The document discusses turbulence near walls and different approaches to modeling it in computational fluid dynamics (CFD). It explains that the boundary layer can be divided into different zones, and CFD requires different considerations depending on whether the viscous sub-layer is solved, the log-law layer is modeled, or the whole boundary layer is solved. It also discusses the use of non-dimensional variables to characterize the boundary layer and describes different near-wall treatments in CFD, including resolving the boundary layer with fine meshes or using wall functions with coarser meshes.
The document discusses reactive flow modeling using the eddy dissipation model (EDM) in ANSYS Fluent. EDM solves conservation equations for chemical species by predicting local mass fractions through a convection-diffusion equation. Reaction rates are assumed to be controlled by turbulence, ignoring chemical timescales. EDM gives the smaller of two expressions to calculate reaction rates, with the chemical reaction rate governed by the large eddy mixing timescale. EDM is computationally cheap but works best for one-two step global reactions, as it cannot capture detailed chemistry effects.
01 reactive flows - governing equations favre averaging Mohammad Jadidi
This document discusses reactive flow modeling in combustion chambers. It covers the equations governing reacting flows, including conservation equations for mass, momentum, molecular species, and energy. It also discusses the equation of state and turbulence transport. The document then covers statistical descriptions of turbulent flows using Reynolds decomposition and Favre averaging. Favre averaging is preferred for reacting flows with variable density as it leads to simpler expressions in the transport equations for continuity, momentum, species, and energy compared to Reynolds averaging. Various terms that arise in the averaged equations require turbulence modeling approaches.
The document discusses the governing equations for reacting flows, including conservation of mass, momentum, molecular species, and energy. It outlines the continuity, momentum, species transport, and energy equations. The species transport equation accounts for convection, diffusion, and chemical reaction sources. The energy equation considers changes in enthalpy due to convection, diffusion, pressure work, and radiation. Simplifications are discussed under certain assumptions, such as a single diffusion coefficient and negligible pressure work/radiation terms, in which case enthalpy behaves as a passive scalar. Other relationships presented include the equation of state and definitions of specific heat capacity and density.
01 reactive flows - finite-rate formulation for reaction modelingMohammad Jadidi
This document discusses equations governing reacting flows as modeled in ANSYS Fluent. It describes how Fluent solves conservation equations for species mass fractions using a convection-diffusion equation, where the chemical source term Ri accounts for reaction rates. Finite-rate kinetics and turbulence-chemistry interaction models are discussed for determining Ri, including the eddy dissipation model. The Arrhenius equation is also presented for calculating forward reaction rate constants based on pre-exponential factors, temperature exponents, and activation energies specified in the kinetic mechanism.
The document discusses different types of multiphase flows. It defines multiphase flow as any fluid system with two or more distinct phases flowing simultaneously in mixture. Multiphase flows are classified into four main categories: gas-liquid flows, gas-solid flows, liquid-solid flows, and three-phase flows. Each category contains different flow regimes depending on factors like particle size and flow rates. Flow maps are used to characterize different flow patterns that can occur for a given system.
This document discusses turbulence modeling in computational fluid dynamics (CFD). It contains three main points:
1. Turbulence models used in CFD simulations like RANS and LES are introduced. Important turbulence concepts such as eddies, length scales, and the energy cascade are explained.
2. Reynolds-averaged Navier-Stokes (RANS) equations are presented along with Reynolds stress tensor and turbulent heat flux terms. Common RANS turbulence models and their governing equations are outlined.
3. Large eddy simulation (LES) is described as an alternative to RANS. Filtering operations in LES to separate large and small scales are discussed. Root-mean-square velocities are presented as a
Large eddy simulation (LES) is a computational fluid dynamics technique that resolves the larger turbulent scales in the fluid flow while modeling the smaller scales. LES aims to directly simulate the larger turbulent scales while parameterizing the effects of smaller scales through a subgrid scale model. LES requires significantly more computational resources than Reynolds-averaged Navier–Stokes (RANS) modeling but provides more detailed turbulent flow information.
