Practical Modeling Approach Research Articles

Estimation of space deformation model for non-stationary random functions

Stationary Random Functions have been successfully applied in geostatistical applications for decades. In some instances, the assumption of a homogeneous spatial dependence structure across the entire domain of interest is unrealistic. A practical approach for modeling and estimating non-stationary spatial dependence structure is considered. This consists in transforming a non-stationary Random Function into a stationary and isotropic one via a bijective continuous deformation of the index space. So far, this approach has been successfully applied in the context of data from several independent realizations of a Random Function. In this work, we propose an approach for non-stationary geostatistical modeling using space deformation in the context of a single realization with possibly irregularly spaced data. The estimation method is based on a non-stationary variogram kernel estimator which serves as a dissimilarity measure between two locations in the geographical space. The proposed procedure combines aspects of kernel smoothing, weighted non-metric multi-dimensional scaling and thin-plate spline radial basis functions. On a simulated data, the method is able to retrieve the true deformation. Performances are assessed on both synthetic and real datasets. It is shown in particular that our approach outperforms the stationary approach. Beyond the prediction, the proposed method can also serve as a tool for exploratory analysis of the non-stationarity.

Concept and application of ideal protein for pigs.

Knowledge about the amino acid requirements and the response of pigs to the amino acid supply is essential in feed formulation. A deficient AA supply results in a reduction in performance while an oversupply is costly and leads to excessive nitrogen excretion with a potentially negative environmental impact. Amino acid requirements are determined to a large extent by the protein deposition in the body and, for lactating sows, by the protein exported in the milk. The concept of ideal protein was developed more than 50 years ago and refers to a protein with an amino acid profile that exactly meets the animal’s requirement so that all amino acids are equally limiting for performance. Because Lys typically is the first-limiting amino acid, the ideal amino acid profile is often expressed relative to Lys. Although the ideal protein profile is often assumed to be constant for a given production stage, (small) changes in the ideal protein profile can occur within a production stage. This can be caused by changes in the relative contribution of the different components of amino acid requirements during the productive life on the animal (e.g. changes in the relative contribution of growth and maintenance). Amino acids requirements can be determined experimentally using dose–response studies. The design of the study, the chosen response criterion, and the statistical model affect the requirement estimate. Although considerable experimental work has been carried out to determine the requirements for Lys, Met, Thr, and Trp in growing pigs (and to a lesser extent in sows), little is known about the requirements for the other essential amino acids. Experimental dose–response studies generally focus on the requirement and less on the overall response (i.e. what are the consequences of an amino acid deficiency?). This latter aspect is, to some extent, accounted for in modelling approaches that quantify the response of the animal to the amino acid supply in a dynamic way. The paper describes the origin of ideal protein and illustrates how fundamental concepts of amino acid nutrition have been integrated in practical modeling approaches for the nutrition of growing pigs and sows.

Building neighborhood emerging properties and their impacts on multi-scale modeling of building energy and airflows

This paper provides a critical review on the building neighborhood properties influencing the energy and airflows in urban neighborhoods. Specifically, the review focus is on the multi-scale modeling required to quantify this influence of the building neighborhood properties on the energy consumption in buildings. The energy consumption patterns of buildings located in dense city centers are highly dependent on the surrounding urban neighborhood, compared to the low density, suburban/rural regions, where the building energy consumption patterns are similar to an isolated building energy consumption patterns. Due to the complex nature of the outdoor airflow around the buildings in urban neighborhoods, a practical modeling approach utilizes multi-scale modeling to account for different spatial and temporal scales for the relevant transport processes. Specifically, this modeling approach aims to identify the most important neighborhood properties influencing building energy consumption. The urban morphology parameters, such as the urban plan area density, frontal area density, and mean height of the buildings represent successful examples of emerging properties suitable for development of generalized solutions and physical models at the neighborhood scale. This paper also reviews different modeling approaches that account for the impacts of the urban neighborhood properties on the thermo-fluid property of the air, surfaces, and sky in the built environment as the required inputs for accurate assessment of building energy consumption. Furthermore, these emerging properties of urban neighborhoods directly affect (1) the mitigation strategies for a better adaptation, (2) design performance metrics of neighborhoods for the green building rating systems, and (3) socio-environmental factors.

