The document describes a numerical methodology for simulating large strain solid dynamics using OpenFOAM. It proposes using a total Lagrangian formulation and first-order conservation laws similar to computational fluid dynamics to model solid mechanics problems involving large deformations. A cell-centered finite volume method is used for spatial discretization along with Riemann solvers and linear reconstruction to capture fluxes. A two-stage Runge-Kutta scheme is employed for time integration. Results are presented demonstrating the method's ability to handle problems involving mesh convergence, enhanced reconstruction, highly nonlinear behavior, plasticity, contact, unstructured meshes, and complex geometries.
The presentation is about how to evaluate the probability of finding the system in any particular state at any later time when the simple Hamiltonian was added by time dependent perturbation. So now the wave function will have perturbation-induced time dependence.
Changing variable is something we come across very often in Integration. There are many
reasons for changing variables but the main reason for changing variables is to convert the
integrand into something simpler and also to transform the region into another region which is
easy to work with. When we convert into a new set of variables it is not always easy to find the
limits. So, before we move into changing variables with multiple integrals we first need to see
how the region may change with a change of variables. In order to change variables in an
integration we will need the Jacobian of the transformation.
The presentation is about how to evaluate the probability of finding the system in any particular state at any later time when the simple Hamiltonian was added by time dependent perturbation. So now the wave function will have perturbation-induced time dependence.
Changing variable is something we come across very often in Integration. There are many
reasons for changing variables but the main reason for changing variables is to convert the
integrand into something simpler and also to transform the region into another region which is
easy to work with. When we convert into a new set of variables it is not always easy to find the
limits. So, before we move into changing variables with multiple integrals we first need to see
how the region may change with a change of variables. In order to change variables in an
integration we will need the Jacobian of the transformation.
Dealing with Notations and conventions in tensor analysis-Einstein's summation convention covariant and contravariant and mixed tensors-algebraic operations in tensor symmetric and skew symmetric tensors-tensor calculus-Christoffel symbols-kinematics in Riemann space-Riemann-Christoffel tensor.
Spline interpolation is a problem of "Numerical Methods".
This slide covers the basics of spline interpolation mostly the linear spline and cubic spline interpolation.
What is numerical differentiation?
What is finite difference?
How to apply that to boundary value problems?
#WikiCourses #Num001
https://wikicourses.wikispaces.com/Topic+Boundary+Value+Problems+-+Finite+Difference
An Overview to the most common Industrial Mass Transfer Operations & Process Separation Technologies
Course Description
In this course we will cover the most basic processes involved in Mass Transfer Operations. This is an overview of what type of processes, methods and units are used in the industry. This is mostly an introductory course which will allow you to learn, understand and know the approach towards separation processes involving mass transfer phenomena.
It is an excellent course before any Mass Transfer Process or Unit Operation Course such as Distillations, Extractions, Leaching, Membranes, Absorption, etc...
This course is extremely recommended if you will continue with the following:
Flash Distillation, Simple Distillation, Batch Distillation
Gas Absorption, Desorption & Stripping
Binary Distillation, Fractional Distillation
Scrubbers, Gas Treating
Sprayers / Spray Towers
Bubble Columns / Sparged Vessels
Agitation Vessels
Packed Towers, Tray Towers
Membranes
Liquid Extraction
Dryers / Humidifiers
Adsorbers
Evaporators/Sublimators
Crystallizers
Centrifugations
And many other Separation Technology!
At the end of the Course:
You will be able to understand the mass transfer operations concepts. You will be able to identify Mass Transfer Unit Operations. You will be also able to ensure the type of method of separation technology used.
You will be able to apply this theory in further Unit Operations.
Theory-Based Course
This is a very theoretical course, some calculations and exercises are present, but overall, expect mostly theoretical concepts.
Large strain computational solid dynamics: An upwind cell centred Finite Volu...Jibran Haider
Presented our research at the 12th World Congress on Computational Mechanics (WCCM) and 6th Asia Pacific Congress on Computational Mechanics (APCOM) at the COEX Convention Center in Seoul, Korea.
