Methodology Of Mathematical Modeling Research Articles

Maximum constant boost approach for controlling quasi‐Z‐source‐based interlinking converters in hybrid AC–DC microgrids

This study presents the mathematical modelling and control design methodology of bidirectional quasi-Z-source inverters (qZSIs) for interlinking converter application in hybrid AC–DC microgrids. The proposed control scheme provides the maximum constant boost (MCB) control capability for the qZSI in both grid-connected and islanded modes of operation even in the presence of unbalanced AC loads. The proposed approach maintains the MCB without any additional control loop for regulating the voltage of the DC-side capacitor of the qZSI. This is done by determining the shoot through duty cycle of the qZSI based on the inverter modulation index. Moreover, maintaining the MCB condition, the proposed control scheme provides a high stability margin for the qZSI network. The effectiveness of the proposed method is demonstrated through simulation studies conducted on a typical AC–DC hybrid microgrid in MATLAB/Simulink environment for both islanded and grid-connected modes of operation.

Mathematical and Physical Modeling of the Rolling Process of Tapered Shafts for Aviation Purposes

One of the most promising methods for manufacture of axially symmetric parts such as disks or hollow shafts of gas turbine engines is local deformation using cold rolling. Physical and mathematical modeling can be quite effective for designing this class of equipment and process operations. This article presents the methodology and results of physical and mathematical finite element modeling of local deformation of parts such as a tapered cylinder fabricated from chromium steel alloy grade 11H11N2V2МF-Sh. Chemical elements in the alloy are designated by the letters which stand for: H – Chromium, N – Nickel, V – tungsten, M – molybdenum, F – vanadium, Sh – electroslag remelting. According to GOST 5632-72 (Russian standard), this type of nickel-chromium alloy consists of about 11 % of chromium, 1.5–2 % of tungsten and nickel, up to 1 % of molybdenum and vanadium, and 0.11 % of carbon, hundredths of one percent of phosphorus and sulfur. It is heat-resistant high-grade steel, which is used for the manufacture of parts operating unloaded at 900–1000 °C. The purpose of the paper is to analyze the process energy-power parameters and possible fracture of parts during deformation.

Новая концепция в профилактической ортопедии. Предупреждение патологических переломов проксимального отдела бедра путем хирургического армирования кости

The paper is dedicated to the pilot study of the surgical ways of preventing fractures of the hip
 among elderly patients suffering from various diseases that cause destructive‐dystrophic changes of the
 bony tissue (osteoporosis, cancer, cartilage and fibrous dysplasia, etc.) and are the cause of pathological fractures.
 The research involves the identification of people at risk, the development of preventive techniques
 and original reinforcement implant designs, the definition of a methodology for mathematical modeling and
 bench tests to determine the strength of the original implant reinforced hip. Studies have shown that the index
 of strain in the bone is considerably lower than on its surface (closer to longer‐term cortical layer), and when the load increases, it results in the development of a fracture. As a result of the reinforcement of the
 bone with different implants the index of strain at critical points is increases up to 11.6% ‐12.1. The bench
 tests proved that the preventive reinforcement to prevent fractures in low‐energy trauma can increase the
 strength of bone‐implant, depending on the type, design, quality, implant and method of its introduction up
 to 23‐93%.

Simulation of an Excavator Hydraulic System Using Nonlinear Mathematical Models

This paper describes a mathematical modelling methodology developed for the rapid simulation of an excavator hydraulic system. The modelling approach presented enables a reduction of the control system development time for a complete excavator, while providing accurate system dynamics. A tool for defining an appropriate control strategy is a key point for satisfying the need for systems with better energy-efficiency. Moreover, the model will be a significant support in investigating energy recovery solutions and evaluating the suitability of hybrid solutions (mechanical/hydraulic/electric). The hydraulic model, composed of the pump’s grey box model and the valve block white box model, has been validated on the basis of a set of experimental data collected on a test bench. The results of this study are presented in this paper.

