scholarly journals MODELING OF PHOSPHORUS PRODUCTION PROCESSES AND DEVELOPING A MANAGEMENT STRUCTURE BASED ON GREY SYSTEMS

2021 ◽  
Author(s):  
Nigina Toktasynova ◽  
◽  
Batyrbek Suleimenov ◽  
Yelena Kulakova ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Predictive Model ◽  
Real Time ◽  
General Structure ◽  
Sinter Machine ◽  
Forecast Model ◽  
Practical Significance ◽  
Time Data ◽  
Vacuum Chambers ◽  
Model Based

The agglomeration process is one of the complex, multidimensional technological processes; it takes place under conditions of a large number of disturbing influences. As a result, the amount of return during sintering reaches 40-50%. The work is devoted to the development of a mathematical model capable of predicting and controlling the sintering point based on real-time data. As the main parameters for the construction of predictive models, data measured in real time were used – the temperature in the vacuum chambers and the gas velocity determined through the measured pressure (rarefaction) in the vacuum chambers. This paper describes the methodology and basic algorithms for modeling agglomeration processes, starting from the ingress of the charge into the sinter machine and ending with the production of a suitable agglomerate. The obtained curves of the developed mathematical model of temperature in vacuum chambers served as the basis for testing the forecast model based on the use of the theory of gray systems and the optimization algorithm of the "swarm of particles". Based on the developed mathematical model, a system for predicting the sintering point is constructed, which is the basis for determining the quality of the agglomerate, which will reduce the return volume during sintering. The general structure of the sinter control system based on a dynamic predictive model is also proposed. The practical significance of the developed predictive model based on the theory of gray systems is as follows: - forecast of the sintering point value of the agglomerate and synthesis of the control action based on the forecast; - the algorithm for constructing a mathematical model of the forecast can be used for any process that has the character of a "gray exponential law".

scholarly journals Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

2012 ◽  
Vol 12 (12) ◽  
pp. 3719-3732 ◽  
Author(s):  
L. Mediero ◽  
L. Garrote ◽  
A. Chavez-Jimenez
Keyword(s):  
Data Assimilation ◽  
Genetic Programming ◽  
Real Time ◽  
High Performance ◽  
Forecast Model ◽  
Flood Forecasting ◽  
Distribution Functions ◽  
Model Parameters ◽  
Hydrological Process ◽  
Model Based

Abstract. Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

scholarly journals Model of the dynamics of a wheeled vehicle for a complex of full-scale-mathematical modeling

2020 ◽  
Vol 1 (4) ◽  
pp. 46-60
Author(s):  
B.B. Kositsyn ◽  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Real Time ◽  
Block Diagram ◽  
Plane Motion ◽  
Full Scale ◽  
Practical Significance ◽  
Modes Of Operation ◽  
Wheeled Vehicle ◽  
Full Scale Tests

Introduction. The use of the method of full-scale-mathematical modeling in “real time” opens up wide opportunities associated with the analysis of the modes of operation of the “man – vehicle – environment” system, as well as the study of the loading of units and assemblies of vehicles. The existing research complexes of full-scale mathematical modeling are suitable for obtaining most of the indicators usually determined by full-scale tests. The difference lies in the ability to fully control the course of virtual testing, recording any parameters of the vehicle movement, taking into account the “human factor”, as well as complete safety of the experiment. Purpose of research. The purpose of this work is to create a mathematical model of the dynam-ics of a wheeled vehicle, suitable for use in such a complex of full-scale mathematical modeling and assessment of the load of transmission units in conditions close to real operation. Methodology and methods. The proposed model is based on the existing model of the dynamics of a wheeled vehicle developed at Bauman Moscow State Technical University. Within the framework of the model, the dynamics of a vehicle is described as a plane motion of a rigid body in a horizontal plane. The principle of possible displacements is applied to determine the normal reac-tions of the bearing surface. The interaction of the wheel with the ground in the plane of the support base is described using an approach based on the “friction ellipse” concept. To enable the driver and operator of the full-scale mathematical modeling complex to drive a virtual vehicle in “real time” mode, the mathematical model is supplemented with a control system that communicates between the control parameter set by the driver by pressing the accelerator and brake pedals and the control actions of the vehicle's transmission units, such as: an electric machine, an internal combustion en-gine, a hydrodynamic retarder and a brake system. The article presents a block diagram of the de-veloped control algorithm, as well as approbation of the system's operation in a complex of full-scale mathematical modeling. Results and scientific novelty. A mathematical model of the dynamics of a wheeled vehicle was developed. It opens up wide possibilities for studying the modes of operation of the “driver-vehicle-environment” system in “real time”, using a complex of full-scale mathematical modeling. Practical significance. A mathematical model of the dynamics of a wheeled vehicle was devel-oped. It is supplemented with an algorithm for the distribution of traction / braking torques between the transmission units, which provide a connection between the driver's pressing on the accelerator / brake pedal and the control parameters of each of the units.