Dealing with Notations and conventions in tensor analysis-Einstein's summation convention covariant and contravariant and mixed tensors-algebraic operations in tensor symmetric and skew symmetric tensors-tensor calculus-Christoffel symbols-kinematics in Riemann space-Riemann-Christoffel tensor.
Spline interpolation is a problem of "Numerical Methods".
This slide covers the basics of spline interpolation mostly the linear spline and cubic spline interpolation.
What is numerical differentiation?
What is finite difference?
How to apply that to boundary value problems?
#WikiCourses #Num001
https://wikicourses.wikispaces.com/Topic+Boundary+Value+Problems+-+Finite+Difference
An Overview to the most common Industrial Mass Transfer Operations & Process Separation Technologies
Course Description
In this course we will cover the most basic processes involved in Mass Transfer Operations. This is an overview of what type of processes, methods and units are used in the industry. This is mostly an introductory course which will allow you to learn, understand and know the approach towards separation processes involving mass transfer phenomena.
It is an excellent course before any Mass Transfer Process or Unit Operation Course such as Distillations, Extractions, Leaching, Membranes, Absorption, etc...
This course is extremely recommended if you will continue with the following:
Flash Distillation, Simple Distillation, Batch Distillation
Gas Absorption, Desorption & Stripping
Binary Distillation, Fractional Distillation
Scrubbers, Gas Treating
Sprayers / Spray Towers
Bubble Columns / Sparged Vessels
Agitation Vessels
Packed Towers, Tray Towers
Membranes
Liquid Extraction
Dryers / Humidifiers
Adsorbers
Evaporators/Sublimators
Crystallizers
Centrifugations
And many other Separation Technology!
At the end of the Course:
You will be able to understand the mass transfer operations concepts. You will be able to identify Mass Transfer Unit Operations. You will be also able to ensure the type of method of separation technology used.
You will be able to apply this theory in further Unit Operations.
Theory-Based Course
This is a very theoretical course, some calculations and exercises are present, but overall, expect mostly theoretical concepts.
Large strain computational solid dynamics: An upwind cell centred Finite Volu...Jibran Haider
Presented our research at the 12th World Congress on Computational Mechanics (WCCM) and 6th Asia Pacific Congress on Computational Mechanics (APCOM) at the COEX Convention Center in Seoul, Korea.
A first order hyperbolic framework for large strain computational computation...Jibran Haider
An explicit Total Lagrangian momentum-strains mixed formulation in the form of a system of first order hyperbolic conservation laws, has recently been published to overcome the shortcomings posed by the traditional second order displacement based formulation when using linear tetrahedral elements.
The formulation, where the linear momentum and the deformation gradient are treated as unknown variables, has been implemented within the cell centred finite volume environment in OpenFOAM. The numerical solutions have performed extremely well in bending dominated nearly incompressible scenarios without the appearance of any spurious pressure modes, yielding an equal order of convergence for velocities and stresses.
To have more insight into my research, please visit my website:
http://jibranhaider.weebly.com/
Vertex Centric Asynchronous Belief Propagation Algorithm for Large-Scale GraphsUniversidade de São Paulo
Inference problems on networks and their algorithms were always important subjects, but more so now with so much data available and so little time to make sense of it.
Common applications range from product recommendation to social networks and protein interaction.
One of the main inferences in this types of networks is the guilty-by-association method, where labeled nodes propagate their information throughout the network, towards unlabeled nodes.
While there is a widely used algorithm for this context, called Belief Propagation, it lacks the necessary convergence guarantees for loopy-networks.
More recently, a new alternative method was proposed, called LinBP and while it solved the convergence issue, the scalability for large graphs that do not fit memory remains a challenge.
Additionally, most works that try to use BP considering large scale graphs rely on specific infrastructure such as supercomputers and computational clusters.