Modeling and implementation of sequencing of tasks to Maximize the Processing in an organization

The main objective of this work is to conceive a practical approach to improve customer’s satisfaction which is generally considered as the pillar of the development of customer fidelity for the company. It is necessary to have a platform which we master to manage to satisfy the customer by studying its needs, by having the capacity to be close and serving him for the shortest deadlines.The waiting time before being served is systematically badly noted by the customers and can cause their dissatisfactions. For that, it is necessary to find a way to decrease the dissatisfaction of the customer by improving the service.We propose in this work, a simple and practical approach for modeling and implementation of a sequencing of tasks to maximize the processing in an organization. This approach respects the constraints of the organization and eliminates any shape of wasting of time at the level of service. She can be personalized for any company, as long as an organizational structure including the actors is defined, the authorities as well as the skills required for every participant in the organization.The problem is mathematically modeled by an integer linear programming and in series solved numerically by respecting rules of priority at the level of the departments. At the end, practical examples to illustrate the work are given.

Microscopic Dynamics of Water and Hydrocarbon in Shale-Kerogen Pores of Potentially Mixed Wettability

Summary Distribution of alkanes and water in organic pores of shale, referred to as kerogen, is essential information required for the estimation of shale-reservoir oil and gas in place, adsorption of hydrocarbon, and fate of hydraulic-fracture water. A practical modeling approach is presented for the proper description of the kerogen pore systems with different mixed wettability, surface roughness, tortuous paths, and material disorder. Three kerogen models—activated kerogen, kerogen free of activated sites, and graphite-slit pore—with proper surface-oxidized functional groups and high-temperature and pressure maturation are constructed by simulation. Distribution of octane and water in the organic pores of these models is predicted by molecular dynamics (MD) simulation. The results from our studies underscore the need for accurate characterization of kerogen pore systems in terms of the pore morphology, level of surface activation, and pore size. The improved kerogen models constructed to structurally resemble real organic materials have the potential to enable a better understanding of the placement, distribution, and trapping mechanisms of hydraulic-fracture water in shales. We demonstrate that depending on the maturity of the kerogen within organic-rich shales, organic pore systems may have mixed-wet characteristics and may create opportunities for water entrapment. The differences in the uptake of water are shown to be a function of the existence of oxygenated functional groups. In addition, the adsorption characteristics of alkanes in pores characterized by surface roughness are shown to be significantly different from those observed in the graphite-slit pore model. Our results indicate that careful consideration of the pore morphology is merited when estimating hydrocarbons in place with the Langmuir monolayer-adsorption theory.

A practical approach for finite-element modeling of transfer length in pretensioned, prestressed concrete members using end-slip methodology

This paper presents a numerical modeling approach that accounts for slip between prestressing strands and the surrounding concrete within the transfer zone. The objective of the study was to develop a modeling approach that can accurately and efficiently predict member behavior based on specified transfer lengths. The modeling approach uses three components: a matrix of solid elements to represent the concrete, truss elements to represent the prestressing strand, and nonlinear springs accounting for the interface between the prestressing strand and surrounding concrete. The force-versus-displacement curves for the nonlinear springs are based on the known relationship between end slip and transfer length. The results of 23 numeri- cal models are included and compared with experi- mental data from corresponding test specimens. The study confirms the practicality and accuracy of the modeling approach to predict member behavior based on specified transfer lengths.

Frequency-Dependent Modeling of Transformer Winding Impedance From <formula formulatype="inline"><tex Notation="TeX">${\rm R}(\omega)/{\rm L}$</tex></formula> Measurements

We describe a practical modeling approach for including the frequency dependency of transformer winding resistance in Electromagnetic Transients Program-type simulation tools, based on typical curves of R(ω)/L ratios. From the given resistance component, the inductance component is calculated via Kramers-Kronig dispersion relations. The resulting impedance is subjected to low-order rational approximation impedance by a Foster equivalent circuit. The proposed model can be easily applied to any transformer in the range of 20-500 MVA by rescaling the given Foster circuit parameters by the 50-Hz winding resistance.

A Practical Approach for Identity-Embodied 3D Artistic Face Modeling

This paper describes a practical technique for 3D artistic face modeling where a human identity can be inserted into a 3D artistic face. This approach can automatically extract the human identity from a 3D human face model and then transfer it to a 3D artistic face model in a controllable manner. Its core idea is to construct a face geometry space and a face texture space based on a precollected 3D face dataset. Then, these spaces are used to extract and blend the face models together based on their facial identities and styles. This approach can enable a novice user to interactively generate various artistic faces quickly using a slider control. Also, it can run in real-time on an off-the-shelf computer without GPU acceleration. This approach can be broadly used in various 3D artistic face modeling applications such as a rapid creation of a cartoon crowd with different cartoon characters.