Experimental Verification of a Dynamic Finger Model Using Real-Time Data Acquisition

2003 ◽  
Author(s):  
David McNeal ◽  
Farid Amirouche ◽  
Mark Gonzalez
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Experimental Verification ◽  
Time Data ◽  
Stiffness Constant ◽  
Real Time Data ◽  
Flexion Moment ◽  
Human Finger ◽  
Finger Model ◽  
Annular Pulleys

The purpose of this experiment is to create a mathematical model for the function of the annular pulleys of the human finger in flexion. We have assumed that the flexion moment of the middle and proximal phalanges occurs at the proximal and distal ends of the A-2 and A-4 pulleys. The amount of force generated is dependent on the angle of flexion at the adjacent joint, the tension in the tendon and the stiffness constant of the pulley.

Real-Time Well Monitoring and Engineering Analysis of Drilling Activities: Intelligent Rig State Detection and Prediction With Uncertainty

2020 ◽  
Author(s):  
Vanessa Kemajou ◽  
Robello Samuel
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Engineering Calculation ◽  
Open Architecture ◽  
Engineering Analysis ◽  
Time Data ◽  
Multiple Sensors ◽  
Real Time Data ◽  
Drilling Quality ◽  
Drilling Operations

Abstract Drilling activities are risky and costly, especially when performed offshore. Careful monitoring and real time data analysis are required for safe and efficient operations with minimized down-time. Drilling operations, being fast-paced and not visible, often lead to transient and unforeseen issues. The synchronous assessment and prediction of drilling quality has historically been a challenge. It relies on a prompt collection, analysis and prediction of the multiple sensors data, as well as an immediate comparison to the original drilling plan. Another challenge is achieving real-time well engineering, and automatically and instantaneously providing valuable insights to the engineering and operations teams. A system was successfully developed to tackle these challenges. It is a cloud-based application, made with an event-driven streaming architecture to automatically retrieve real-time drilling data and compare it with planned data. The real-time data is automatically made available to determine the current well operation or rig state, and trigger the subsequent engineering analysis. Next, a forecast model is trained with the engineering calculation outputs and it returns predictions on these outputs while considering their inherent uncertainty. As a result, these predictions enable alerts to be sent when the system detects approaching anomalous conditions. The proposed system is a DecisionSpace® 365 cloud-native application on an open architecture. It is flexible, accessible from anywhere, can be automatically updated for continuous improvement, and can be deployed easily and quickly. It can also be extended to further applications.