Therefore we propose a new algorithm, that leverages state-of-the-art asynchronous vertex-centric parallel processing techniques in conjunction with the state-of-the-art BP alternative LinBP, to provide a scalable framework for large graph inference that runs on a single commodity machine.
Our results show that our algorithm is up to 200 times faster than LinBP's SQL implementation on tested networks, while achieving the same accuracy rate.
We also show that due to the asynchronous processing, our algorithm actually needs less iterations to converge when compared to LinBP when using the same parameters.
Finally, we believe that our methodology highlights the yet not fully explored parallelism available on commodity machines, leaning towards a more cost-efficient computational paradigm.
Abstract : Motivated by the recovery and prediction of electricity consumption time series, we extend Nonnegative Matrix Factorization to take into account external features as side information. We consider general linear measurement settings, and propose a framework which models non-linear relationships between external features and the response variable. We extend previous theoretical results to obtain a sufficient condition on the identifiability of NMF with side information. Based on the classical Hierarchical Alternating Least Squares (HALS) algorithm, we propose a new algorithm (HALSX, or Hierarchical Alternating Least Squares with eXogeneous variables) which estimates NMF in this setting. The algorithm is validated on both simulated and real electricity consumption datasets as well as a recommendation system dataset, to show its performance in matrix recovery and prediction for new rows and columns.
A Class of Continuous Implicit Seventh-eight method for solving y’ = f(x, y) ...AI Publications
In this article, we develop a continuous implicit seventh-eight method using interpolation and collocation of the approximate solution for the solution of y’ = f(x, y) with a constant step-size. The method uses power series as the approximate solution in the derivation of the method. The independent solution was then derived by adopting block integrator. The properties of the method was investigated and found to be zero stable, consistent and convergent. The integrator was tested on numerical examples ranging from linear problem, Prothero-Robinson Oscillatory, Growth Model and Sir Model. The results show that the computed solution is closer to the exact solution and also, the absolutes errors perform better than the existing methods.
Lecture 1 from https://irdta.eu/deeplearn/2022su/
Covers concepts from Part 1 of my new book, https://meyn.ece.ufl.edu/2021/08/01/control-systems-and-reinforcement-learning/
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
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.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
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HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdf
Large strain solid dynamics in OpenFOAM
1. Introduction Governing equations Numerical methodology Results Conclusions
Large strain solid dynamics in OpenFOAM
Jibran Haider a, b
, Chun Hean Lee a
, Antonio J. Gil a
, Javier Bonet c
& Antonio Huerta b
a
Zienkiewicz Centre for Computational Engineering (ZCCE),
College of Engineering, Swansea University, UK
b
Laboratory of Computational Methods and Numerical Analysis (LaCàN),
Universitat Politèchnica de Catalunya (UPC BarcelonaTech), Spain
c
University of Greenwich, London, UK
The 4th Annual OpenFOAM User Conference (11th
- 13th
October 2016)
12 th
October 2016
http://www.jibranhaider.weebly.com
Funded by the Erasmus Mundus SEED PhD Programme and ESI Group
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 1
2. Introduction Governing equations Numerical methodology Results Conclusions
Research group at Swansea University
Dr. Antonio J. Gil
Associate Professor
Dr. Chun Hean Lee
Research Fellow
Prof. Javier Bonet
University of Greenwich
Prof. Antonio Huerta
UPC BarcelonaTech
Dr. Rogelio
Ortigosa
Postdoc
Jibran Haider
Research Assistant
Osama I.
Hassan
Research Assistant
Roman Poya
Research Assistant
Emilio G. Blanco
Research Assistant
Ataollah
Ghavamian
Research Assistant
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 2
5. Introduction Governing equations Numerical methodology Results Conclusions
Fast transient dynamics
Objectives
• Simulate fast-transient solid dynamic problems.
• Develop an industry-driven library of low order numerical
schemes.
