Classification of mathematical modeling,
Classification based on Variation of Independent Variables,
Static Model,
Dynamic Model,
Rigid or Deterministic Models,
Stochastic or Probabilistic Models,
Comparison Between Rigid and Stochastic Models
Urban strategies to promote resilient cities The case of enhancing Historic C...inventionjournals
This research tackles disaster prevention problems in dense urban areas, concentrating on the urban fire challenge in Historic Cairo district, Egypt, through disaster risk management approach. The study area suffers from the strike of several urban fire outbreaks, that resulted in disfiguring historic monuments and destroying unregulated traditional markets. Therefore, the study investigates the significance of hazard management and how can urban strategies improve the city resilient through reducing the impact of natural and man-made threats. The main findings of the research are the determination of the vulnerability factors in Historic Cairo district, either regarding management deficiency or issues related to the existing urban form. It is found that the absence of the mitigation and preparedness phases is the main problem in the risk management cycle in the case study. Additionally, the coping initiatives adopted by local authorities to address risks are random and insufficient. The study concludes with recommendations which invoke incorporating hazard management stages (pre disaster, during disaster and post disaster) into the process of evolving development planning. Finally, solutions are offered to mitigate, prepare, respond and recover from fire disasters in the case study. The solutions include urban policies, land-use planning, urban design outlines, safety regulation and public awareness and training.
Scilab Finite element solver for stationary and incompressible navier-stokes ...Scilab
In this paper we show how Scilab can be used to solve Navier-stokes equations, for the incompressible and stationary planar flow. Three examples have been presented and some comparisons with reference solutions are provided.
Data Science Meetup: DGLARS and Homotopy LASSO for Regression ModelsColleen Farrelly
Short overview of two regression model extensions using differential geometry and homotopy continuation. Case study involves an open-source dataset that can be found on my ResearchGate page, along with the R code used in the analysis. Contains a short reference section for readers interested in learning more about the methods.
Classification of mathematical modeling,
Classification based on Variation of Independent Variables,
Static Model,
Dynamic Model,
Rigid or Deterministic Models,
Stochastic or Probabilistic Models,
Comparison Between Rigid and Stochastic Models
Urban strategies to promote resilient cities The case of enhancing Historic C...inventionjournals
This research tackles disaster prevention problems in dense urban areas, concentrating on the urban fire challenge in Historic Cairo district, Egypt, through disaster risk management approach. The study area suffers from the strike of several urban fire outbreaks, that resulted in disfiguring historic monuments and destroying unregulated traditional markets. Therefore, the study investigates the significance of hazard management and how can urban strategies improve the city resilient through reducing the impact of natural and man-made threats. The main findings of the research are the determination of the vulnerability factors in Historic Cairo district, either regarding management deficiency or issues related to the existing urban form. It is found that the absence of the mitigation and preparedness phases is the main problem in the risk management cycle in the case study. Additionally, the coping initiatives adopted by local authorities to address risks are random and insufficient. The study concludes with recommendations which invoke incorporating hazard management stages (pre disaster, during disaster and post disaster) into the process of evolving development planning. Finally, solutions are offered to mitigate, prepare, respond and recover from fire disasters in the case study. The solutions include urban policies, land-use planning, urban design outlines, safety regulation and public awareness and training.
Scilab Finite element solver for stationary and incompressible navier-stokes ...Scilab
In this paper we show how Scilab can be used to solve Navier-stokes equations, for the incompressible and stationary planar flow. Three examples have been presented and some comparisons with reference solutions are provided.
Data Science Meetup: DGLARS and Homotopy LASSO for Regression ModelsColleen Farrelly
Short overview of two regression model extensions using differential geometry and homotopy continuation. Case study involves an open-source dataset that can be found on my ResearchGate page, along with the R code used in the analysis. Contains a short reference section for readers interested in learning more about the methods.
Principal component analysis - application in financeIgor Hlivka
Principal component analysis is a useful multivariate times series method to examine and study the drivers of the changes in the entire dataset. The main advantage of PCA is the reduction of dimensionality where the large sets of data get transformed into few principal factors that explain majority of variability in that group. PCA has found many applications in finance – both in risk and yield curve analytics
Lecture notes of Industrial Waste Treatment (Elective -III) as per syllabus of Solapur university for BE Civil
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K ORchid College of Engg and Tech,
Solapur
Lecture notes of Environmental Engineering-II as per Solapur university syllabus of TE CIVIL.
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K Orchid college of Engg and Technology,
Solapur
Principal component analysis - application in financeIgor Hlivka
Principal component analysis is a useful multivariate times series method to examine and study the drivers of the changes in the entire dataset. The main advantage of PCA is the reduction of dimensionality where the large sets of data get transformed into few principal factors that explain majority of variability in that group. PCA has found many applications in finance – both in risk and yield curve analytics
Lecture notes of Industrial Waste Treatment (Elective -III) as per syllabus of Solapur university for BE Civil
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K ORchid College of Engg and Tech,
Solapur
Lecture notes of Environmental Engineering-II as per Solapur university syllabus of TE CIVIL.
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K Orchid college of Engg and Technology,
Solapur
The importance of risk management in businessr2financial
R2 Financial Technologies provides multi-asset risk analytics and risk intelligence to all sorts of business decision makers. Visit their website today to learn more http://www.r2-financial.com/.
Lecture Notes of Environmental Engg-II as per solapur university syllabus of TE Civil,
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K Orchid college of Engg and Technology,
Solapur
Lecture notes of Environmental Engineering-II as per Solapur university syllabus of TE CIVIL.