Ontological characterization of functions: Perspectives for capturing functions and modeling guidelines

AbstractThe authors have been involved in ontological modeling of function for over 15 years. As an instance of the revisionary approach discussed in Vermaas's position paper, we have proposed an ontological definition of function and a modeling framework based on it, which has been deployed in industry. In addition, as an instance of the overarching approach, we have proposed a reference ontology of function that explains some kinds, definitions, and practical expressions of functions. In this paper, we explain our methodology in an overarching approach based onperspectives for capturing functions. When one captures a function of an artifact, one focuses on a specific aspect of the artifact from a specific perspective. In this paper, we conceptualize such perspectives behind the reference ontology. In addition, based on our experiences in deployment in an industrial setting, we report some solutions, such as ontological modeling guidelines, for overcoming some of the difficulties faced in the practical functional modeling approach described in Eckert's position paper. Our findings suggest that such solutions will help engineers to describe consistent functional models compliant with a single definition of function.

The component interaction network approach for modeling of complex thermal systems

A practical approach for the thermal modeling of complex thermal systems, called the component interaction network (CIN) is presented. Its stages are explained: description of the thermal system as a set of non-overlapping components and their interactions by heat and mass exchanges, modeling of components with different levels of precision using finite volumes and finite elements, modeling of interactions by conduction, convection, radiation and advection, time resolution scheme and simulation. Non-conventional notions of conditional existence of components or time events are introduced. The approach is illustrated with a simple example of an electric furnace. It is then applied to a rapid thermal processing (RTP) furnace and validated experimentally. The advantages of the CIN approach are demonstrated.

Magnetic Heating of Nanoparticles: The Importance of Particle Clustering to Achieve Therapeutic Temperatures.

Hyperthermia therapy for cancer treatment seeks to destroy tumors through heating alone or combined with other therapies at elevated temperatures between 41.8 and 48 °C. Various forms of cell death including apoptosis and necrosis occur depending on temperature and heating time. Effective tumoricidal effects can also be produced by inducing damage to the tissue vasculature and stroma; however, surrounding normal tissue must be spared to a large extent. Magnetic nanoparticles have been under experimental investigation in recent years as a means to provide a favorable therapeutic ratio for local hyperthermia; however, practical numerical models that can be used to study the underlying mechanisms in realistic geometries have not previously appeared to our knowledge. Useful numerical modeling of these experiments is made extremely difficult by the many orders of magnitude in the geometries: from nanometers to centimeters. What has been missing is a practical numerical modeling approach that can be used to more deeply understand the experiments. We develop and present numerical models that reveal the extent and dominance of the local heat transfer boundary conditions, and provide a new approach that may simplify the numerical problem sufficiently to make ordinary computing machinery capable of generating useful predictions. The objectives of this paper are to place the discussion in a convenient interchangeable classical electromagnetic formulation, and to develop useful engineering approximations to the larger multiscale numerical modeling problem that can potentially be used in experiment evaluation; and eventually, may prove useful in treatment planning. We cast the basic heating mechanisms in the framework of classical electromagnetic field theory and provide calibrating analytical calculations and preliminary experimental results on BNF-Starch® nanoparticles in a mouse tumor model for perspective.

Upscaled Modeling of CO2 Injection and Migration with Coupled Thermal Processes

A practical modeling approach for CO2 storage over relatively large length and time scales is the vertical-equilibrium model, which solves partially integrated conservation equations for flow in two lateral dimensions. We couple heat transfer within the vertical equilibrium framework for fluid flow, focusing on thermal processes that most impact the CO2 plume. We investigate a simplified representation of heat exchange that also includes transport of heat within the plume. In addition, we explore available CO2 thermodynamic models for reliable prediction of density under different injection pressures and temperatures. The model concept is demonstrated on simplified systems.