Solid dynamics in OpenFOAM [Jasak & Weller, 2000]
× Standard displacement based implicit dynamics
× Linear elastic material with small strain deformation
× Locking in nearly incompressible scenarios
× First order convergence for stresses and strains
× Poor performance in shock dominated scenarios
OpenFOAM solid mechanics community [Ivankovic et al.]
• [Cardiff et al., 2012; 2014; 2016] −→ displacement based + pressure instabilities +
moderate strains + ....
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 5
6. Introduction Governing equations Numerical methodology Results Conclusions
Proposed solid formulation
• First order conservation laws similar to the one used in CFD community.
• Entitled TOtal Lagrangian Upwind Cell-centred FVM for Hyperbolic conservation laws
(TOUCH).
• Programmed in the open-source CFD software OpenFOAM.
TOUCH scheme
[Haider et al., 2016; Lee et al., 2013]
Mixed explicit dynamics
Complex constitutive models
Large strain deformation
No bending and volumtric locking
Second order convergence for stresses and
strains
v = 100 m/s
(0.5, 0.5, 0.5)
(−0.5, −0.5, −0.5)
[Punch cube]
Aim is to bridge the gap between CFD and computational solid dynamics.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 6
8. Introduction Governing equations Numerical methodology Results Conclusions
Total Lagrangian formulation
Conservation laws
• Linear momentum
∂p
∂t
= 0 · P(F) + ρ0b; p = ρ0v
• Deformation gradient
∂F
∂t
= 0 ·
1
ρ0
p ⊗ I ; CURL F = 0
Additional equations
• Total energy
∂E
∂t
= 0 ·
1
ρ0
PT
p − Q + s
An appropriate constitutive model is required to close the system.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 8
9. Introduction Governing equations Numerical methodology Results Conclusions
Hyperbolic system
First order conservation laws
∂U
∂t
= 0 · F(U) + S
U =
p
F
E
; F =
P(F)
1
ρ0
p ⊗ I
1
ρ0
PT p − Q
; S =
ρ0b
0
s
• Geometry update
∂x
∂t
=
1
ρ0
p; x = X + u
Adapt CFD technology to the proposed formulation.
Develop an efficient low order numerical scheme for transient solid dynamics.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 9
14. Introduction Governing equations Numerical methodology Results Conclusions
Lagrangian contact dynamics
Rankine-Hugoniot jump conditions
c U = F N
where = + − −
c p = t
c F =
1
ρ0
p ⊗ N
c E =
1
ρ0
PT
p · N
X, x
Y, y
Z, z
Ω+
0
Ω−
0
N+
N−
n−
n+
Ω+(t)
Ω−(t)
φ+
φ−
n−
n+
c−
s
c+
s
c+
pc−
p
Time t = 0
Time t
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 14
15. Introduction Governing equations Numerical methodology Results Conclusions
Acoustic Riemann solver
Jump condition for linear momentum
c p = t
Normal jump → cp pn = tn
Tangential jump → cs pt = tt
Upwinding numerical stabilisation
p
C
=
c−
p p−
n + c+
p p+
n
c−
p + c+
p
+
c−
s p−
t + c+
s p+
t
c−
s + c+
s
pC
Ave
+
t+
n − t−
n
c−
p + c+
p
+
t+
t − t−
t
c−
s + c+
s
pC
Stab
t
C
=
c+
p t−
n + c−
p t+
n
c−
p + c+
p
+
c+
s t−
t + c−
s t+
t
c−
s + c+
s
tC
Ave
+
c−
p c+
p (p+
n − p−
n )
c−
p + c+
p
+
c−
s c+
s (p+
t − p−
t )
c−
s + c+
s
tC
Stab
How do we obtain U−,+
?
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 15
16. Introduction Governing equations Numerical methodology Results Conclusions
Godunov’s method
• Piecewise constant representation in every cell.
