detuning Parameter (ODP) method is carried out as a multi-stage problem, the proposed 2-ODP method formulates the controller design as a single-stage optimization problem. An effective transfer function (ETF) parameterization followed by controller synthesis using the IMC theory and further the optimal detuning comprises the various stages in 1-ODP design. In this regard, a novel ETF parameterization procedure for large scale processes or systems with higher-order elements is presented in this manuscript. Contrary to the centralized controller design in the kp,ki space, where the dimensionality of the optimization problem blows at O(2n2), the proposed 1-ODP and 2-ODP design methods always aim at solving a uni- and bi-dimensional optimization problem, respectively, irrespective of the dimensionality of the MIMO process. Hence, the proposed method is easily applicable even to high-dimensional MIMO processes. Several illustrative industrial MIMO systems are considered to demonstrate the applicability of the proposed methods to highly interacting and large scale processes. The simulation studies show that the proposed methods performs better as compared to the other centralized PI controller designs. Even with parameter variations, the proposed methods give satisfactory closed-loop performance. Further, robust stability analysis for the proposed designs is performed by considering multiplicative input and output uncertainties.

Linkage Between Micro- and Nano-Raman Spectroscopy of Defects in Graphene

On nanomaterials characterization, the evolution from the broadly utilized micro-Raman spectroscopy to a nanoscale regime is taking place with the improvements in tip-enhanced Raman spectroscopy (TERS). It is not clear, however, to which extent protocols developed within the diffraction-limited far-field configuration apply to the near-field regime. Defects in graphene nanoflakes are investigated in this work in both micro and nano regimes, showing that the Raman characteristics utilized to quantify defects in the far-field regime actually change in the presence of the TERS tip, generating incompatible results. The micro-to-nano spectral mismatch can be modeled using a theory of spatial coherence in near-field Raman scattering, from which a parameterization procedure can be derived in order to obtain consistent results. The incompatibilities observed here for graphene should also happen in other structures relevant to nanoscience and nanotechnology when explored in the nano-Raman regime, and they can be resolved similarly.

Research on parameterization and optimization procedure of low-Reynolds-number airfoils based on genetic algorithm and Bezier curve

A systematic procedure of high-precision parameterization and multi-objective optimization for airfoils was proposed in this paper in order to improve the aerodynamic performance under full working conditions. The Bezier curve was applied in the airfoil parameterization with the coordinates of the 8 Bezier control points chosen to be the design variables. The control points were initialized by self-programming software and then optimized by direct search method to guarantee the fitting precision. The multi-objective optimization of low-Reynolds-number airfoil E387 was executed through NSGA II based on the result from XFOIL calculation, with the increment and variance of lift-drag ratio chosen to be the objective functions. Two representative solutions were selected from the Pareto front, and the performances of the new airfoils were promoted in different ways. The lift-drag ratio of the optimized airfoil with smaller variance is increased uniformly under different attack angles and maintains the similar characteristics with the original one. For the optimized airfoil with larger variance, the distribution of lift-drag ratio relative to the attack angle is altered obviously, and the performance under small attack angles and stall conditions are significantly ameliorated. The introduction of variance control in the objective function enables the differentiation of the optimized solutions for different requirement in engineering application.

Az emberi test kültéri hőterhelésének a humán állapothatározóktól való függése

A new clothing resistance model for estimating outdoor thermal load of a walking individual has been proposed by our research team. The model is used as a tool to analyse the relationship between clothing resistance (estimated by this new model) and body structural parameters in different weather conditions. More than 3000 children’s and adults’ body structural – BMI, relative fat mass (fatBMI) and relative muscle mass (muscleBMI) data, as well as simulated data of weather conditions having influence on thermal perception were used in the analysis.
 The relationship between BMI, fatBMI, muscleBMI and clothing resistance showed very strong relations both in simulated winter and summer conditions, in both sexes in almost every age-group. The bigger the BMI, fatBMI, muscleBMI, the smaller clothing resistance (smaller heating demand) was estimated in winter weather conditions, while the bigger clothing resistance (smaller cooling demand) was estimated in summer weather conditions. Females’ clothing resistance was higher in winter weather conditions, while was smaller in summer conditions than the clothing resistance of their male age-peers having the same relative body mass, fat mass or muscle mass. BMI showed the strongest relations with clothing resistance both in summer and winter thermal stresses. The preliminary results of the project confirmed that age, gender, BMI and presumably relative fat and muscle mass should be built in the procedure of parameterization of clothing resistance.