Design of Data Acquisition System for Fiber Optic Gyro Based on the FAT32 File System

2013 ◽  
Vol 365-366 ◽  
pp. 658-661
Author(s):  
Ying Bo Cai ◽  
Huan Zha ◽  
Xue Tong Wei
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
High Speed ◽  
Fiber Optic ◽  
High Reliability ◽  
Practical Significance ◽  
Fiber Optic Gyro ◽  
Fiber Optic Gyroscope ◽  
Time Data ◽  
Large Capacity

Demand for high-speed fiber optic gyroscope data acquisition and real-time record, the design of the SD Card as storage medium to large capacity fiber optic gyro high - speed real - time acquisition and bulk storage systems, The system by applying the sd2.0 protocol and fat32 file systems in the system, enable real - time Data Acquisition of fiber optic gyro and large capacity storage. Experiments have shown that the system properly designed, easy to use, high reliability to meet the actual demand, is of important practical significance.

scholarly journals Forecast Model Update Based on a Real-Time Data Processing Lambda Architecture for Estimating Partial Discharges in Hydrogenerator

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7242
Author(s):  
Fabio Henrique Pereira ◽  
Francisco Elânio Bezerra ◽  
Diego Oliva ◽  
Gilberto Francisco Martha de Souza ◽  
Ivan Eduardo Chabu ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Forecast Model ◽  
Partial Discharges ◽  
Forecasting Model ◽  
Distributed Data ◽  
Time Data ◽  
Lambda Architecture ◽  
Real Time Data ◽  
Real Time Data Processing

The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updated due to the high cost to collect sensors’ data and insufficient real-time data analysis. This article proposes a method to update the forecasting model, aiming to improve its accuracy. The method is based on a distributed data platform with the lambda architecture, which combines real-time and batch processing techniques. The results show that the proposed system enables real-time updates to be made to the forecasting model, allowing partial discharge forecasts to be improved with each update with increasing accuracy.

Fault detection for control of wastewater treatment plants

2006 ◽  
Vol 53 (4-5) ◽  
pp. 375-382 ◽  
Author(s):  
O. Schraa ◽  
B. Tole ◽  
J.B. Copp
Keyword(s):  
Wastewater Treatment ◽  
Process Control ◽  
Real Time ◽  
Control Structure ◽  
Wastewater Treatment Plants ◽  
Process Models ◽  
Sensor Data ◽  
Time Data ◽  
Model Based Control ◽  
Model Based

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.

Visual Simulation of Shells Exploding in Virtual Environment

2013 ◽  
Vol 756-759 ◽  
pp. 1809-1813
Author(s):  
Gong Lin ◽  
Da Wei Jiang
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Dynamic Model ◽  
Virtual Environment ◽  
Particle System ◽  
Texture Mapping ◽  
Visual Simulation ◽  
Model Based ◽  
Mapping Techniques ◽  
The Mathematical Model

The mathematical model of smoke diffusion and dissipation when shells exploding is studied, and the dynamic model based on particle system controlled by the mathematical model and texture mapping techniques is established. The visual simulation of the method is efficient and real-time.

scholarly journals A data based mechanistic real-time flood forecasting module for NFFS FEWS

2012 ◽  
Vol 9 (6) ◽  
pp. 7271-7296 ◽  
Author(s):  
D. Leedal ◽  
A. H. Weerts ◽  
P. J. Smith ◽  
K. J. Beven
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Open Shell ◽  
Flood Forecasting ◽  
Time Data ◽  
Flood Alert ◽  
Interaction Interface ◽  
Forecast Models ◽  
Forecasting System ◽  
The Uk

Abstract. The data based mechanistic (DBM) approach for identifying and estimating rainfall to level, and level to level models has been shown to perform well for flood forecasting in several studies. The DELFT-FEWS open shell operational flood forecasting system provides a framework linking hydrological/meteorological real-time data, real-time forecast models, and a human/computer interaction interface. This infrastructure is used by the UK National Flood Forecasting System (NFFS) and the European Flood Alert System (EFAS) among others. The open shell nature of the FEWS framework has been specifically designed to make it easy to add new forecasting models written as FEWS modules. This paper shows the development of the DBM forecast model as a FEWS module and presents results for the Eden catchment (Cumbria UK) as a case study.

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