• Methodology is first order accurate in space.
x
y
U
Ue
Uα1
Uα4
Uα2
Uα3
(a) Piecewise constant values ×
x
y
U
Uα4
Uα3
Uα2
Uα1
Ue
Uα3
Uα4
(b) Linear reconstruction
× First order simulations suffer from excessive numerical dissipation.
A linear reconstruction procedure is essential to increase spatial accuracy.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 16
17. Introduction Governing equations Numerical methodology Results Conclusions
Linear reconstruction procedure
Gradient operator:
• Classical least squares minimisation procedure.
Ge =
α∈Λα
e
ˆdeα ⊗ ˆdeα
−1
α∈Λα
e
Uα − Ue
deα
ˆdeα
Linear extrapolation to flux integration point:
U{f,a} = Ue + Ge · X{f,a} − Xe
de1α2
e1
α1
α2
α3
α4
αf1
αf2
αf3αf4
αf5
e2
de2α4
Gradient correction procedure:
• Necessary for the satisfaction of monotonicity through Barth and Jespersen limiter (φe).
U{f,a} = Ue + φe Ge(Ue, Uα) · X{f,a} − Xe
Ensures that the spatial discretisation is second order accurate.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 17
19. Introduction Governing equations Numerical methodology Results Conclusions
Godunov-type FVM
Standard FV update (CURL F = 0)
dFe
dt
=
1
Ωe
0
f∈Λ
f
e
pC
f
ρ0
⊗ Cef X
Constrained FV update (CURL F = 0)
[Dedner et al., 2002; Lee et al., 2013]
dFe
dt
=
1
Ωe
0
f∈Λ
f
e
˜pC
f
ρ0
⊗ Cef
• Algorithm is entitled ’C-TOUCH’.
pe
pC
f −→
˜pe
Ge
˜pC
f
←−
pa
Constrained transport schemes are widely used in Magnetohydrodynamics (MHD).
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 19
21. Introduction Governing equations Numerical methodology Results Conclusions
Time integration
Two stage Runge-Kutta time integration
1st
RK stage −→ U∗
e = Un
e + ∆t ˙U
n
e(Un
e, tn
)
2nd
RK stage −→ U∗∗
e = U∗
e + ∆t ˙U
∗
e (U∗
e , tn+1
)
Un+1
e =
1
2
(Un
e + U∗∗
e )
with stability constraint:
∆t = αCFL
hmin
cp,max
; cp,max = max
a
(ca
p)
An explicit Total Variation Diminishing Runge-Kutta time integration scheme.
Monolithic time update for geometry.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 21
24. Introduction Governing equations Numerical methodology Results Conclusions
Low dispersion cube
X, x
Y, y
Z, z
(0, 0, 0)
(1, 1, 1)
Displacements scaled 300 times
t = 0 s t = 2 ms t = 4 ms t = 6 ms
Pressure (Pa)
Boundary conditions
1. Symmetric at:
X = 0, Y = 0, Z = 0
2. Skew-symmetric at:
X = 1, Y = 1, Z = 1
Analytical solution
u(X, t) = U0 cos
√
3
2
cdπt
A sin
πX1
2 cos
πX2
2 cos
πX3
2
B cos
πX1
2 sin
πX2
2 cos
πX3
2
C cos
πX1
2 cos
πX2
2 sin
πX3
2
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 24
Problem description: Unit side cube, linear elastic material, ρ0 = 1100 kg/m3
, E = 17 MPa, ν = 0.3
[Haider et al., 2016] and αCFL = 0.3.
[Aguirre et al., 2014]
25. Introduction Governing equations Numerical methodology Results Conclusions
Low dispersion cube: Mesh convergence
Velocity at t = 0.004 s
10
−2
10
−1
10
0
10
−7
10
−6
10
−5
10
−4
Grid Size (m)
L2NormError
vx
vy
vZ
Slope = 2
Stress at t = 0.004 s
10
−2
10
−1
10
0
10
−7
10
−6
10
−5
10
−4
Grid Size (m)
L2NormError
Pxx
Pyy
Pzz
Slope = 2
Demonstrates second order convergence for velocities and stresses.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 25
Problem description: Unit side cube, linear elastic material, ρ0 = 1100 kg/m3
, E = 17 MPa, ν = 0.3
[Haider et al., 2016] and αCFL = 0.3.