Mathematical modeling and human gait recovering with electromechanical exoskeleton

The mathematical model for dynamical analysis and recovering of the human gait by the electromechanical exoskeleton is built. Human locomotor apparatus is modeled by planar system of nine rigid bodies, and exoskeleton by pair of three-link hinge levers, connected to the lower extremities. The exoskeleton is controlled by electromechanical devices: the electrical power, which is supplied to the electric motor input, provides generating of the necessary torques in the system’s joints. Assuming, that the level of the muscle forces in the primary human legs joints (hip, knee and ankle) is small and not sufficient for performing locomotor functions, the problem for determining exoskeleton control, which provide for biotechnical system anthropomorphic movement is formulated. The algo­rithm for construction of approximate solution, based on a procedure of parameterization of generalized coordinates of the mechanical system by a set of cubic smoothing splines, conception of reverse dynamic problems and numerical methods of nonlinear programming is built. Cite as: M. V. Demydyuk, B. A. Lytvyn, “Mathematical modeling and human gait recovering with electromechanical exoskeleton,” Prykl. Probl. Mekh. Mat. , Issue 17, 147–159 (2019) (in Ukrainian), https://doi.org/10.15407/apmm2019.17.147-159

Assembly pin factor parameterization method based on the proper orthogonal decomposition

The proper orthogonal decomposition (POD) is introduced into the assembly pin factor parameterization. The decomposition is performed first to the pin factors with specific discrete state parameters to capture the spatial characteristic of pin factors. Then the POD basis are stored, and the POD coefficients are functionalized according to the state parameters. While the few-group constants are needed in the core calculation, the functionalized POD coefficients are calculated. Then the required pin factors are obtained by multiplying the POD basis and the functionalized POD coefficients. This assembly pin factor parameterization procedure based on the POD is carried out and verified based on the assembly in the BEAVRS benchmark core. Moreover, the comparison is performed between the POD method and the traditional method for the assembly pin factor parameterization. The numerical results show that this procedure based on the POD is feasibility and effective with high accuracy and calculation speed.

Parameterization and Validation of an Electrochemical Thermal Model of a Lithium-Ion Battery

The key challenge in developing a physico-chemical model is the model parameterization. The paper presents a strategic model parameterization procedure, parameter values, and a developed model that allows simulating electrochemical and thermal behavior of a commercial lithium-ion battery with high accuracy. Steps taken are the analysis of geometry details by opening a battery cell under argon atmosphere, building upon reference data of similar material compositions, incorporating cell balancing by a quasi-open-circuit-voltage experiment, and adapting the battery models reaction kinetics behavior by comparing experiment and simulation of an electrochemical impedance spectroscopy and hybrid pulse power characterization. The electrochemical-thermal coupled model is established based on COMSOL Multiphysics® platform (Stockholm, Sweden) and validated via experimental methods. The parameterized model was adopted to analyze the heat dissipation sources based on the internal states of the battery at different operation modes. Simulation in the field of thermal management for lithium-ion batteries highly depends on state of charge-related thermal issues of the incorporated cell composition. The electrode balancing is an essential step to be performed in order to address the internal battery states realistically. The individual contribution of the cell components heat dissipation has significant influence on the temperature distribution pattern based on the kinetic and thermodynamic properties.

Development of the method of structural and parametric synthesis of the Quanton diagnostic and health complex

The synthesis method based on the use of information invariants is proposed, and structural-parametric synthesis of the Quanton diagnostic and health complex is performed. Structural and parametric optimization of the complex is carried out according to the performance criterion. As information invariants, complete (within the accepted classification) sets of methods to obtain the functional properties of the complex, phase cycles of the life cycle, structures of technical subsystems and methods for controlling the technicalization levels, productivity and energy efficiency of processes are used. The sets of methods to obtain the functional properties of the complex and phase cycles of the life cycle are formed by elementwise complication of the corresponding attributes. The set of structures of technical subsystems corresponding to certain levels of technicalization of functions is determined on the basis of the periodic system of technical elements. Complete sets of possible structural solutions for methods of controlling the productivity and energy efficiency of processes are obtained by the topological product of the sets of types of objects by the types of methods for ensuring the required properties or qualities of objects. For each structurally different variant, the usual object parameterization procedure and the system of dependencies of the deductive parametric optimization problem are applied. The system of dependencies is a specific case of parametric information invariants. The dependencies are specified using the information about the necessary source data and target transformations occurring in the Quanton complex during the interaction of subsystems. The algorithm for finding an extremely effective solution is step-by-step. This algorithm assumes a step-by-step determination of the optimal process performance parameters within the limiting contours and subsequent improvement of energy efficiency and quality. Due to the use of complete sets of process structures, elements and discrete-continuum procedure of search for the optimal solution, the integration of the optimization of technical innovation is achieved.

