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Performance Comparison: Versions of Frost 3D Universal and Hardware

There are 4 versions of Frost 3D Universal. The main difference of each version is the software implementation of mathematical solver used for numerical solving of the heat problem.

As a result, the question “Which version of Frost 3D Universal could fulfil users specific requirements?”often arises.

Below is a list of parameters to help you to choose the most appropriate program version:

1. What are the typical dimensions of the computational domain during simulation (10 x 10 or 100 x 100 meters)?

2. What is the level of computational model detalisation – is there a significant amount of small elements important to the computation?

3. How critical is the computation accuracy – is significant coursing of computational domain possible during discretization?

4. What are the requirements for computation speed – are simulation results required in a matter of hours or can they wait a day or more?

Review of simulation results for the models in Frost 3D Universal will help you choose the right software version. Different hardware setups were used for computations: 1 processor core / 4 processor cores, low-cost video card / powerful Nvidia accelerators.

Examples of computations in Frost 3D Universal.

Versions of Frost 3D Universal: Computation speed comparison

Bovanenkovo gas field reservoir

Bovanenkovo gas field reservoir

FROST 3D UNIVERSAL

Software package for simulation of heat processes in grounds with the account of:

 

  • Phase transitions
  • Filtration
  • Snow cover thickness
  • Operation of cooling devices
  • Heat impact of buildings and constructions
  • Complex ground structure

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Bovanenkovo gas field reservoir computation results

Coarse discretization

Computational domain: The number of cells: Simulation period:

14.6×11×19.5 meters

0.7 million

5 years

Computational unit:

single core, Intel Core i7

Computational time:

11 hours

Program version:

64-bit, single core CPU

Computational unit:

4 cores, Intel Core i7

Computational time:

6 hours

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA GTX 660

Computational time:

2 hours

Program version:

64-bit, multicore GPU

Bovanenkovo gas field reservoir computation results

Fine discretization

Computational domain: The number of cells: Simulation period:

14.6×11×19.5 meters

3.5 million

5 years

Fine discretization
Computational unit:

single core, Intel Core i7

Computational time:

80 hours

Program version:

64-bit, single core CPU

Computational unit:

4 cores, Intel Core i7

Computational time:

33 hours

Program version:

64-bit, single core CPU

Computational unit:

NVIDIA GTX 660

Computational time:

14 hours

Program version:

64-bit, multicore GPU


Computer simulation of ground freezing under an oil tank

Computational domain: The number of cells: Simulation period:

90×90×30 meters

7 millions

5 years

Computer simulation of ground freezing under an oil tank
Computational unit:
4 cores, Intel Core i7
Computational time:
11 hours

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA GTX 660

Computational time:

4 hours

Program version:

64-bit, multicore GPU

Computational unit:

NVIDIA TITAN

Computational time:

27 minutes

Program version:

64-bit, multicore GPU

Learn more about computer simulation of ground freezing under an oil tank.

Artificial ground freezing of underground tunnel

Computational domain: The number of cells: Simulation period:

62×20×18.5 meters

3.9 million

2 years

Artificial ground freezing of underground tunnel
Computational unit:

single core, Intel Core i7

Computational time:

15 hours

Program version:

64-bit, single core CPU

+ Filtration module

Computational unit:

4 cores, Intel Core i7

Computational time:

9 hours

Program version:

64-bit, multicore CPU

+ Filtration module

Computational unit:
NVIDIA GTX 660
Computational time:

2 hours

Program version:

64-bit, multicore GPU

+ Filtration module

Learn more about  computer simulation of artificial ground .

Eastern Siberia–Pacific Ocean oil pipeline section

Configuration of mutual arrangement of the pipeline and the ice wedges

ESPO pipeline computation results

Computational domain: The number of cells: Simulation period:

25×25×15 meters

4.8 million

20 years

3D temperature field calculation
Computational unit:

4 cores, Intel Core i5

Computational time:

89 hours

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA GTX 660

Computational time:

34 hours

Program version:

64-bit, multicore GPU

Computational unit:

NVIDIA Tesla K20

Computational time:

10 hours

Program version:

64-bit, multicore GPU

Learn more about thermal analysis of an oil pipeline on permafrost.