[Aguirre et al., 2014]
35. Introduction Governing equations Numerical methodology Results Conclusions
Bar rebound
X, x
Y, y
v0
(−0.0032, 0, 0)
(0.0032, 0.0324, 0)
Z, z
r0
0.004
[Bar rebound]
t = 3 ms t = 6 ms t = 12 ms t = 18 ms t = 27 ms
Pressure (Pa)
Demonstrates the ability of the algorithm to simulate contact problems.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 35
Problem description: Nearly incompressible neo-Hookean material, ρ0 = 8930 kg/m3
, E = 585 MPa,
[Lahiri et al., 2010] ν = 0.45, αCFL = 0.3 and v0 = −150 m/s.
36. Introduction Governing equations Numerical methodology Results Conclusions
Bar rebound
X, x
Y, y
v0
(−0.0032, 0, 0)
(0.0032, 0.0324, 0)
Z, z
r0
0.004
y Displacement of the points X = [0, 0.0324, 0]T
and X = [0, 0, 0]T
0 0.5 1 1.5 2 2.5 3
x 10
−4
−20
−16
−12
−8
−4
0
4
8
x 10
−3
Time (sec)
yDispacement(m)
Top (2880 cells)
Top (23040 cells)
Bottom (2880 cells)
Bottom (23040 cells)
Demonstrates the ability of the algorithm to simulate contact problems.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 36
Problem description: Nearly incompressible neo-Hookean material, ρ0 = 8930 kg/m3
, E = 585 MPa,
[Lahiri et al., 2010] ν = 0.45, αCFL = 0.3 and v0 = −150 m/s.
37. Introduction Governing equations Numerical methodology Results Conclusions
Torus impact
[Torus impact]
t = 2 ms t = 4 ms t = 8 ms
t = 17 ms t = 28 ms t = 28 ms
Pressure (Pa)
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 37
Problem description: Neo-Hookean material, ρ0 = 1000 kg/m3
, E = 1 MPa, ν = 0.4, αCFL = 0.3 and
v0 = −3 m/s.
39. Introduction Governing equations Numerical methodology Results Conclusions
Spinning plate: Structured vs unstructured elements
X, x
Y, y
(0.5, 0.5, 0)
ω0 = [0, 0, Ω]T
(−0.5, −0.5, 0)
Time = 0.15 s
(a) Structured 20 × 20 cells (b) Unstructured 484 cells
Pressure (Pa)
Demonstrates the ability of the framework to handle unstructured grids.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 39
Problem description: Unit side square, nearly incompressible hyperelastic neo-Hookean material,
[Haider et al., 2016] ρ0 = 1000 kg/m3
, E = 17 MPa, ν = 0.45 and αCFL = 0.3 and Ω = 105 rad/s.
40. Introduction Governing equations Numerical methodology Results Conclusions
Spinning plate: Structured vs unstructured elements
X, x
Y, y
(0.5, 0.5, 0)
ω0 = [0, 0, Ω]T
(−0.5, −0.5, 0)
Displacement of point X = [0.5, 0.5, 0]T
0 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2
−1.5
−1.25
−1
−0.75
−0.5
−0.25
0
0.25
0.5
0.75
1
Time (sec)
Displacement(m)
ux
structured
u
y
structured
u
x
unstructured
u
y
unstructured
Demonstrates the ability of the framework to handle unstructured grids.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 40
Problem description: Unit side square, nearly incompressible hyperelastic neo-Hookean material,
[Haider et al., 2016] ρ0 = 1000 kg/m3
, E = 17 MPa, ν = 0.45, αCFL = 0.3 and Ω = 105 rad/s.