Forecasting Influenza Epidemics in Hong Kong.

Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions.

Mathematical Approach to Security Risk Assessment

The goal of this paper is to provide a mathematical threat modeling methodology and a threat risk assessment tool that may assist security consultants at assessing the security risks in their protected systems/plants, nuclear power plants and stores of hazardous substances: explosive atmospheres and flammable and combustible gases and liquids, and so forth, and at building an appropriate risk mitigation policy. The probability of a penetration into the protected objects is estimated by combining the probability of the penetration by overcoming the security barriers with a vulnerability model. On the basis of the topographical placement of the protected objects, their security features, and the probability of the penetration, we propose a model of risk mitigation and effective decision making.

Mathematical Modeling and Analysis Methodology for Opportunistic Routing in Wireless Multihop Networks

Modeling the forwarding feature and analyzing the performance theoretically for opportunistic routing in wireless multihop network are of great challenge. To address this issue, a generalized geometric distribution (GGD) is firstly proposed. Based on the GGD, the forwarding probability between any two forwarding candidates could be calculated and it can be proved that the successful delivery rate after several transmissions of forwarding candidates is irrelevant to the priority rule. Then, a discrete-time queuing model is proposed to analyze mean end-to-end delay (MED) of a regular opportunistic routing with the knowledge of the forwarding probability. By deriving the steady-state joint generating function of the queue length distribution, MED for directly connected networks and some special cases of nondirectly connected networks could be ultimately determined. Besides, an approximation approach is proposed to assess MED for the general cases in the nondirectly connected networks. By comparing with a large number of simulation results, the rationality of the analysis is validated. Both the analysis and simulation results show that MED varies with the number of forwarding candidates, especially when it comes to connected networks; MED increases more rapidly than that in nondirectly connected networks with the increase of the number of forwarding candidates.

Development of approximate analytical method for modeling transient thermal processes using S-functions

A new methodology for mathematical modeling of transient thermal processes in structural components is proposed. It is based on the joint application of the structural method, the Bubnov-Galerkin method and S-functions to solving heat conduction problems with unsteady boundary conditions of the third kind. The analytic structures for solving these problems, accurately satisfying unsteady boundary conditions at any given time dependence of the heat transfer coefficient and ambient temperature are constructed. These qualitative features of the analytic structures for solving heat conduction problems have allowed first proposed solution methods to obtain approximate analytical solutions of these problems.Using the Bubnov-Galerkin method has allowed to reduce solving heat conduction problems with unsteady boundary conditions to solving the system of ordinary differential equations with respect to the unknown time-dependent coefficients of problem solution structures. Herewith, in the given system of ordinary differential equations, known time-dependent coefficients contain the heat transfer coefficients and the ambient temperature in analytical representation at their any given time dependence. This first allows one-dimensional unsteady heat conduction problems (infinite plates, cylinder, hollow sphere) to obtain an approximate analytical solution of unsteady heat conduction problems for those options of time dependence of the heat transfer coefficient and the ambient temperature, for which the operating method is not applicable.

Global Threat HIV/Aids: Burden, Trends And Hope

In this present review work, we seek to provide the basic characteristics of HIV/AIDS, brief statistics of HIV/ AIDS epidemic with respect to global level and Indian level and also with the description of controlling efforts against it. We also provided brief methodology of mathematical models of HIV/AIDS as hope for prevention strategies by shaping the disease burden and trends.

Seeking genetic signature of radiosensitivity--a novel method for data analysis in case of small sample sizes.

