scholarly journals Aluminum bar cutting optimization for door and window manufacturing

DYNA ◽  
2020 ◽  
Vol 87 (212) ◽  
pp. 155-162
Author(s):  
Ageu Araujo Machado ◽  
João Carlos Zayatz ◽  
Marcos Meurer Da Silva ◽  
Guilherme Melluzzi Neto ◽  
Gislaine Camila Lapasini Leal ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Real Data ◽  
Raw Material ◽  
Process Efficiency ◽  
Computational Time ◽  
Advantages And Disadvantages ◽  
Key Factor ◽  
Material Procurement ◽  
The One ◽  
The Mathematical Model

This study aims to optimize the one-dimensional cutting process of aluminum bars for the production of aluminum doors. Reducing the use of bars and the amount of material that becomes scrap is a key factor in process efficiency, reducing the need for raw material procurement. The mathematical model used considers the size of the bar, the number and size of cuts, the size of the leftovers that can be used and the size of the leftovers that are considered scrap. Based on real data from a company in the aluminum frame segment, the mathematical model was used to simulate three different scenarios. Three different objective functions were used in the simulations, and the results obtained in each scenario were described in order to indicate the advantages and disadvantages of using each objective function. For the instance sizes studied, the model is able to obtain optimal solutions with little computational time.

THE DEVELOPMENT OF THE MATHEMATICAL MODEL OF PREDICTING THE INDICATORS OF ACCREDITATION OF TECHNICAL UNIVERSITIES IN THE RUSSIAN FEDERATION

2017 ◽  
pp. 27-38
Author(s):  
Olga Mikhaylovna Tikhonova ◽  
Alexander Fedorovich Rezchikov ◽  
Vladimir Andreevich Ivashchenko ◽  
Vadim Alekseevich Kushnikov
Keyword(s):  
Mathematical Model ◽  
System Dynamics ◽  
Regression Model ◽  
Oriented Graph ◽  
Real Data ◽  
Educational Process ◽  
Proposed Model ◽  
Linear Differential ◽  
The University ◽  
The Mathematical Model

The paper presents the system of predicting the indicators of accreditation of technical universities based on J. Forrester mechanism of system dynamics. According to analysis of cause-and-effect relationships between selected variables of the system (indicators of accreditation of the university) there was built the oriented graph. The complex of mathematical models developed to control the quality of training engineers in Russian higher educational institutions is based on this graph. The article presents an algorithm for constructing a model using one of the simulated variables as an example. The model is a system of non-linear differential equations, the modelling characteristics of the educational process being determined according to the solution of this system. The proposed algorithm for calculating these indicators is based on the system dynamics model and the regression model. The mathematical model is constructed on the basis of the model of system dynamics, which is further tested for compliance with real data using the regression model. The regression model is built on the available statistical data accumulated during the period of the university's work. The proposed approach is aimed at solving complex problems of managing the educational process in universities. The structure of the proposed model repeats the structure of cause-effect relationships in the system, and also provides the person responsible for managing quality control with the ability to quickly and adequately assess the performance of the system.

scholarly journals MATHEMATICAL MODELING OF LEACHING PROCESS OF RED MUD IN ORDER TO OBTAIN THE KINETICS PARAMETERS

2015 ◽  
Vol 14 (2) ◽  
pp. 90 ◽  
Author(s):  
K. L. M. Dos Passos ◽  
B. M. Viegas ◽  
E. N. Macêdo ◽  
J. A. S. Souza ◽  
E. M. Magalhães
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Red Mud ◽  
Mineralogical Composition ◽  
Raw Material ◽  
Data Conversion ◽  
Kinetics Parameters ◽  
Leaching Process ◽  
Iron Leaching ◽  
The Mathematical Model

The use of the waste of the Bayer process, red mud, is due to its chemical and mineralogical composition that shows a material rich in oxides of iron, titanium and aluminum. Some studies conducted show that this waste can be applied as a source of alternative raw material for concentration and subsequent recovery of titanium compounds from an iron leaching process, which is present in higher amounts, about 30% by weight. To obtain a greater understanding about the leaching kinetics, the information of the kinetic data of this process is very important. In this context, the main objective of this work is the development of a mathematical model that is able to fit the experimental data (conversion / extraction iron, titanium and aluminum) of the leaching process by which is possible to obtain the main kinetic parameters such as the activation energy and the velocity of chemical reactions as well as the controlling step of the process. The development of the mathematical model was based on the model of core decreasing. The obtained model system of ordinary differential equations was able to fit the experimental data obtained from the leaching process, enabling the determination of the controlling step, the rate constants and the activation energies of the leaching process.