Application of the Corresponding-State Law to the Parametrization of Statistical Associating Fluid Theory (SAFT)-Type Models: Generation and Use of “Generalized Charts”

Most of the Statistical Associating Fluid Theory (SAFT) and cubic equations of state (EoS) for nonassociating pure components obey the three-parameter corresponding-state law, meaning that the knowledge of three component-specific properties is a prerequisite to apply an EoS to a given pure species. Here, the methodology used to attribute values to EoS parameters is called “parameterization procedure”. In this Article, it is shown that generalized charts, derived from the corresponding-state theory, can be used advantageously to parametrize SAFT models. SAFT EoS is a well-established class of models frequently used for process simulation. Depending on the EoS parameter set selected, most of SAFT EoS are likely to predict unrealistic phenomena (mainly, the presence of multiple critical points and three-fluid phase equilibrium regions in pure-component phase diagrams). Generalized charts can be used to detect whether such unrealistic phenomena affect pure-component phase diagrams in the temperature and pressure domains of interest. As a second application, it is proposed to parametrize SAFT EoS in the same spirit as cubic EoS: the three SAFT input parameters are fixed in order to exactly reproduce the experimental critical temperature, critical pressure, and one point of the vaporization curve through the acentric factor. It is shown that the procedure is simple to implement and opens the door to a large industrialization of SAFT EoS (i.e., the possibility to determine SAFT input parameters for any compound using a universal and univocal method).

Isogeometric configuration design sensitivity analysis of geometrically exact shear-deformable beam structures

In this paper, using an isogeometric approach, a continuum-based adjoint configuration design sensitivity analysis (DSA) method is presented for three-dimensional finite deformation shear-deformable beam structures. A geometrically exact beam model together with a multiplicative update of finite rotation by an exponential map of a skew-symmetric matrix is utilized. The material derivative of the orthogonal transformation matrix can be evaluated at final equilibrium configuration, which enables to compute design sensitivity using the tangent stiffness at the equilibrium without further iterations. We also present a procedure of explicit parameterization of initial orthonormal frame using the smallest rotation (SR) method within the isogeometric analysis framework. Furthermore, it is shown that for curve entities embedded to a smooth surface, the convected basis of the surface can be effectively utilized for reference orthonormal frames in the SR method. Various numerical examples including pressure loads and nonhomogeneous kinematic boundary conditions in built-up structures demonstrate the effectiveness of the developed DSA method.

A self-propelled robotic system with a visco-elastic joint: dynamics and motion analysis

This paper studies the dynamics and motion generation of a self-propelled robotic system with a visco-elastic joint. The system is underactuated, legless and wheelless, and has potential applications in environmental inspection and operation in restricted spaces which are inaccessible to human beings, such as pipeline inspection, medical assistance and disaster rescue. Locomotion of the system relies on the stick–slip effects, which interacts with the frictional force of the surface in contact. The nonlinear robotic model utilizes combined tangential-wise and normal-wise vibrations for underactuated locomotion, which features a generic significance for the studies on self-propelled systems. To identify the characteristics of the visco-elastic joint and shed light on the energy efficacy, parameter dependences on stiffness and damping coefficients are thoroughly analysed. Our studies demonstrate that the dynamic behaviour of the self-propelled system is mainly periodic and desirable forward motion is achieved via identification of the variation laws of the control parameters and elaborate selection of the stiffness and damping coefficients. A motion generation strategy is developed, and an analytical two-stage motion profile is proposed based on the system response and dynamic constraint analysis, followed by a parameterization procedure to optimally generate the trajectory. The proposed method provides a novel approach in generating self-propelled locomotion, and designing and computing the visco-elastic parameters for energy efficacy. Simulation results are presented to demonstrate the effectiveness and feasibility of the proposed model and motion generation approach.

Systematic parameterization procedure to develop force fields for molecular fluids using explicit water

The three steps systematic parameterization procedure, 3SSPP, to develop force fields of polar liquids proposed by our group (J. Chem. Theory Comput.2015, 11, 683) is reviewed. The method allows obtaining independently the charge distribution and Lennard-Jones parameters of pure components if the experimental dielectric constant, surface tension and liquid density are used as target properties. Different methods to determine the partial atomic charges from electronic structure calculations of isolated polar molecules are analyzed. It is shown that the charge distribution plays an important role in several properties of pure components and binary mixtures, including solubility. Molecular dynamics simulations of 12 typical polar liquids in aqueous solutions show that the TraPPE-UA force field, in general, underestimates the experimental solubility in a liquid-liquid equilibrium at room conditions. The 3SSPP is used to reparameterize the TraPPE-UA non-bonding parameters of liquid 1-propanol, 2-pentanone and methyl acetate using scaled atomic charges from the Hirshfeld partition scheme. The new parameters predict the correct solubility of 1-propanol in water but fail to reproduce that of the other two molecules. The new parameterization procedure, 4SSPP, is extended to include the solubility as a target property. The solubility is reproduced by modifying the charge distribution obtained for the pure components keeping constant the molecular dipole moment and Lennard-Jones parameters. The method is applied to 2-pentanone and methyl acetate as pure components and their mixtures with water. The target properties of the pure components are almost unaffected after the refining process of the charge distribution. The liquid-vapor phase diagram is also determined for a single component. The results show that the use of an explicit solvent, water in this case, in a simulation is a good way to improve, with a small additional computational cost, the force field parameters of pure components to be used in computer simulations in multicomponent systems. The new parameters are used to obtain the liquid density of 1-propanol/methanol and methyl acetate/methanol mixtures and excellent agreement with experimental data is found.