BackgroundThe identification of polymorphisms and/or genes responsible for an organism's radiosensitivity increases the knowledge about the cell cycle and the mechanism of the phenomena themselves, possibly providing the researchers with a better understanding of the process of carcinogenesis.AimThe aim of the study was to develop a data analysis strategy capable of discovering the genetic background of radiosensitivity in the case of small sample size studies.ResultsAmong many indirect measures of radiosensitivity known, the level of radiation-induced chromosomal aberrations was used in the study. Mathematical modelling allowed the transformation of the yield-time curve of radiation-induced chromosomal aberrations into the exponential curve with limited number of parameters, while Gaussian mixture models applied to the distributions of these parameters provided the criteria for mouse strain classification. A detailed comparative analysis of genotypes between the obtained subpopulations of mice followed by functional validation provided a set of candidate polymorphisms that might be related to radiosensitivity. Among 1857 candidate relevant SNPs, that cluster in 28 genes, eight SNPs were detected nonsynonymous (nsSNP) on protein function. Two of them, rs48840878 (gene Msh3) and rs5144199 (gene Cc2d2a), were predicted as having increased probability of a deleterious effect. Additionally, rs48840878 is capable of disordering phosphorylation with 14 PKs. In silico analysis of candidate relevant SNP similarity score distribution among 60 CGD mouse strains allowed for the identification of SEA/GnJ and ZALENDE/EiJ mouse strains (95.26% and 86.53% genetic consistency respectively) as the most similar to radiosensitive subpopulationConclusionsA complete step-by-step strategy for seeking the genetic signature of radiosensitivity in the case of small sample size studies conducted on mouse models was proposed. It is shown that the strategy, which is a combination of mathematical modelling, statistical analysis and data mining methodology, allows for the discovery of candidate polymorphisms which might be responsible for radiosensitivity phenomena.

Impact analysis of political decisions on business sustainability

In recent times, rapidly growing negative impacts on environment and new global trade conditions have caused international regulations and governmental laws to be more sensitive and strict about sustainability issues in their policy decisions. Therefore, a significant pressure on business has occurred to be more flexible to meet the revisions that affect industrial structures. Business sustainability has been affected easily by these revisions. This study explains the influence of regulations and policies on industries' strategic decisions simultaneously. In this paper, authors aim to develop a generic decision-making strategy to represent scenario generation mechanism by unified matrix for interactive impacts structure which can define the relations between criteria and functions of closed-loop supply chain from planning to the 3R activities (reuse, recover, recycle) level. In this scenario generation mechanism, the results could be applicable in analytical solution methodology of mathematical modelling. The parameters coefficients and the weights of each objective function in model are related to the range of evaluation results. The coefficients are defined by the probable range of results considering the effects of stakeholders in each function and sustainability issues from unified matrix.

Application of Taguchi Method and Surface Response Methodology to Evaluate Of Mathematical Models to Chip Deformation when Drilling With Coated and Uncoated Twist Drills

The paper deals with the methodology and suitability of mathematical models applying analysis of the signal-to-noise (S/N) ratio as well as analysis of variance (ANOVA) and surface response methodology (RSM) on effect of TiAlN coating on chip ratio when drilling with HSS Co5 twist drill with diameter of 8 mm. Experimental work was performed according to design of experiment (DoE) Taguchi method. Cutting speed vc (m/min) and feed f (mm/rev) were selected as control factors in three levels and chip ratio K was used as a response variable. The main aim of this study is to establish relevant methodology for short term testing and find adequate mathematical model for chip ratio parameter K = f(vc, f) as a function of cutting condition when drilling with PVD coated and uncoated tool. Statistical software Minitab 14 was employed to process and evaluate of experimental data. The effect of feed and cutting speed on chip ratio was investigated through analysis of the signal-to-noise (S/N) ratio and analysis of variance. Equations for chip ratio K as a function of control factors were developed.

