Computer simulation reducing environments

For experimental studies, a chemical thermodynamic modelling approach could theoretically reduce unnecessary experimental effort and hence the overall cost of a research project. Once experiments are underway, the computer simulation should also offer valuable assistance in the interpretation of results. Modelling techniques with particular reference to radionuclide speciation have been discussed by Cross and Day (1986) who pointed out that models are only as good as the thermodynamic data upon which they are based. For example, formation constants (a prerequisite for chemical modelling) are invariably generated in idealised laboratory conditions and their use seldom reflects the natural environment... 

Computer simulation of the weathering processes involving reducing environments. 

Nethods of computer simulation. Our purpose is to calculate the evolution of the water composition in reducing environments. The sulfur system is assumed to be the result of a constant yield of sulfur at a given initial oxidation level included between -2 and 0, plus modifications brought about by possible oxidation. 

The dielectric constant is a bulk property of the environment of a system. The dielectric of a vacuum is one, which implies that no polarization of the environment exists. If a solvent, such as water or methanol, is explicitly included in the system, then a dielectric of one is used, because the orientation of the solvent molecules will polarize in the presence of the electric field. If water is the solvent, it is possible to use continuum models and, thus, reduce the amount of computation required. This does add artifacts to the simulation. These artifacts are fairly well characterized, however, and the computation time is dramatically reduced. In some case, two different dielectric constants were used to mimic the different biological environments. For example, in a membrane protein structural modeling, the dielectric constant was set to a value of five for simulating the hydrophobic transmembrane environment and the dielectric constant to 80 for mimicking the hydrophilic loop environment in the two phases of computer simulations (34). 

The methods discussed earlier are applied to the seat-occupant-restraint system of an aircraft. A description of a computer-aided analysis environment, including a multibody model of the occupant and a nonlinear finite element model of the seat, is provided, which can be used to re-construct variety of crash scenarios. These detailed models are useful in studies of the potential human injuries in a crash environment, injuries to the head, the upper spinal column, and the lumbar area, and also structural behavior of the seat. The problem of reducing head injuries to an occupant in case of a head contact with the surroundings (bulkhead, interior walls, or instrument panels), is then considered. The head impact scenario is re-constructed using a nonlinear visco-elastic type contact force model. A measure of the optimal values for the bulkhead compliance and displacement requirements is obtained in order to keep the possibility of a head injury as little as possible. This information could in turn be used in the selection of suitable materials for the bulkhead, instrument panels, or interior walls of an aircraft. The developed analysis tool also allows aircraft designers/engineers to simulate a variety of crash events in order to obtain information on mechanisms of crash protection, designs of seats and safety features, and biodynamic responses of the occupants as related to possible injuries. 

Early biomolecular simulations were carried out either in vacuum or in an environment of fixed dielectric constant in order to reduce the computational expense. In most modern simulations, water is explicitly included in order to describe the system as completely as possible. In some cases, such as very large protein systems, for example myosin," it remains necessary to use one of a range of so-called implicit solvent models such as ACE. ... 

A limited number of sink effect studies have been conducted in full-sized environments. Tichenor et al. [20] showed the effect of sinks on indoor concentrations of total VOCs in a test house from the use of a wood stain. Sparks et al. [50] reported on test house studies of several indoor VOC sources (i.e., p-dichlorobenzene moth cakes, clothes dry-cleaned with perchloroethylene, and aerosol perchloroethylene spot remover) and they were compared with computer model simulations. These test house studies indicated that small-chamber-derived sink parameters and kj) may not be applicable to full-scale, complex environments. The re-emission rate (kj) appeared to be much slower in the test house. This result was also reported by other investigators in a later study [51]. New estimates of and were provided,including estimates of fca (or deposition velocity) based on the diffusivity of the VOC molecule [50]. In a test house study reported by Guo et al. [52], ethylbenzene vapor was injected at a constant rate for 72 h to load the sinks. Re-emissions from the sinks were determined over a 50-day period using a mass-balance approach. When compared with concentrations that would have occurred by simple dilution without sinks, the indoor concentrations of ethylbenzene were almost 300 times higher after 2 days and 7 times higher after 50 days. Studies of building bake-out have also included sink evaluations. Offermann et al. [53] reported that formaldehyde and VOC levels were reduced only temporarily by bake-out. They hypothesized that the sinks were depleted by the bake-out and then returned to equilibrium after the post-bake-out ventilation period. Finally, a test house study of latex paint emissions and sink effects again showed that... 

When the simulated system is bounded by walls or by free surfaces, a substantial fraction of the atoms is located next to the surface, in an environment different from the bulk. Interactions with about half of the neighbors are replaced by interactions with the bounding wall, or are just absent. The effect of the surface is roughly proportional to the fraction of atoms in its vicinity, relative to the total number of atoms in the model. An obvious way to reduce the effect of the surface is to increase the system size, which is however limited by computational resources. This limitation was a lot more severe in the early days, when simulations were run on mainframes capable of handling only about a hundred particles. A very good solution to the problem was found back then and is still in wide use today. 

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