A Modular Code for Real Time Dynamic Simulation of Gas Turbines in Simulink

2002 ◽  
Vol 128 (3) ◽  
pp. 506-517 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Gas Turbines ◽  
Simulation Software ◽  
Computational Time ◽  
High Fidelity ◽  
Time Step ◽  
The Mathematical Model

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aero-derivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

scholarly journals Mathematical Model of the Piped Vehicle Motion in Piped Hydraulic Transportation of Tube-Contained Raw Material

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yongye Li ◽  
Xihuan Sun
Keyword(s):  
Mathematical Model ◽  
Transportation Cost ◽  
Raw Material ◽  
Maximum Relative Error ◽  
Transportation Energy ◽  
Core Components ◽  
Vehicle Motion ◽  
Motion Characteristics ◽  
Experimental Values ◽  
The Mathematical Model

The piped hydraulic transportation of tube-contained raw material is an emerging technique for transporting materials. In this technique, the piped vehicle is one of the core components, and its motion characteristics directly determine the transportation energy consumption and the transportation cost of this technique. To study the motion characteristics of the piped vehicle, the force of the piped vehicle was analyzed from the mechanical perspective in this paper. On the assumption that the piped vehicle moved steadily and it had sufficient stiffness, the mathematical model of the piped vehicle motion was established in the turbulent flow according to the stress characteristics of the piped vehicle and the factors influencing its motion characteristics, and then the mathematical model was tested by experiments. The findings show that the calculated values of the velocities of the piped vehicle were identical to the experimental values with changes in various influencing factors. When the flow discharge, the diameter or length of the piped vehicle increased, or the mass of transported material decreased, the velocity of the piped vehicle increased. The maximum relative error did not exceed 9.47%, which proved that the mathematical model of the piped vehicle motion was rational. The results can provide theoretical basis to improve the structure of the piped vehicle and the piped hydraulic transportation technique of tube-contained raw material.

A High-Fidelity Real-Time Simulation Code of Gas Turbine Dynamics for Control Applications

2002 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Computational Time ◽  
High Fidelity ◽  
Simulation Code ◽  
Real Time Simulation ◽  
Time Simulation ◽  
The Mathematical Model

A novel high-fidelity real-time simulation code based on a lumped, non-linear representation of gas turbine components is presented. The aim of the work is to develop a general-purpose simulation code useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of the gas turbine engine. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

scholarly journals A MULTIDIMENSIONAL SUBDIFFUSION MODEL WITH CHEMOTAXIS

2019 ◽  
Vol 11 (2) ◽  
pp. 1
Author(s):  
Bambang Hendriya Guswanto
Keyword(s):  
Mathematical Model ◽  
Probability Measure ◽  
Random Walks ◽  
Unit Ball ◽  
Dimensional Case ◽  
One Dimensional ◽  
The One ◽  
The Mathematical Model

The mathematical model for subdiffusion process with chemotaxis proposed by Langlands and Henry [1] for the one-dimensional case is extended to the multi-dimensional case. The model is derived from random walks process using a probability measure on a n-multidimensional unit ball $S^{n-1}$.

scholarly journals Prediction of Al2O3 leaching recovery in the Bayer process using statistical multilinear regresion analysis

2010 ◽  
Vol 46 (2) ◽  
pp. 161-169 ◽  
Author(s):  
I. Djuric ◽  
P. Djordjevic ◽  
I. Mihajlovic ◽  
Dj. Nikolic ◽  
Z. Zivkovic
Keyword(s):  
Mathematical Model ◽  
Bayer Process ◽  
Alumina Production ◽  
Statistical Reliability ◽  
Leaching Process ◽  
Input Parameters ◽  
Statistical Sample ◽  
One Year ◽  
The One ◽  
The Mathematical Model

This paper presents the results of defining the mathematical model which describes the dependence of leaching degree of Al2O3 in bauxite from the most influential input parameters in industrial conditions of conducting the leaching process in the Bayer technology of alumina production. Mathematical model is defined using the stepwise MLRA method, with R2 = 0.764 and significant statistical reliability - VIF<2 and p<0.05, on the one-year statistical sample. Validation of the acquired model was performed using the data from the following year, collected from the process conducted under industrial conditions, rendering the same statistical reliability, with R2 = 0.759.

scholarly journals Indicators of Violence Levels: Questionnaires and Predictive Mathematical Model

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
E. Leal-Enríquez ◽  
A. R. Gutiérrez-Antúnez
Keyword(s):  
Mathematical Model ◽  
Partner Violence ◽  
Numerical Procedure ◽  
Numerical Data ◽  
Intimate Partner ◽  
Loss Of Control ◽  
Victim Assistance ◽  
Key Factor ◽  
The Mathematical Model ◽  
Health Experts