NUMERICAL MODELLING FOR UNDERGROUND MINING RELATED GEOTECHNICAL ISSUES

Abstract Issues presented in this work relate to geotechnical problems that are specific to the mining areas. The paper discusses the methodology of mathematical and numerical modeling of these problems. Examples contained in the paper include: predicting the influence of mining exploitation on a detached building and evaluating the effectiveness of the building protection with the trench. Possible applications of numerical modeling as a tool to aid the continuous monitoring of the building state during the exploitation have also been discussed

Design and calibration of a new compact radiative heat-flux gauge (RHFG) for combustion applications

It is important to develop an inexpensive and robust gauge for measuring the contribution of radiation heat-flux component while operating in high temperature conditions without the need of cooling water supply. This work presents a new compact radiative heat-flux gauge (RHFG) for measuring the radiative heat-flux from combustion systems operating at high operating temperatures (∼1200K). Various types of total heat-flux meters (convective and radiative) are available for measuring heat-flux. In this study, pure radiative heat-flux measuring gauge (RHFG) is developed. Quartz plate is used as a window of RHFG acting as media to transfer pure radiative heat from the heat source. Copper plate is used as the heat sensing element. A thermocouple is brazed to the copper plate to measure the rate of heat transfer to the sensing element. The mathematical modeling, numerical analysis and construction methodology of RHFG is discussed. Initially, a large sized gauge (G1) is fabricated and calibrated with cone calorimeter. The measured response time of 670s is observed for G1. Numerical analysis is carried out to optimize the size of RHFG and reduce the response time. Four different gauges with various dimensions (G2, G3, G4 and G5) are analyzed numerically and a response time of 208, 17, 14 and 12s respectively is observed. The gauge, G5 is manufactured and calibrated with cone calorimeter with known radiative heat-flux and the experimental response time of 13s is observed. This RHFG is of low cost, simple to manufacture, rugged and requires no water cooling even for high temperature combustion applications.

Innovation and imitation effects' dynamics in technology adoption

PurposeThe purpose of this paper is to investigate longitudinal patterns of ICT and non‐ICT products' adoption over life cycles.Design/methodology/approachThe Bass diffusion model is used to discern distinctive changes in users' adoption behavior due to the innovation and the imitation effects.FindingsThe innovation effect is more influential for innovators and opinion leaders than it is for all adopters. However, it diminishes as time passes. Conversely, the imitation effect becomes a more powerful factor for the early majority, late majority and laggards. The imitation effect in the ICT industry is greater than that in the non‐ICT industry, revealing the high network effect in ICT diffusion.Research limitations/implicationsMobile phones are not the representative of all ICTs as the automobiles also do not represent all utility products. More ICT and conventional products need to be included and compared for greater generalization of the results from different countries.Practical implicationsBy identifying the strong innovation effect of a new product at the early stage of its adoption, and the social network effect in the acceleration of the adoption speed through massive numbers of imitating consumers, this research reveals the ever shrinking product life cycle and therefore the importance of continuous disruptive innovation as a competitive strategy for organizations.Originality/valueThe paper provides new theoretical insights into the technology adoption research by using a mathematical modeling methodology using real data. The study provides new insights into the strategic implications of innovation and imitation effects for technology service providers.

Optimal design of sustainable hydrogen networks

Hydrogen is widely used in modern oil refineries to remove the sulfur, nitrogen and aromatic contents of fuels. The existence of such contents would aggravate the greenhouse gas (GHG) emission of petrol fuels. The ultimate goal of massive hydrogen consumption in refineries is to cut down the GHG emission. However, current researches on hydrogen networks are focusing on reducing the cost of hydrogen consumption. The environmental impact of hydrogen consumption, especially the GHG emission, has not been considered yet. If the hydrogen supply network itself discharges too much CO2, then the significance of the hydrogen consumption will be discounted considerably. It is of great importance to design a sustainable hydrogen network. This paper presents a systematic mathematical modeling methodology for the optimal synthesis of sustainable refinery hydrogen networks. The proposed mixed integer nonlinear programming (MINLP) model accounts for both the economic and the environmental aspect of the hydrogen network. Total annual cost (TAC) is employed to evaluate the economic efficiency of the network, while the environmental performance is assessed by the total CO2 emission of the network. Two types of fresh fuels are investigated in the case studies. A multi-objective optimization is carried out via the Pareto front generation, which is obtained by an adaptive weighted-sum method. The economic–environmental Pareto front will allow for determining the most promising options for the reuse, purification and combustion of hydrogen streams. The numerical example has shown the proposed approach to be efficient and powerful.