GCA-EOS extension to mixtures of phenol ethers and derivatives with hydrocarbons and water

Anisol and its derivatives are typically used in the flavoring and fragrance industry, and they are also considered as additives for fuels and solvents for separation processes. Despite their growing importance, due to the development of biomass conversion routes, only few authors have modeled their phase behavior, which is required to assess industrial applications. In this work, we extend the Group Contribution with Association Equation of State (GCA-EOS) to multiphase equilibria of phenol ethers. We investigate pure anisole and its derivatives, as well as their mixtures with linear and cyclic alkanes, alkenes, aromatic hydrocarbons, and water. To fit the model parameters and assess its predictive capacity, we assemble an experimental database with the vapor pressure of 8 phenol ethers and 283 binary equilibrium datapoints. The parameterization procedure aims to reduce the required number of binary interaction parameters, avoiding to over correlate the model. The results show that GCA-EOS predicts the pure vapor pressure data with an average deviation of 3%, as well as the VLE of binary mixtures with similar accuracy. On the other hand, the model is also able to describe the mutual solubility of methoxy aromatic compounds with water.

A holistic parametric design attempt towards geometric modeling of the lumbar spine

ABSTRACTBiomechanical studies based on anatomical meshes are often generated with various segmentation methods; hence they are fixed, preventing tuning of morphometrical parameters. The primary objective of this study was to develop a methodology that would allow construction of a robust and high-fidelity CAD model from the CT scans of an individual. In this framework, a holistic approach was adopted for the design of the lumbar spine. This involved the breaking-up of the design intent into three levels. From top-down, a master layout sketch of the vertebral curve was used to drive the entire model at the highest level. Secondly, each vertebra was divided into two parts in order to simplify the parameterization procedure. Thirdly, a spiral curve was introduced in order to facilitate the placement of the facet joints. This way, a statically-determinate vertebral stacking sequence during assembly was realized. Hausdorff distance between the CAD and CT meshes was used to evaluate the accuracy of the model. In addition, mean and standard deviation of the errors were also calculated. A new generic lumbar vertebral CAD model was successfully built and tested. This model could lead to dramatic reductions in both time and effort required to prepare patient-specific biomechanical models.

Towards revised physically based parameter estimation methods for the Pitman monthly rainfall-runoff model

This paper presents a preliminary stage in the development of an alternative parameterisation procedure for the Pitman monthly rainfall runoff model which enjoys popular use in water resource assessment in Southern Africa. The estimation procedures are based on the premise that it is possible to use physical basin properties directly in the quantification of the soil moisture accounting, runoff, and recharge and infiltration parameters. The results for selected basins show that the revised parameters are at least as good as current regionalised sets or give satisfactory results in areas where no regionalised parameters exist.

Comprehensive evaluation and parametric sensitivity of interatomic potential models for diffusion kinetics of Cr2O3 in molecular dynamics

While molecular dynamics (MD) has proven to be a promising approach to investigate the diffusion properties, the grand challenge resides in evaluating potential model parameters to accurately replicate experimentally measured properties. The Buckingham potential model with Columbic interaction is widely employed in MD simulations of chromia (Cr2O3) systems, as it allows for reasonable computational cost and accuracy. However, considering the well-known limitation of classical potential models in simultaneous reproduction of various physical phenomena, further comprehensive evaluation of the potential is required for calculation of diffusion properties. In this study, we benchmark the performance of three different Buckingham models with the experimental data by calculating structural, thermodynamic, and mechanical properties of defect-free Cr2O3, and diffusion properties of Cr2O3 with vacancy defects. Available Buckingham models display limited accuracies, consolidating the necessity of retraining the potential parameters for all properties impacting the diffusion dynamics. Oversimplification in parameterization procedures is suggested to impede the universal performance in property reproduction. This research also demonstrates effective guidelines for choosing a proper parameter set of current Buckingham potential for MD simulation with Cr2O3 depending on properties and for potential reparameterization.

Parameterization procedure of a powertrain model for a driving simulator

The automotive industry is facing a major challenge to reduce environmental impacts. As a consequence, the increasing diversity of powertrain configurations put a demand on testing and evaluation p ...