Prepared by
Prof S S Jahagirdar,
Associate Professor,
N K Orchid college of Engg and Technology,
Solapur
Dimensional analysis Similarity laws Model laws R A Shah
Rayleigh's method- Theory and Examples
Buckingham Pi Theorem- Theory and Examples
Model and Similitude
Forces on Fluid
Dimensionless Numbers
Model laws
Distorted models
Fluid dynamics, actually is the study of fluid under motion, governed with a certain set of conservation equations, wherein things are conserved, with reference to mass, momentum & energy.
If these three quantities i.e. mass, momentum & energy are solved entirely we can define any fluid flow. The conservation laws are formulated in the form of equations which we try to solve and that’s what simulation is all about. For my blogs kindly visit: https://www.learncax.com/knowledge-base/blog/by-author/ganesh-visavale
Interpretability in ML & Sparse Linear RegressionUnchitta Kan
The presentation, first given on January 8, 2019, introduces the concept of interpretability in machine learning, and why we might care about it. It also introduces an example of an interpretable, sparse model which is lasso regression.
A simple finite element solver for thermo-mechanical problems - margonari eng...Scilab
In this paper we would like to show how it is possible to develop a simple but effective finite element solver to deal with thermo-mechanical problems. In many engineering situations it is necessary to solve heat conduction problems, both steady and unsteady state, to estimate the temperature field inside a medium and, at the same time, compute the induced strain and stress states.
To solve such problems many commercial software tools are available. They provide user-friendly interfaces and flexible solvers, which can also take into account very complicated boundary conditions, such as radiation, and nonlinearities of any kind, to allow the user to model the reality in a very accurate and reliable way.
However, there are some situations in which the problem to be solved requires a simple and standard modeling: in these cases it could be sufficient to have a light and dedicated software able to give reliable solutions. Moreover, other two desirable features of such a software could be the possibility to access the source to easily program new tools and, last but not least, to have a cost-and-license free product. This turns out to be very useful when dealing with the solution of optimization problems.
Keeping in mind these considerations, we used the Scilab platform and the gmsh (which are both open source codes) to show that it is possible to build tailored software tools, able to solve standard but complex problems quite efficiently.
Power System Simulation: History, State of the Art, and ChallengesLuigi Vanfretti
This talk will give an overview of power system simulation technology through several decades, aiming to provide an understanding of the modeling philosophy and approach that has lead to the state of the art in (domain specific) power system simulation tools. This historical perspective will contrast the de facto proprietary software development method used by the power engineering community, against the open source development model. Aspects of resistance to change particular to the power system engineering community will be highlighted.
Given this particular context, power system simulation faces enormous challenges to adapt in order to satisfy simulation needs of both cyber-physical and sustainable system challenges. Such challenges will be highlighted during the talk.
There is, however, an opportunity for disruptive change in power system simulation technology emerging for the EU Smart Grid Mandate M/490, which requires "a set of consistent standards, which will support the information exchange (communication protocols and data models) and the integration of all users into the electric system operation." These regulatory aspects will be explained to highlight the importance of collaboration between the power system domain and computer system experts.
Open modeling and simulation standards may have a large role to play in the development of the European Smart Grid which will have to overcome challenges related to the design, operation and control of cyber-physical and sustainable electrical energy systems. To contribute to this role, the KTH SmarTS Lab research group has been applying the standardized Modelica language and the FMI standard for model exchange in order to couple the domain specific data exchange model (CIM) with the powerful and modern simulation technologies developed by the Modelica community. These efforts will be also discussed.
3. Introduction A mathematical model is defined as a description from the point of view of mathematics of a fact or phenomenon of the real world, the size of the population to physical phenomena such as speed, acceleration or density.
16. Types of differential equations Elliptical Satellite Hyperbolic Laplace equation (Steady state two-dimensional space) Equation heat conduction (Variable time and dimension spatial) Wave equation (Variable time and dimension spatial)
17. Fundamental Flow Equation GEOMETRIC FACTOR FLUID DENSITY FLOW RATE POROSITY SOURCES AND / OR SINKS
19. In 1856, in the French city of Dijon, the engineer Henry Darcy was responsible for study of the supply network to the city. It seems that it also had to design filters sand to purify water, so I was interested in the factors influencing the flow of water through the sandy, and presented the results of his work as a appendix to his report of the distribution network. That little appendix has been the basis of all subsequent physico-mathematical studies on groundwater flow. In today's laboratories have equipment similar to that used Darcy, and are called constant head permeameter
20. Fig.4 constant head permeameter Q = Caudal Δ h = Potential Difference entre A y B Δ l = Distance between A y B Hydraulic gradient = section Basically a permeameter is a recipient of constant section which makes Flush connecting one end of a high constant level tank. In the other end is regulated by an outflow valve in each experiment also maintains the flow constant. Finally, measure the height of the water column at various points
21. Section If the environment changes but the relationship is fulfilled K constant changes. This was called permeability.
22. Conservation of Momentum caudal section x velocity Velocidad Darcy : Caudal / Saccion total This is false because the water does not circulate throughout the cross section
23. Limitations of Darcy's law The proportionality constant K is not proper or other feature the porous medium. PERMEABILITY INTRINSIC SPECIFIC WEIGHT FLUID VISCOSITY DYNAMICS FLUID
24. In some circumstances the relationship between Q and the gradient Hydraulic non-linear. This can happen when the value of K is very low or very high speeds. Darcy is met Darcy is not met can be fulfilled or not
25. Equations of State Incompressible fluid Fluid slightly compressible Compressible fluid constant