42. Introduction Governing equations Numerical methodology Results Conclusions
Flapping device
t = 0 ms t = 25 ms t = 50 ms t = 75 ms
t = 100 ms t = 125 ms t = 175 ms t = 200 ms
Pressure (Pa)
[Flapping device]
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 42
Problem description: Nearly incompressible hyperelastic neo-Hookean material, ρ0 = 1000 kg/m3
,
E = 17 MPa, ν = 0.45, αCFL = 0.3.
43. Introduction Governing equations Numerical methodology Results Conclusions
Complex twisting
[Complex twisting]
t = 5 ms t = 10 ms t = 15 ms
t = 20 ms t = 25 ms t = 30 ms
Pressure (Pa)
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 43
Problem description: Nearly incompressible hyperelastic neo-Hookean material, ρ0 = 1000 kg/m3
,
E = 17 MPa, ν = 0.45, αCFL = 0.3.
45. Introduction Governing equations Numerical methodology Results Conclusions
Conclusions and on-going work
Conclusions
• Upwind cell centred FVM is presented for fast solid dynamic simulations within the OpenFOAM
environment.
• Linear elements can be used without usual locking.
• Velocities and stresses display the same rate of convergence.
On-going work
• Investigation into an advanced Roe’s Riemann solver with robust shock capturing algorithm.
• Extension to multiple body and self contact.
• Ability to handle tetrahedral elements.
• Extension to fluid-structure interaction problems.
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 45
46. Introduction Governing equations Numerical methodology Results Conclusions
References
Published / accepted
• J. Haider, C. H. Lee, A. J. Gil and J. Bonet. "A first order hyperbolic framework for large strain computational solid
dynamics: An upwind cell centred Total Lagrangian scheme", IJNME (2016), DOI: 10.1002/nme.5293.
• C. H. Lee, A. J. Gil, G. Greto, S. Kulasegaram and J. Bonet. "A new Jameson-Schmidt-Turkel Smooth Particle
Hydrodynamics algorithm for large strain explicit fast dynamics, CMAME (2016); 311: 71-111.
• A. J. Gil, C. H. Lee, J. Bonet and R. Ortigosa. "A first order hyperbolic framework for large strain computational solid
dynamics. Part II: Total Lagrangian compressible, nearly incompressible and truly incompressible elasticity",
CMAME (2016); 300: 146-181.
• J. Bonet, A. J. Gil, C. H. Lee, M. Aguirre and R. Ortigosa. "A first order hyperbolic framework for large strain
computational solid dynamics. Part I: Total Lagrangian isothermal elasticity", CMAME (2015); 283: 689-732.
• M. Aguirre, A. J. Gil, J. Bonet and C. H. Lee. "An upwind vertex centred Finite Volume solver for Lagrangian solid
dynamics", JCP (2015); 300: 387-422.
• C. H. Lee, A. J. Gil and J. Bonet. "Development of a cell centred upwind finite volume algorithm for a new
conservation law formulation in structural dynamics", Computers and Structures (2013); 118: 13-38.
Under review
• C. H. Lee, A. J. Gil, O. I. Hassan, J. Bonet and S. Kulasegaram. "An efficient Streamline Upwind Petrov-Galerkin
Smooth Particle Hydrodynamics algorithm for large strain explicit fast dynamics, CMAME (2016).
In preparation
• J. Haider, C. H. Lee, A. J. Gil, A. Huerta and J. Bonet. "Contact dynamics in OpenFOAM, JCP.
• A. J. Gil, J. Bonet, C. H. Lee, J. Haider and A. Huerta. "Adapted Roe’s Riemann solver in explicit fast solid
dynamics, JCP.
More information at: http://www.jibranhaider.weebly.com/research
Jibran Haider (Swansea University, UK & UPC, Spain) 4th OpenFOAM User Conference (Cologne, Germany) 46