Water Analysis Simulation Program

WASP/TOXIWASP/WASTOX. The Water Quality Analysis Simulation Program (WASP, 3)is a generalized finite-difference code designed to accept user-specified kinetic models as subroutines. It can be applied to one, two, and three-dimensional descriptions of water bodies, and process models can be structured to include linear and non-linear kinetics. Two versions of WASP designed specifically for synthetic organic chemicals exist at this time. TOXIWASP (54) was developed at the Athens Environmental Research Laboratory of U.S. E.P.A. WASTOX (55) was developed at HydroQual, with participation from the group responsible for WASP. Both codes include process models for hydrolysis, biolysis, oxidations, volatilization, and photolysis. Both treat sorption/desorption as local equilibria. These codes allow the user to specify either constant or time-variable transport and reaction processes. 

Ambrose, R.B., Jr., T.A. Wool, and J.L. Martin. 1993. The Water Quality Analysis Simulation Program, WASPS. Part A Model Documentation. U.S. EPA Environmental Research Laboratory, Athens, GA, September 20. 

Wool, T.A., R.B. Ambrose, J.L. Martin, and E.A. Comer. 2001. Water Quality Analysis Simulation Program (WASP), Version 6.0—Draft Users Manual. U.S. EPA. - Region 4. Atlanta, GA. 

Fig. 9.4. Pa (e) and (e) as a function of the binding energy. The simulations treated 216 water molecules, utilizing the SPC/E water model, and the Lennard-Jones parameters for methane were from [63]. The number density for both the systems is fixed at 0.03333 A 3, and T = 298 K established by velocity rescaling. These calculations used the NAMD program (www.ks.uiuc.edu/namd). After equilibration, the production run comprised 200 ps in the case of the pure water simulation and 500 ps in the case of the methane-water system. Configurations were saved every 0.5 ps for analysis...

Lefkoff, L. J., and Gorelick, S. M. (1986). Design and cost analysis of rapid aquifer restoration systems using flow simulation and quadratic programming. Ground Water, 24(6), 777-790. 

Clementi (1985) described ab initio computational chemistry as a global approach to simulations of complex chemical systems, derived directly from theory without recourse to empirical parametrizations. The intent is to break the computation into steps quantum mechanical computations for the elements of the system, construction of two-body potentials for the interactions between them, statistical mechanical simulations using the above potentials, and, finally, the treatment of higher levels of chemical complexity (e.g., dissipative behavior). This program has been followed for analysis of the hydration of DNA. Early work by Clementi et al. (1977) established intermolecular potentials for the interaction of lysozyme with water, given as maps of the energy of interaction of solvent water with the lysozyme surface. 

A Fischer assay simulates the conversion of oil shale to usable fuels in an above-ground retort. The results of an extensive program of chemical analysis of major and trace elements in spent shale, oil, and water collected from the Fischer assay of a standard oil shale are presented. The concentration of major elements in raw and spent shale can be determined only to 10% in this study. Two criteria show that fluorine and zinc may have been mobilized during the assays. The concentrations of arsenic and selenium in the Fischer assay retort water exceed the maximum permissible concentrations for drinking water. 

B.2, Here, we demonstrate once more how Brownian dynamics relates to diffusive behavior, by simulating spherical particles of radius 1 mm in water at room temperature. At time f = 0, a particle is released at the origin and undergoes 3-D Brownian motion. Write a program that repeats this simulation many times and plots the radial concentration profile of particles as a function of time. It is easier to do the data analysis if you do the simulations concurrently. Then, solve the corresponding time-dependent diffusion equation in spherical coordinates and compare the results to that obtained fi om Brownian dynamics. 

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