Parallel Computations Efficiency: Abaqus, Ansys and Simmakers

Hardware that is based on parallel computing architecture has recently been gaining increasing popularity in high performance computing.

The efficiency of parallel processing hardware in engineering problem solving such as the computer simulation of physical processes is not directly dependent on the number of processors: four CPU cores do not in fact provide a fourfold speed increase in solving complex engineering problems over one CPU core. Similarly, the transfer of computation to graphics cards with hundreds of cores cannot provide a hundredfold increase in speed.

First of all, parallel computation acceleration is limited by computational algorithms; running algorithms with a low degree of parallelization on supercomputers and high-performance workstations is irrational. The notion of "efficiency of parallelization" is explained by Amdahl's law, according to which if at least 1/10 of the program is executed sequentially, then the acceleration cannot be increased beyond 10 times the original speed regardless the number of cores employed.

Telling examples of the limited effectiveness of algorithm parallelization for solving engineering problems are provided in the relatively weak results of worldwide leaders in computer-aided engineering (CAE) software - Abaqus and Ansys.

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FAQ for the Updated Version of Frost 3D Universal Software

Following the release of the article “Thermal analysis of a lengthy section of a gas pipeline on permafrost”, we received lots of questions from users.
In this post, we cover the more frequently asked questions concerning the functionality of the updated version of Frost 3D Universal software. Firstly, however, we would like to remind readers that the new version of the software was released in May, 2014. Here, we implemented new technologies in the architecture of the software and its main components, which enables the calculation of computational meshes as large as 100 million nodes on a PC. To demonstrate the extraordinary performance of the newest version of Frost 3D Universal, we conducted the thermal analysis of a long section of pipeline lying on permafrost, with a mesh consisting of 58.5 million nodes.

Question: Why do we need such large computational meshes?

Answer: The necessity for such large quantities of computational mesh nodes derives from the following factors:
1) The computation of extensive regions and long or massive objects often involves many elements for discretization in the computational domain.
2) There are often relatively small elements in the computational domain; there could, for example, be a thin layer of heat insulation, or ground strata. A significant increase in mesh refinement is required to discretize these relatively miniscule elements.
3) Areas with significant temperature gradients (near heat insulators, heat sources, cooling devices, etc.) require increased computational mesh density, consequently significantly increasing the total amount of nodes in the computational domain.
Note that even with the use of a non-uniform cell size (at irregular computational mesh), for example, we still need a lot of nodes. The increase in the cell size in irregular computational meshes needs to be very smooth; otherwise, the numerical method returns significantly less accurate results.

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Application of ANSYS Software for Thermal Analysis of Permafrost Ground. Advantages of Frost 3D Universal Software.

An engineering company has recently asked Simmakers to comment on the possibility of applying the finite-element package of ANSYS to the problems of ground thawing and thermal stabilization, and to explain the advantages of Frost 3D Universal software when solving such problems.

Note that this issue has also been addressed by various specialists in dedicated forums and conferences.

Claims by the ANSYS distributor:

ANSYS with finite-element method analysis is used for ground thawing analysis. ANSYS is a longstanding universal software system for finite-element analysis. It is popular with specialists in the field of computer engineering (CAE, Computer-Aided Engineering) and finite-element solutions for linear and non-linear, stationary and non-stationary spatial problems of rigid body mechanics and construction mechanics (including non-stationary geometrically and physically non-linear problems of contact interaction of construction elements), problems of liquid and gas mechanics, heat exchange and heat transfer, electrodynamics, acoustics, and also mechanics of coupled fields.

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Simulation of Groundwater Flow in Saturated Ground

Applicability in construction engineering

Ground water flow rates predefine largely predetermine the construction methods and materials used for footings, basement walls, underground constructions and many other in-ground works. The stability of beds and banks of water reservoirs and channels also depends on the filtration in coastal terrain. Factoring the flow of ground water improves the modeling accuracy of othe rphysical processes in the ground. When distribution of thermal fields takes place in the ground, the convective heat transfer is caused by groundwater flow.

Water is able to flow through the ground because of the presence of pores, which are voids of various diameters and shapes that appear due to the fact that structural elements produced during terrain formation don’t fit flush with each other. The approach for modeling water flow processes differ according to the degree of water porosity and the velocity of water in pores: if the pores are in a saturated condition, the groundwater flow process is simulated based on the Darcy differential equation; water flow in unsaturated ground is described by Richard’s or Brinkman’s equation.

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Thermal Analysis of a Lengthy Section of a Gas Pipeline on Permafrost

Numerical solution of the problem was implemented in Frost 3D Universal software, with a computational mesh of 58.5 million nodes, to predict ground thaw under the influence of the pipeline. A 2-year simulation of the ground thaw around the pipeline was performed. The computation in Frost 3D Universal software on a quad-core CPU took approximately 70 hours and used 17 GB of RAM. We had already simulated this model before with less detailed discretization: the mesh consisted of 22.3 million nodes and this wasn’t enough to enable us to factor in small elements such as thin heat insulators. Using an NVIDIA Titan graphics accelerator, the prediction of ground thaw over a 20-year period took about 7 hours.

The model of a lengthy section of pipeline

The model of a lengthy section of a gas pipeline

The specific nature of the current problem – simulation of the ground thaw formation along a 500-meter section of the oil pipeline, 1.2 meters in diameter – rendered a large computational mesh necessary. This section is characterized by a complex geological-lithological structure of grounds, which also includes layers of ice deposits. A total of 21 ground typologies with various thermophysical properties were revealed in this section alone. Altitude differences in the daylight surface of 35 meters were also taken into account.

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