Merge branch 'main' of https://github.com/InteractiveComputerGraphics/physics-simulation into main

Author: janbender

examples/sph_approximation.html

@@ -61,7 +61,7 @@ <h1 style="text-align:center">SPH Approximation</h1>
 
 		<tr><td colspan="2">
 			<h2>SPH Approximation of different functions:</h2>
-			In this example we discretized a linear and a quadratic polynomial as well as a trigonometric function using SPH with the cubic spline kernel [KBST19]. The left plot shows the particle sampling pattern while the right plot shows the exact functions and their SPH approximations. To compute the SPH approximations the function values are sampled along the red line in the left plot. That means that for each point on the line the neighbors are determined and the SPH approximation formula is applied:
+			In this example we discretized a linear and a quadratic polynomial as well as a trigonometric function using SPH with the cubic spline kernel [KBST19, KBST22]. The left plot shows the particle sampling pattern while the right plot shows the exact functions and their SPH approximations. To compute the SPH approximations the function values are sampled along the red line in the left plot. That means that for each point on the line the neighbors are determined and the SPH approximation formula is applied:
 			$$\langle f(x,y) \rangle = \sum_j \frac{m_j}{\rho_j} f(x_j,y_j) W_{ij}$$
 
 			Linear function: 
@@ -80,7 +80,9 @@ <h3>Shepard filter</h3>
 
 			<h3>References</h3>
 			<ul>
-			<li>[KBST19] Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner.  Smoothed Particle Hydrodynamics for Physically-Based Simulation of Fluids and Solids. Eurographics Tutorial, 2019</li>
+			<li>[KBST19] Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner. Smoothed Particle Hydrodynamics for Physically-Based Simulation of Fluids and Solids. Eurographics Tutorial, 2019
+			<li>[KBST22] Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner. A Survey on SPH Methods in Computer Graphics. Computer Graphics Forum, 2022
+			</li>
 			</ul>
 		</td></tr>
 	</table>	

examples/sph_gradient_approximation.html

@@ -69,7 +69,7 @@ <h1 style="text-align:center">SPH Gradient Approximation</h1>
 
 		<tr><td colspan="2">
 			<h2>SPH approximation of the gradient of a quadratic function:</h2>
-			In this example we approximate the gradient of a quadratic polynomial using the SPH discretization with the cubic spline kernel [KBST19]. The left plot shows the particle sampling pattern while the right plot shows the quadratic function, the exact gradient, the SPH gradient approximation, and the error. To compute the SPH approximation the function values are sampled along the red line in the left plot. That means that for each point on the line the neighbors are determined and the SPH difference formula to approximate the gradient is applied [KBST19]:
+			In this example we approximate the gradient of a quadratic polynomial using the SPH discretization with the cubic spline kernel [KBST19, KBST22]. The left plot shows the particle sampling pattern while the right plot shows the quadratic function, the exact gradient, the SPH gradient approximation, and the error. To compute the SPH approximation the function values are sampled along the red line in the left plot. That means that for each point on the line the neighbors are determined and the SPH difference formula to approximate the gradient is applied [KBST19]:
 			$$\langle \nabla f(x,y) \rangle = \sum_j \frac{m_j}{\rho_j} (f(x_j,y_j) - f(x,y)) \nabla W_{ij}$$
 
 			Quadratic_function:
@@ -90,6 +90,8 @@ <h3>Kernel gradient correction</h3>
 			<h3>References</h3>
 			<ul>
 			<li>[KBST19] Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner.  Smoothed Particle Hydrodynamics for Physically-Based Simulation of Fluids and Solids. Eurographics Tutorial, 2019</li>
+			<li>[KBST22] Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner. A Survey on SPH Methods in Computer Graphics. Computer Graphics Forum, 2022
+			</li>
 			</ul>
 		</td></tr>
 	</table>	

index.md

@@ -2,7 +2,7 @@
 
 Physics simulation is an important research topic in visual computing. It has many applications ranging from such as virtual prototyping, training simulators, robotics, animation software for digital production including visual effects in film and animation movies, and computer games – just to mention a few.
 
-At [RWTH Aachen university](https://animation.rwth-aachen.de) I offer [lectures](https://animation.rwth-aachen.de/courses/) which give an introduction to state-of-the-art simulation methods for rigid bodies, deformable solids and fluids in the area of visual computing (e.g, the Finite Element Method (FEM) and the Smoothed Particle Hydrodynamics (SPH) approach). For the lectures I programmed several simulation examples using JavaScript.  
+At [RWTH Aachen university](https://animation.rwth-aachen.de) I offer [lectures](https://animation.rwth-aachen.de/courses/) which give an introduction to state-of-the-art simulation methods for rigid bodies, deformable solids and fluids in the area of visual computing (e.g, the Finite Element Method (FEM) and the [Smoothed Particle Hydrodynamics (SPH)](https://interactivecomputergraphics.github.io/SPH-Tutorial/) approach). For the lectures I programmed several simulation examples using JavaScript.  
 
 Why JavaScript? Because everybody can directly run the examples in the browser. Moreover, I was able to add a short web page for each example which explains the method.