Our company has extensive experience in mathematical simulation of heat and mass transfer in capillary-porous media, and statistical analysis of spatial data. We provide services for the numerical study in the following areas:
The process of computer simulation in the oil and gas industry includes assessment and minimization of temperature and humidity impacts on degradation of protective coatings. It also provides geological and hydrodynamic models of oil and gas field creation, and the simulation of multiphase flow in reservoirs of hydrocarbons deposits.
Introducing moisture into building constructions via the atmosphere and soil moisture decreases a building’s longevity. In order to reduce this, it is necessary to make appropriate computations. Simulation of the movements of air and contaminants within buildings can help with effectively servicing structures and improving microclimatic conditions of the building interior.
Using computer simulations reduces the time required to choose operational parameters for technological processes such as material drying and the development of specialized software for such purposes. Computer simulation helps to optimize the removal of moisture from the material, thus reducing energy costs.
The simulation of physical processes through numerical methods, such as finite element analysis, describes the state of physical systems of a complex structure. For instance, the heating of materials is used in many industrial processes. The use of computer simulation in this field allows us to select heating options that will provide the desired temperature distribution at the lowest possible energy consumption.
The process of contaminants propagation produced by industrial site includes the following steps:
• Creation of a 3D model of hydrogeological object.
• Simulation of the groundwater movement in the saturated and non-saturated environment.
• Simulation of contaminants transfer by means of groundwater.
• Simulation of environmental thermal pollution.
• Analysis of the spatial data distribution.
• Analyses on contaminant profiles using stochastic modeling.