The document discusses turbulence near walls and different approaches to modeling it in computational fluid dynamics (CFD). It explains that the boundary layer can be divided into different zones, and CFD requires different considerations depending on whether the viscous sub-layer is solved, the log-law layer is modeled, or the whole boundary layer is solved. It also discusses the use of non-dimensional variables to characterize the boundary layer and describes different near-wall treatments in CFD, including resolving the boundary layer with fine meshes or using wall functions with coarser meshes.
The document discusses reactive flow modeling using the eddy dissipation model (EDM) in ANSYS Fluent. EDM solves conservation equations for chemical species by predicting local mass fractions through a convection-diffusion equation. Reaction rates are assumed to be controlled by turbulence, ignoring chemical timescales. EDM gives the smaller of two expressions to calculate reaction rates, with the chemical reaction rate governed by the large eddy mixing timescale. EDM is computationally cheap but works best for one-two step global reactions, as it cannot capture detailed chemistry effects.
01 reactive flows - governing equations favre averaging Mohammad Jadidi
This document discusses reactive flow modeling in combustion chambers. It covers the equations governing reacting flows, including conservation equations for mass, momentum, molecular species, and energy. It also discusses the equation of state and turbulence transport. The document then covers statistical descriptions of turbulent flows using Reynolds decomposition and Favre averaging. Favre averaging is preferred for reacting flows with variable density as it leads to simpler expressions in the transport equations for continuity, momentum, species, and energy compared to Reynolds averaging. Various terms that arise in the averaged equations require turbulence modeling approaches.
The document discusses the governing equations for reacting flows, including conservation of mass, momentum, molecular species, and energy. It outlines the continuity, momentum, species transport, and energy equations. The species transport equation accounts for convection, diffusion, and chemical reaction sources. The energy equation considers changes in enthalpy due to convection, diffusion, pressure work, and radiation. Simplifications are discussed under certain assumptions, such as a single diffusion coefficient and negligible pressure work/radiation terms, in which case enthalpy behaves as a passive scalar. Other relationships presented include the equation of state and definitions of specific heat capacity and density.
01 reactive flows - finite-rate formulation for reaction modelingMohammad Jadidi
This document discusses equations governing reacting flows as modeled in ANSYS Fluent. It describes how Fluent solves conservation equations for species mass fractions using a convection-diffusion equation, where the chemical source term Ri accounts for reaction rates. Finite-rate kinetics and turbulence-chemistry interaction models are discussed for determining Ri, including the eddy dissipation model. The Arrhenius equation is also presented for calculating forward reaction rate constants based on pre-exponential factors, temperature exponents, and activation energies specified in the kinetic mechanism.
The document discusses different types of multiphase flows. It defines multiphase flow as any fluid system with two or more distinct phases flowing simultaneously in mixture. Multiphase flows are classified into four main categories: gas-liquid flows, gas-solid flows, liquid-solid flows, and three-phase flows. Each category contains different flow regimes depending on factors like particle size and flow rates. Flow maps are used to characterize different flow patterns that can occur for a given system.
This document discusses turbulence modeling in computational fluid dynamics (CFD). It contains three main points:
1. Turbulence models used in CFD simulations like RANS and LES are introduced. Important turbulence concepts such as eddies, length scales, and the energy cascade are explained.
2. Reynolds-averaged Navier-Stokes (RANS) equations are presented along with Reynolds stress tensor and turbulent heat flux terms. Common RANS turbulence models and their governing equations are outlined.
3. Large eddy simulation (LES) is described as an alternative to RANS. Filtering operations in LES to separate large and small scales are discussed. Root-mean-square velocities are presented as a
Large eddy simulation (LES) is a computational fluid dynamics technique that resolves the larger turbulent scales in the fluid flow while modeling the smaller scales. LES aims to directly simulate the larger turbulent scales while parameterizing the effects of smaller scales through a subgrid scale model. LES requires significantly more computational resources than Reynolds-averaged Navier–Stokes (RANS) modeling but provides more detailed turbulent flow information.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.