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|BEST| Crocodile Physics 1.7

There was no interaction with the world besides camera movement until this version. I wanted to change this and as a result, For the past 1.5 months, I focused mainly on implementing complex physics. It was an unequal struggle, but it was worth it. Making the world more interactive changed the engine for the better.

|BEST| Crocodile Physics 1.7


Before I move into the technical details of physics in the CLUSEK-RT game engine, I would like to present you with the final result of the current physics implementation. It's not perfect, but in my opinion good enough. I will try to polish it more in the future.

From the start, I knew that I didn't want to implement physics on my own because it would be too much work and even AAA games use libraries to solve physics interactions. I googled a little bit and came up with 4 candidates:

Let's start with the first one from the list. Havok Physics is a highly customizable and optimized physics engine. It has been in constant development for over 20 years and it's clearly visible. It's really mature and has got dedicated tools for debugging and optimization. That's the reason why it's an industry standard and games like Doom Ethernal, Detroit: Become Human and Assassin's Creed: Odyssey use this engine. It's a perfect solution for the game and it has been battle-tested by big corporations. Does it have any disadvantages then? Yes, it's really expensive (cost 25 000 $) and that's way too much for my hobby project.

Fast, accurate, popular and poorly documented. That's how I would describe Bullet library. It's one of the best libraries, but when it comes to documentation, then it's really bad, especially with more complex topics. The reason for the poor documentation may the focus on the PuBullet version of the library. Plus there's no dedicated tool like in Havok for debugging.

Last, but not least: PhysX (4.1) by Nvidia. It's also an industry standard but it's open-source, free and... AMAZING! Really, it's like a free version of Havok. It's fast, accurate and has got amazing documentation. Of course, that's not all, because there's also "PhysX Visual Debugger" that's designed to debug problems with physics. I would describe the solution from Nvidia more like a toolbox because it's made out of many elements.

Implementing physics for rigid-body objects was quite simple and well described in the official documentation, so I don't want to focus on it now. Instead, I would like to talk a little bit about vehicles.

This tool is like RenderDoc/NSight, but for physics. In this tool besides simple things, you can also verify how vehicle physics are calculated and if something doesn't work, then you can easily diagnose it. I already used it to eliminate "jumpy wheels" in my engine, so it already helped me solve the problem that I was not able to find, just by looking at the code.

This article is quite short, but it's all about quality and not quantity. So that's all for today. In the next release, I will try to polish physics, add more internal tools to the engine and maybe upgrade the renderer a little bit. I don't want to plan, because, in the end, I might end up with different elements added. If you're interested in the source code, then you can find it on the GitHub platform, where I also published compiled version of the engine.

International Journal of Theoretical Physics is a peer-reviewed (single blind) journal entirely dedicated to the development and fostering of theoretical physics as an overarching and unifying conceptual, mathematical, methodological and computational framework for carrying out fundamental research in physics.The journal is particularly interested in articles that combine several aspects of the above, with contributions exposing either new and broadly applicable theoretical methods or uncovering connections between hitherto independent theoretical approaches from various branches of physics being particularly welcome.Papers submitted to the journal should clearly state in the abstract and in the introduction what contribution to theoretical physics, viewed broadly, is intended to be given.

Some of the major unsolved problems in physics are theoretical, meaning that existing theories seem incapable of explaining a certain observed phenomenon or experimental result. The others are experimental, meaning that there is a difficulty in creating an experiment to test a proposed theory or investigate a phenomenon in greater detail.

There are many different scaling laws. At one extreme, there aresimple scaling laws that are easy to learn, easy to use, and veryuseful in everyday life. Scaling laws can be and should be introducedat the elementary-school level, and then reinforced and extended everyyear through middle school, high school, and beyond. Scaling laws arecentral to physics. This has been true since Day One of modernscience. Galileo presented several important scaling results in 1638(reference 1 or reference 2).

Perhaps the best known scaling law pertains to the relationshipbetween length and area. In figure 3, when it comes tolength, every length in the large square is twice as great as thecorresponding length in the small square. When it comes to area, youcan see that the area of the large square is not twice as great, butrather four times as great as the area of the small square.

