scholarly journals Basic bases of calculations and optimization of NPP power unit equipment parameters methods of mathematical modelling

2021 ◽  
pp. 29-32
Author(s):  
Olexander Yefimov ◽  
Boris Ilchenko ◽  
Larysa Tiutiunyk ◽  
Tetyana Yesipenko ◽  
Anastasiia Motovilnik ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Power Unit ◽  
Complex Function ◽  
Optimality Criteria ◽  
Electricity Production ◽  
Hierarchical Level ◽  
Systematic Analysis ◽  
Load Schedule ◽  
Selection Of

The materials of the article consider the optimization of certain parameters and characteristics of the equipment of NPP power units, which are closely related to the processes of their design and construction. Modern NPP power units are complex technical systems. They include a set of interconnected equipment for different technological purposes, which ensures the performance of power units of a complex function of electricity production and heat of the specified quality and according to a given load schedule. Complete mathematical models of the functional state of steam turbine power units are characterized by a large number of nonlinear connections and contain implicit functions. This complicates their widespread use to solve problems of systematic analysis of the quality of operation of power units. The aim of the work is to analyze the basic theoretical foundations, methods and approaches to the calculation and optimization of the parameters of the equipment of NPP power units by methods of mathematical modeling. The solution of the problem of optimization of NPP power unit parameters includes the following stages: selection of optimality criteria (objective functions); development of a system of interconnected mathematical models in accordance with the required hierarchical level of optimization research; selection of computational methods and optimization algorithms. Taking into account the above methodological provisions and approaches increases the efficiency of mathematical modeling to solve problems of calculations and optimization of NPP power unit parameters.

The Optimization of Mechanized Earthwork Processes

2016 ◽  
Vol 820 ◽  
pp. 96-101 ◽  
Author(s):  
Lucia Paulovičová
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Decision Maker ◽  
Multicriteria Optimization ◽  
Optimization Process ◽  
Multicriteria Method ◽  
Wise Decision ◽  
The Right ◽  
The Cost ◽  
Selection Of

Earthwork processes are the most costly and time consuming component of construction these days and they are characterized by a powerful heavy mechanization which participate on the earthwork process. Current pressure for minimize the cost and maximize the productivity highlights the need to optimize earthworks. In this paper, the optimization process in the area of earthwork processes is described. The selection of the right types of machines for earthwork and its implements has become very difficult these days because of availability of variety of machines models and therefore a multicriteria method is presented to tackle the problem. This paper describes methodology for optimizing the earthwork process according to the selected optimal criteria. The methodology is focused on the proposal phase of optimization where the decision maker has to make a decision and choose the right type of excavators. To overcome the problem of comparing the chosen machines a mathematical modeling approach leading to multicriteria optimization was adopted to make the step wise decision. The methodology gives an mathematical models by which we can solve this problem.

scholarly journals Mathematical modeling in economics for selection of optimum investment solution

2021 ◽  
Vol 273 ◽  
pp. 08003
Author(s):  
Arthur Alukhanyan ◽  
Olga Panfilova
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Linear Programming ◽  
Mathematical Models ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Target Function ◽  
Investment Portfolio ◽  
Monetary Relations ◽  
Selection Of

This work is devoted to development of economic and mathematical models for selection of the optimum investment solution. Moreover, it states the basis for development of model examples and correction of the model considering the results obtained in the examples. In the work the problem is set for selection of the investment sources and objects, which is limited to the linear programming problem. The controlled variable and basic limitations simulating real credit and monetary relations are distinguished in the provided model. The discounted profit obtained from implementation of the optimum investment portfolio is considered as a target function. The economic and mathematical model presented in the article allows finding the optimum investment solution within the limits of the credit and monetary relations taking place both at the micro- and macroeconomic level.

Evolution and Selection of Quantitative Traits

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mathematical Models ◽  
Quantitative Genetics ◽  
Complex Traits ◽  
Evolutionary Biology ◽  
Quantitative Traits ◽  
Specific Gene ◽  
Real World Data ◽  
Holistic Treatment ◽  
Genetics And Genomics ◽  
Selection Of

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

scholarly journals A Tool for the Analysis and Characterization of School Mathematical Models

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1569
Author(s):  
Jesús Montejo-Gámez ◽  
Elvira Fernández-Ahumada ◽  
Natividad Adamuz-Povedano
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Educational Research ◽  
Analysis Procedure ◽  
Real System ◽  
The Real ◽  
School Model ◽  
Corresponding Analysis ◽  
Three Components

This paper shows a tool for the analysis of written productions that allows for the characterization of the mathematical models that students develop when solving modeling tasks. For this purpose, different conceptualizations of mathematical models in education are discussed, paying special attention to the evidence that characterizes a school model. The discussion leads to the consideration of three components, which constitute the main categories of the proposed tool: the real system to be modeled, its mathematization and the representations used to express both. These categories and the corresponding analysis procedure are explained and illustrated through two working examples, which expose the value of the tool in establishing the foci of analysis when investigating school models, and thus, suggest modeling skills. The connection of this tool with other approaches to educational research on mathematical modeling is also discussed.

Call for Manuscripts for the 2015 Focus Issue: Mathematical Modeling

2013 ◽  
Vol 18 (9) ◽  
pp. 571
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Real World ◽  
The Real

This call for manuscripts is requesting articles that address how to use mathematical models to analyze, predict, and resolve issues arising in the real world.

Mathematical Modeling of Machining Parameters in Electrical Discharge Machining with Cu-B4C Composite Electrode

2012 ◽  
Vol 488-489 ◽  
pp. 871-875
Author(s):  
V. Anandakrishnan ◽  
V. Senthilkumar
Keyword(s):  
Mathematical Models ◽  
Current Pulse ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Selection Of

Copper based metal matrix composite reinforced with Boron Carbide is a newly developed Electrical Discharge Machining (EDM) electrode showing better performance than the conventional copper based electrode. Right selection of machining parameters such as current, pulse on time and pulse off time is one of the most important aspects in EDM. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Removal Rate (TRR) and Surface roughness (Ra) to machining parameters (current, pulse-on time and pulse-off time). Furthermore, a study was carried out to analyze thSubscript texte effects of machining parameters on various performance parameters such as, MRR, TRR and Ra. The results of Analysis of Variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied. Response surface modeling is used to develop surface and contour graphs to analyze the effects of EDM input parameters on outer parameters.

Mathematical Alternatives to Standard Probability that Provide Selectable Degrees of Precision

2017 ◽  
Author(s):  
Terrence Fine
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Theory Of Measurement ◽  
Belief Functions ◽  
Standard Practice ◽  
Mathematical Probability ◽  
Comparative Probability ◽  
The Relationship ◽  
Standard Probability

This chapter challenges the nearly universal reliance upon standard mathematical probability for mathematical modeling of chance and uncertain phenomena, and offers four alternatives. In standard practice, precise assignments are made inappropriately, even to the occurrences of events that may be unobservable in principle. Four familiar examples of chance or uncertain phenomena are discussed, about which this is true. The theory of measurement provides an understanding of the relationship between the accuracy of information and the precision with which the phenomenon under examination should be modeled mathematically. The model of modal or classificatory probability offers the least precision. Comparative probability, plausibility/belief functions and upper/lower probabilities are carefully considered. The selectable precision of these alternative mathematical models of chance and uncertainty makes for an improved range of levels of accuracy in modeling the empirical domain phenomena of chance, uncertainty, and indeterminacy. Knowledge of such models encourages further thought in this direction.

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