Modeling Approach Based on Modular Fuzzy Model

Fuzzy modeling is one of the most important techniques for nonlinear modeling. SIRMs (Single Input Rule Modules) has been studied as a useful modeling method for real-life applications such as control and pattern recognition. Although the SIRMs is a practical modeling approach based on fuzzy reasoning, its performance is adversely affected by high-dimensional or complicated characteristics of the problems. The modular fuzzy model is an extension of the SIRMs for overcoming such a performance problem. In this paper, we study a modeling approach based on the modular fuzzy model by extending the SIRMs architecture. We show that the construction of error objective functions for modeling the modular fuzzy model and the SIRMs affects the prediction performance of the model. Through numerical experiments on modeling problems and reinforcement learning problems, we study the model construction based on the error objective functions. We find that the error objective function should be selected according to the number of dimensions of projection in the modular fuzzy model.

A model to simulate special concentrically braced frames beyond brace fracture

SUMMARYSpecial concentrically braced frames (SCBFs) are commonly used as the lateral‐load resisting system in buildings. SCBFs primarily sustain large deformation demands through inelastic action in the brace, including compression buckling and tension yielding; secondary yielding may occur in the gusset plate and framing elements. The preferred failure mode is brace fracture. Yielding, buckling, and fracture behavior results in highly nonlinear behavior and accurate analytical modeling of these frames is required. Prior research has shown that continuum models are capable of this level of simulation. However, those models are not suitable for structural engineering practice. To enable the use of accurate yet practical nonlinear models, a research study was undertaken to investigate modeling parameters for line‐element models, which is a more practical modeling approach. This portion of the study focused on methods to predict brace fracture. A fracture modeling approach simulated the nonlinear, cyclic response of SCBFs by correlating onset of fracture to the maximum strain range in the brace. The model accounts for important brace design parameters including slenderness, compactness, and yield strength. Fracture data from over 40 tests was used to calibrate the model and included single‐brace component, single story frame, and full‐scale multistory frame specimens. The proposed fracture model is more accurate and simpler than other, previously proposed models. As a result, the proposed model is an ideal candidate for practical performance simulation of SCBFs. Copyright © 2012 John Wiley & Sons, Ltd.

Analysis of composite frame structures with mixed elements - state of the art

The paper presents a review of the application of the newly proposed mixed finite element model for seismic simulation of different types of composite frame structures. To evaluate the performance of the element, a comparison with displacement-based and force-based models is conducted. The study revealed that the mixed model is superior to the others in terms of both speed of convergence and numerical stability, and is therefore considered the most practical approach for modeling of composite structures. In this model, the element is derived using independent force and displacement shape functions. The nonlinear response of the frame element is based on the section discretization into fibers with uniaxial material models. The interfacial behavior is modeled using an inelastic interface element. Numerical examples to clarify the advantages of the model are presented for the following structural applications: anchored reinforcing bar problems, composite steel-concrete girders with deformable shear connectors, beam on elastic foundation elements, R/C girders strengthened with FRP sheets, R/C beam-columns with bond-slip, and prestressed concrete girders. These studies confirmed that the model represents a major advancement over existing elements in simulating the inelastic behavior of composite structures.

A Practical Modelling Approach for Stiction in Control Valves

Pneumatic control valves are widely used in the process industry and it has surprisingly received little attention until recently. The presence of non-linearities in a control valve limits the control loop performance. Stiction is the commonly existing valve problem. It is essential for one to know the dynamics of stiction, so that the relationship directly linked to the physical situation can be understood. Both physical model and empirical data driven models have been developed in the past decade to investigate the valve stiction behaviour. But, there is a need to better understanding of stiction physics through theoretical analysis as well as empirical investigations. A new nonlinear control valve model is developed and its effectiveness in simulating valve stiction is demonstrated. This paper focuses on the development of a MATLAB/Simulink model for control valve with stiction. The reliable stiction model that captures the stiction behaviour provides an important tool in order to investigate by analysis and simulation, the properties of stiction that are relevant to control design.

Rigorous optical modeling and optimization of thin‐film photovoltaic cells with textured transparent conductive oxides

ABSTRACTTypical thin‐film photovoltaic (PV) cells incorporate a textured transparent conductive oxide to enhance light trapping and efficiently harvest solar energy. Rigorous coherent optical simulations of these devices and a complete characterization of these textured films are a challenging problem because of the several orders of magnitude difference between the wavelengths of interest and the spatial dimension of the sample that needs to be evaluated. In this paper, a practical approach for rigorous and predictive modeling of optical properties of thin‐film PV cells incorporating a vast variety of light‐trapping structures including semi‐coherent textured films and patterned coherent structures is presented. In contrast to the existing semi‐empirical device models, it is demonstrated that the presented methodology can accurately predict the scattering properties of textured fluorine‐doped tin oxide and aluminum‐doped zinc oxide conductive transparent films. It is further shown that the optical response of single‐junction and tandem‐junction PV devices incorporating such films can also be predicted with good accuracy as compared with the measured results. Next, a methodology to identify the sufficient statistical fingerprints of semi‐coherent textured films that are needed to unambiguously predict the light propagation in thin‐film cells is presented. This comprehensive approach then lends itself to identifying the optimal surface morphology needed for strong light trapping. This rigorous approach automatically includes the effects of important loss mechanisms such as the surface plasmon‐enhanced absorption in textured metal surfaces that are otherwise very difficult to account for semi‐coherent approaches based on scalar scattering theory. Copyright © 2011 John Wiley & Sons, Ltd.

A novel structural modeling and analysis of VLSI interconnect with an RLC tree network system using a BG/SEBD approach

A practical and effective novel graphical structural modeling and analysis approach is presented. This approach is used for solving the state interactions modeling problem caused by the model approximations in VLSI interconnect for RLC tree network systems. The bond graph (BG) energy model with a simulink energybased block diagram (SEBD) algorithm is developed. The dynamic behaviors of an example of VLSI interconnect with a 20 th -order RLC tree are presented. Methods of sequent structuring and the delineation of dynamic interactions can be provided for users applying the BG/SEBD algorithms in the development of structural models. It is shown that the new BG/SEBD structural modeling approach requires neither mathematical higher-order reduction nor physically based model reduction. Therefore, useful information can be extracted from the BG/SEBD representation of physical RLC tree network systems. Both time-domain and frequency-domain simulation results are applied to analyze the dynamic response of energy-storing elements using BG/SEBD algorithm combined with Matlab/Simulink software. Finally, a causal analysis of the system zeros plot from the shortest causal path method is proposed, to predict the dynamic response of energy-storing elements and the system performance for design and verification purposes. The dynamic response outputs from different node points were revealed, and the obtained physical information is significant which suggests feasible directions for design (re-design) improvement toward better overall system performance.

A multi-scale approach to material modeling of fuel cell diffusion media

Effective diffusivity of porous media in fuel cells has been identified as a relevant material property in automotive applications. Pore-scale simulations utilizing imaging data sets of real materials or virtual model representations provide such diffusivity numbers. However, components like the microporous layer (MPL) or the gas diffusion electrode have not been covered adequately so far by efficient and practical modeling approaches due the small pore sizes and resulting Knudsen contribution to diffusion. In this publication we report the development of a numerical method which allows for the determination of binary diffusion coefficients for all Knudsen numbers and demonstrate the application to fuel cell diffusion media in a multi-scale modeling approach. For high Knudsen numbers effective diffusivity is determined by tracking a large number of individual molecules that collide with the pore walls. For low Knudsen numbers, effective diffusivity is determined by solving the Laplace equation on the pore space. Both contributions to the overall diffusivity are merged by applying Bosanquet’s formula. The resulting diffusivity can be used as an effective number for a microporous layer coating of a spatially resolved fibrous diffusion medium. As this multi-scale method is also based on a 3D voxel grid, we could study any distribution of the MPL on and inside the gas diffusion layer (GDL) with this model, e.g. cracks, different penetration depths, etc.

Development of a Practical Soot Modeling Approach and Its Application to Low-Temperature Diesel Combustion

The author's developed a practical soot model and implemented in the multidimensional computational fluid dynamics code, KIVA-3vr2 for use in low temperature diesel combustion simulations. The model framework is based on four fundamental steps: soot inception through a four-ring polycyclic aromatic hydrocarbon species, surface growth through acetylene, soot coagulation, and oxygen- and OH-induced soot oxidation. Diesel combustion was simulated by using a reduced n-heptane chemistry mechanism. A reduced polycyclic aromatic hydrocarbon chemistry mechanism was formulated from the literature and coupled with the n-heptane mechanism. Improvements were made in the chemistry mechanism for better predictions of ignition delay, liftoff length and soot precursor concentrations. The CHEMKIN-II code was used to solve the combustion chemistry. However, in order to reduce the computational time of the coupled soot and chemistry calculations, a semi-implicit solver was also implemented and used for the soot precursor species. Soot model performance and computational efficiency was evaluated by comparing the model predictions with available optical spray chamber experimental data. The model performance was also evaluated by comparing the model predictions with experimental results from a heavy-duty optical engine as well as light- and heavy-duty metal engines.