The idea of replacing many variables by fewer variables has beenrediscovered multiple times in various contexts, and has been givenmultiple different names. One way to describe it is to say that thecorrect physics occupies a subspace within the full parameterspace. In the context of statistics, the same idea goes by the namesufficient statistic. In the context of critical-point physics,the same idea goes by the name of universality.

This conflict between the dimensional analysis and the actual scalingbehavior may look like a serious mistake, but it is not. It justshows the limitations of dimensional analysis. Seesection 9.3.2 for an explanation of how this comes about.As always, if the dimensions are telling you one thing and the scalingis telling you another, the scaling is incomparably more reliablebecause it is more closely connected to the physics. Dimensionalanalysis is only a hint as to how the scaling might go.

In equation 31, K is dimensionless and (as expected) scales likethe zeroth power of system volume. However, this did not solve any ofthe fundamental problems. We saw in connection with equation 27and equation 26 that we had three quantities, all with the samedimensions. Of these, one scaled V to the -1 power, one scaled likeV to the - power, and one scaled like V to the 0 power. Whenwe make things dimensionless, equation 31 still has threequantities, and one scales V to the -1 power, one scales like V tothe - power, and one scales like V to the 0 power. There isobviously no way you can predict all three of these results usingdimensional analysis. (The best you can do is play whack-a-mole,choosing dimensions so that one of the three scales the way itsdimensions would suggest, while the other two conflict with theirdimensions.)

The key to understanding this is to note that there are two relevantvolumes: the volume of the vessel, and the quantum-statistical volumeΛ3. We can construct perfectly good scaling laws, providedwe base them on honest-to-goodness physics, not mere dimensionalanalysis.

All the concepts are given under their parent topic chapterwise so that it becomes easy for you. Once you are done preparing for the topics listed here try solving different kinds of problems as it is one f the best ways to Master Physics. Practice the Mastering Physics Answers in regular intervals in different methods for a single question so that you will develop a deeper understanding of the Subject Physics.

There is no simple way to master Physics. One of the best ways to master Physics is through a dedicated approach and complete Practice. You can master in Physics with immense curiosity to know and also quench your thirst for knowledge with the best books for Physics.

Before 1978, when the American Physical Society changed the terminology, a career in condensed matter physics meant having a job in solid-state physics. The new field now includes the study of liquids, but not how fluids move and the forces acting on them, which is covered by fluid mechanics. One-third of the physicists in the United States have jobs in condensed-matter physics.

Condensed matter physics jobs include the study of Bose-Einstein condensate, a phenomenon predicted by the famous developers of Bose-Einstein statistics 70 years before physicists with jobs at JILA (a research institute operated by the National Institute of Standards and Technology and the University of Colorado) discovered it. This new state of matter emerged when the temperature of rubidium gas was cooled to 1.7 x 10-7 K. At this low temperature, the momentum of the atoms became more known and their location less known to the extent of forming a single quantum state.

Many jobs in condensed matter physics involve the study of superconductors, which have zero resistivity and other technologically useful properties. It is a quantum mechanical phenomenon thought until 1986 to occur at temperatures near 0 K, but certain ceramics make the transition at 90 K. Superconductors can produce the stable magnetic fields required by magnetic resonance imaging (MRI), a multi-billion dollar business. There are condensed matter physics career opportunities in this subfield which is related to magnetic levitation for transportation, digital circuits, power cables, and electronic filters that operate in the frequency range used by broadcast radio, cell phones, and television.

Many jobs in solid-state physics involve research on semiconductors and transistors and require using X-ray crystallography, neutron diffraction, and electron diffraction to study the structure of materials.

Nanotechnology positions are likely to overlap with careers in condensed matter physics. Nanotech controls matter on an atomic scale and deals with structures smaller than 10-7 meters. In 2000, scientists at IBM reported the micro-fabrication of an electronic chip for high-speed data storage. Another example of nanotechnology is using carbon nanotubes (a form of carbon) to make nanomotors. IBM scientists recently reported using a combination of atomic force microscopy (high-resolution scanning probe microscopy) and MRI to get images of viruses with a resolution of better than 10-8 meters.


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