In this paper, we present, in detail, how a mathematical model that simulates the probable scenarios of intimate partner violence is linked to the application of any questionnaire of domestic violence already in use. This questionnaire assigns a weight of severity to each proposed inquiry for the types of psychological, physical, and sexual violence. We show a numerical procedure that must be performed to obtain the probable scenarios of violence in which the victim is involved, taking as key factor the loss of control of the perpetrator. With the numerical data obtained from the application of the mathematical model, the probable levels of violence that the victim could experience month to month for two cycles of violence are plotted, as well as the behaviors of the probable states of loss of control that the perpetrator would have during the next twelve months. Based on the results obtained, we generated a help table of indicators that could be used by victim assistance centers and/or health experts for decision-making schemes.

CURRENT STATE AND PROBLEMS CONCERNING LOCALISATION TECHNOLOGIES OF OIL PIPELINES FOR THEIRS REPAIR WITH TERMINATION OF OPERATING

2018 ◽  
pp. 170-178
Author(s):  
Y. G. Melnychenko ◽  
G. G. Melnychenko ◽  
T. Y. Dodyk
Keyword(s):  
Mathematical Model ◽  
Critical Analysis ◽  
Transient Flow ◽  
Flow Calculation ◽  
Oil Pipeline ◽  
Current Technology ◽  
Advantages And Disadvantages ◽  
Current State ◽  
Oil Pipelines ◽  
The Mathematical Model

The critical analysis of current technology of onshore oil pipeline sections releasing from product for theirs repair are undertaken. Its shortcomings are established. The overview of modern plugging devices for oil pipelines sections localization while being repaired is provided, in particular the advantages and disadvantages of each considered one were analyzed. On the basis of this review an optimal plugging pig construction for oil pipeline sections isolation is proposed.The advantages and disadvantages of the proposed device are given. The necessity of simulation of plugging pigs motion in the pipeline is proved. The mathematical model of the plugging device movement along the main oil pipelines is formulated. The methodology of transient flow calculation during plugging pigs motion and stopping in the oil pipeline was proposed.

An optimized mathematical model for cancer patient care planning in the COVID-19 era.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18663-e18663
Author(s):  
Isabel Blancas ◽  
David Martínez-Rodríguez ◽  
Fernando Rodríguez-Serrano ◽  
Rafael Jacinto Villanueva ◽  
Jose Manuel Garrido
Keyword(s):  
Mathematical Model ◽  
Demographic Data ◽  
Real Data ◽  
Oncologic Surgery ◽  
Number Of Patients ◽  
Oncologic Patients ◽  
Hospital Resources ◽  
The Difference ◽  
Using Data ◽  
The Mathematical Model

e18663 Background: The COVID-19 pandemic has threatened to collapse hospital and Intensive Care Unit (ICU) services, and it seems to limit the care of oncologic patients. The objective was to develop a mathematical model designed to predict the hospitalization and ICU admission demands due to COVID-19 to forecast the availability of hospital resources for the scheduling of oncological surgery and medical treatment that require hospitalitation or possible use of ICU services. Methods: We have implemented a SEIR model designed to predict the number of patients requiring hospitalization and ICU admissions for COVID-19. We evaluated the model using the number of cases registered in the hospitals of the province of Granada (Spain), that altogether cover 914,678 inhabitants. Calibration was performed using data recorded between March 15 and September 22, 2020. After that, the model was validated by comparing the predictions with data registered between September 23 and November 7, 2020. Besides, we performed a predictive analysis of scenarios regarding different possible sanitary measures. Results: Using patient registered data we developed a mathematical model that reflects the flow among the different sub-groups related to COVID-19 pandemics (Table). The best algorithm that fitted the disease dynamics was Particle Swarm Optimization, that minimized the difference between model output and real data used to calibrate the model. The validation phase showed the accuracy of the predictions, especially concerning trends in hospitalizations and ICU admissions. The different scenarios modelled on November 10, 2020 allowed us to predict the evolution of the pandemic until July 1, 2021, and to detect the peaks and valleys of disease prevalence. Conclusions: The mathematical model presented provides predictions on the evolution of COVID-19, the prevalence and hospital or ICU care demands. The predictions can be used to detect periods of greater availability of hospital resources that make it possible to schedule the oncologic surgery and intensify the care for oncologic patients. Furthermore, our model can be adapted to other population by recalibrating the model according to demographic data, the local evolution of the pandemic and the health policies. [Table: see text]

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