Heat integration of regenerative Rankine cycle and process surplus heat through graphical targeting and mathematical modeling technique

Heat Integration, an effective energy-saving technology, has been popularized in many fields. In the current paper, Pinch-based Heat Integration technology is applied in the Heat Integration of process surplus heat (PSH) and regenerative Rankine cycle (RRC)-based steam power plant. PSH is recovered by preheating boiler feed water (BFW) to reduce consumption of steam extracted from the turbine. A systematic hybrid methodology of graphical targeting and mathematical modeling is developed. The objective function is minimal fuel consumption of steam power plant, rather than maximal heat recovery. The terminal temperature and heat load of process-heated BFW are two decision variables. The graphical targeting method is proposed to ascertain the bounds and constraints of the two decision variables. A mathematical model incorporating rigorous simulation of turbine is formulated to achieve the optimal Heat Integration scheme. Two case studies, one pertaining to the Heat Integration of RRC and PSH at low temperature and the other involving the Heat Integration of RRC and PSH at medium temperature, are elaborated. The results show that significant fuel savings and cold utility reductions are achieved by using the proposed methodology. Compared with other methods of PSH utilization, the proposed Heat Integration scheme is more feasible and effective.

Metabolomics for the future of personalized medicine through information and communication technologies.

Although we have empirically found many ways to improve our lives, the challenge of cur­ ing diseases and extending our lifespan poses enormous problems for which we have, at the moment, no adequate answers. For instance, in spite of expenditures estimated to be on the order of €200 billion for cancer research over the last few decades, the definitive cure rates of most common forms of cancer have hardly increased. We will, therefore, need to take both the genetic and environmental effects differing between individuals much more into account. This will not only require a much more detailed characterization of each individual patient but will also require a new generation of ana lysis tools. We will need to convert much larger amounts of data into predictions on the effects of different therapies/prevention strategies. In turn, this will need to rely on a combination of mathematical and probabilistic modeling and advanced statistical inferential methodologies such as multivariate statistics and machine learn­ ing. Therefore, current empirical approaches will have to be replaced (or extended) by compu­ tational models adequate to take into account the complexity of the whole human being. A futuristic, data­intensive strategy to imple­ ment these ideas in the personalized medicine of the future would be the development of an individual model that, gathering together all the data available from the ’omic sciences, will build a ‘virtual patient’ associated to each individual. In this context, metabolomics will have a particular role with respect to the other ’omic sciences, because of its ability to detect, in real time, the adaptive multiparametric response of the organisms to pathophysiological stimuli or genetic modifications [1].

Methodology for estimating the dependence between force and deplacement: A vehicle crash case

Accident reconstruction software analyzed impact of vehicles considers usage of coefficient of restitution as a known quantity. In practice it is common that numerical value of coefficient of restitution is determined on basis of experience. Presence of error in its evaluation causes an essential error in output results. Thus, it is of exceptional importance to determine more precisely its numerical value. Improved solution of vehicle accident reconstruction software is presented in this paper. To archive that, in this paper was developed methodology which provides such analysis of impact process in which the coefficient of restitution becomes the result, and not input data. We have suggested new methodology for mathematical modeling of function dependence between force and displacement in a collision of vehicles. The compression process was approximated with piecewise linear function. The restitution process was approximated with linear curves. During process of restitution stiffness depends on maximum value of displacements during process of compression. The quality of the coherence between experimental data and mathematical function is quantified by residual sum of squares. Numerical examples are performed by usage of the obtained methodology.

Modeling the Dynamics of the Cardiovascular-respiratory System (CVRS) in Humans, a Survey

In this paper we give a survey on modeling efforts concerning the CVRS. The material we discuss is organized in accordance with modeling goals and stresses control and transport issues. We also address basic modeling approaches and discuss some of the challenges for mathematical modeling methodologies in the context of parameter estimation and model validation.