Prediction of ground thaw formations around an oil well

Computational domain: The number of cells: Simulation period:

40×60×200 meters

4 million

2 years

Soil thermal field distribution over 5 years around oil well
Computational unit:

1 core, Intel Core i7

Computational time:

18 hours 9 minutes

Program version:

64-bit, single core CPU

Computational unit:

4 cores, Intel Core i7

Computational time:

10 hours 37 minutes

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA TITAN

Computational time:

57 minutes

Program version:

64-bit, multicore GPU

Learn more about prediction of ground thaw formations around an oil well.

Thermal influence of steel pile wall in TV tower (Gaz-Sale area)

The main feature of this section is the steel pile wall (width 8 mm). The significant increase in computational time is due to the relatively small size of the elements (~ 1 mm) and high thermal conductivity (time higher than ground).

Thermal influence of a steel pile wall in a TV tower: simulation results

Computational domain: The number of cells: Simulation period:

2×2×12 meters

0.3 million

2 years

Thermal influence of a steel pile wall in a TV tower
Computational unit:

single core, Intel Core i5

Computational time:

146 hours

Program version:

32-bit, singlecore CPU

Computational unit:

4 cores, Intel Core i5

Computational time:

94 hours

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA GTX 660

Computational time:

55 hours

Program version:

64-bit, multicore GPU

Computational unit:

NVIDIA Tesla K20

Computational time:
18 hours
Program version:

64-bit, multicore GPU


Efficiency assessment of thermal stabilization pipeline supports «Zapolyare – NPS «Purpe»

Efficiency assessment of thermal stabilization pipeline supports

The main features of this computation are 2 thermoprobes inside of each pile (diameter- 426 mm).

Computation results of the thermal stabilization in pipeline piles «Zapolyare – NPS «Purpe»

Computational domain: The number of cells: Simulation period:

6×8×11 meters

1.5 million

2 years

Computation results of the thermal stabilization in pipeline piles
Computational unit:

single core, Intel Core i5

Computational time:

35 hours

Program version:

32-bit, single core CPU

Computational unit:

4 cores, Intel Core i5

Computational time:

25 hours

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA GTX 660

Computational time:

4 hours

Program version:

64-bit, multicore GPU

Computational unit:

NVIDIA Tesla K20

Computational time:

1.4 hours

Program version:

64-bit, multicore GPU


Computation of large sites. Ice wall around Fukushima NPP

Computation of large sites

The main features of this computation are: 1) large freezing region (perimeter 1.3 km); 2) high quality discretization (18 millions of cells); 3) a large number of freezing devices (1073 cooling pipes).

Simulation results of an ice wall around Fukushima NPP

Computational domain: The number of cells: Simulation period:

450×210×30 meters

17.8 million

2 years

Simulation results of an ice wall around Fukushima NPP
Computational unit:

4 cores, Intel Core i7

Computational time:

2 hours 51 minutes

Program version:

64-bit, multicore CPU

Computational unit:

NVIDIA TITAN

Computational time:

7 minutes 26 seconds

Program version:

64-bit, multicore GPU

Computational unit:

NVIDIA Tesla K20

Computational time:

5 minutes 43 seconds

Program version:

64-bit, multicore GPU

Learn more about simulation of ground freezing around the perimeter of the Fukushima Nuclear Power Plant.

General information regarding time of numerical computation

in Frost 3D Universal

Computational speed is influenced by:

1) The size of the computational domain. A large computational domain requires a large number of cells, meaning a significant increase in computational time.

2) The cell sizes in the computational mesh: the computational time is different for 2х2х2 m and 20х20х20 m sites with similar cell quantities; the 2х2х2-m computation site will take longer because of the relatively small cell size.

3) Thermophysical properties of materials (layers). Materials of high thermal conductivity significantly increase computational time.

4) Boundary conditions (speed of environment temperature changes and heat exchange coefficient). The higher speed and amplitude of changes over time resulting in a significant increase in computational time.

5) Cooling devices and working mode. The more cooling devices present and the greater their heat capacity, the longer the time of computation.

The efficiency of computation parallelization (computation speed using multicore computing systems) is influenced by following factors:

1) The more materials and different boundary conditions present in the computational domain, the less the degree of parallelization of computations (the acceleration of the calculation in the transition from single-core to multi-core CPU CPU or GPU).

2) Irregularity of the computational mesh reduces the degree of computation parallelization.

Examples of projects: