Simulation results

For the simulation calculations, the following process conditions are assumed according to Asai and Muchi  

As discussed above, Equation (8) is valid for process conditions up to the critical point. The decrease in decarburisation rate from the critical point onwards results in a decrease in CO production and, therefore, less stirring is caused by the gas hubbies. Hence, mass transfer in tbe form of metal droplets in the slag decreases. 

At the beginning of the process, the oxidation of Si from the hot spot is limited by the transport of Si to the phase boundary. Hence, decarburisation starts, although 

The aim of the research presented in this paper is the evaluation of a technique for modelling metallurgical processes. In the long term, the process models developed using this technique will be used to improve process design. Special focus is set on modelling non-equilibrium phenomena that are caused e.g. by transport limitations or dissolution processes. The objective is to model the process with a relatively simple model structure and only a few model-specific parameters. 

We run Monte Carlo simulations to examine the performance of the sensor selection algorithm based on the maximization of mutual information for the distributed data fusion architecture. We examine two scenarios first is the sparser one, which consists of 50 sensors which are randomly deployed in the 200 m x 200 m area. The second is a denser scenario in which 100 sensors are deployed in the same area. All data points in the graphs represent the means of ten runs. A target moves in the area according to the process model described in Section 4. We utilize the Neyman-Pearson detector [20, 30] with a = 0.05, L = 100, r) = 2, 2-dB antenna gain, -30-dB sensor transmission power and -6-dB noise power. 

We employ the Neyman-Pearson detector to find the sensing coverage area of the surveillance wireless sensor networks. In order to find the breach path, we apply Dijkstra s shortest path algorithm by us- 

The model and results developed herein give clues that link false alarms to energy efficiency. Enforcing a low false alarm rate to avoid unnecessary response costs implies either a larger data-set (L) and hence a greater battery consumption, or a denser sensor network, which increases the deployment cost. Similar qualitative and/or quantitative inferences about the relationships between various other parameters can also be made. 

Wireless sensor networks are prone to failures. Furthermore, the sensor nodes die due to their limited energy resources. Therefore, the failures of sensor nodes must be modeled and incorporated into the breach path calculations in the future. Simulating the reliability of the network throughout the entire life of the wireless sensor network is also required. Lastly, especially for perimeter surveillance applications, obstacles in the environment play a critical role in terms of sensing and must be incorporated into the field model. 

A mutual information based information measure is adopted to select the most informative subset of sensors to actively participate in the distributed data fusion framework. The duty of the sensors is to accurately localize and track the targets. Simulation results show 36% energy saving for a given tracking quality can be achievable by selecting the sensors to cooperate according to the mutual information metric. 

Abstract This chapter shows the simulation results obtained with the chemical optimization algorithm for the optimization of benchmark functions and robot 

This chapter shows the results obtained for the application problems described in Chap. 4. The results are presented in the same order that the application problems were introduced. 

The circuit was simulated using PSPICE to verify the operation of the pixel circuits. The simulation was based on the following models for the OTFT and OLED. 

We built SPICE models for the critical paths in both implementations. The parametric RC parameters for in-chip layout structure are extracted using a commercial tool1 41. Obviously, full-chip SPICE simulation would be infeasible. Accordingly, we built a partial layout specifically for RC parameter extraction. The partial layout includes the original logic circuits, driver buffer, bus wire belong to a specific critical path as well as 3 neighboring wires on both side and typical layout structures in adjacent metal layers. 

Generally, the inter-chip contact should be modeled with a distributed RC model. However, we do not know the exact structure of inter-chip contact and we instead use a Pi-model to represent the RC effect of inter-chip contacts on the bus wire. We found that, when in the range of 100- 10 k Ohm, the resistance value in the Pi-model does not have a significant effect on the delay. We assume the two capacitors in the p-model have the same value. 

Lumped Capacitance of inter-chip contact (fF) Bus Wire Delay (ns) Critical Path Delay (ns) Clock Frequency (MHz) Improvement to 2D Solution 

From the design experience of 2.5-D PipeRench, we found that substantial performance gain can be achieved because the 2.5-D integration style provides significant flexibility to cut down long wires through the usage of inter-chip contacts. 

The screening due to the counterions should saturate at approximately this density since at lower densities there are no counterions present to screen the monomer interactions. The values obtained with this calculation are more accurate then Odijk s cl and their chain-length dependence is much better. However, these values tend to be high in comparison with the simulation data. This is easily understood by realizing that eq. (3.53) assumes a uniform counterion distribution when in fact the distribution is peaked near the polymer chain. Thus, it is at lower densities where the counterion density near the chain saturates. Furthermore, given that the chain structure is not completely rod-like these results suggest that there is always some number of coimterions near the polymer chain. 

At densities above the saturation density, one ean eompare with the scaling predictions of Odijk and de Gennes et al., In the semidilute regime where Lg C Li, Odijk s sealing theory predicts R where p is the 

Another criticism of Brender s simulations is that she primarily employs the DH potential instead of the Coulomb potential.One of the most important phenomena to directly examine when A varies is counterion condensation, but this can only be done by simulating the counterions. One of the papers does use the Coulomb potential, but does not directly calculate the counterion distributions. It is only inferred that some condensation occurs because of great differences between the DH and Coulomb simulations. These differences are very interesting as they show that even very small salt concentrations have a strong screening effect. This result is consistent with the effect of counterions seen in the simulations of Stevens and Kremer.  

The main point of Brender s series of papers is to show that the chain expands when the temperature decreases. However, this is not surprising since a decreasing temperature corresponds to an increasing A in these simulations. 

Like the experimental data (Fig. 3.16) the simulation data (Fig. 3.20) show two scaling regimes for the osmotic pressure. The simulations were able to reach the dilute noninteraction limit, where II = cksT + 1/N). Thus, at the lowest concentrations there is a deviation from the experimentally observed c / dependence. Also, at these very dilute concentrations the osmotic pressure does not exhibit a chain-length dependence. At the intermediate concentrations, the c / behavior fits the simulation data very well in agreement with experiment, and there appears some chain-length dependence. 

Generally, the two simplest and most common models for the mechanical properties of fiber reinforced composites are the rule of mixtures and the Halpin-Tsai equations [71]. The computational methods for the investigation of CNTs and CNT-filled composites can be categorized into two classes continuum methods and atomistic methods [31]. 

Nevertheless, near the feed point, there is a difference between TMB and all SMB cases due to the fact that the internal flow rates in the TMB are smaller than in the SMB, leading to a small dilution of the feed stream. As a consequence, near the feed inlet, TMB concentrations will be higher than in the SMB operation. The raffinate and extract purities in SMB units with four (95.2 % and 89.5 %), eight (98.7 % and 95.9%) and 12 columns (99.1 % and 96.8%) are increasing towards the one obtained in the equivalent TMB unit (99.3 % and 97.7 %). The optimum degree of subdivision of the SMB unit will depend of the difficulty of the separation and the product purity requirements. Typically, systems for the pharmaceutical industry have six to 16 columns. 

The design problem of a TMB consists on setting the flow rates in each section to obtain the desired separation. Some constraints have to be met to recover the less-adsorbed component A in the raffinate and the more retained component B in the extract. These constraints are expressed in terms of the net fluxes of components in each section (see Fig. 9-1). In section I, both species must move upwards, in sections II and III the light species must move upwards, while the net flux of the more retained component must be downwards, and in section IV the net flux of both species have to be downwards, i.e.. 

For the case of a binary system with linear adsorption isotherms, very simple formulas can be derived to evaluate the better TMB flow rates [19, 20]. For the linear case, the net fluxes constraints are reduced to only four inequalities, which are assumed to be satisfied by the same margin /3 (/3 1) and so  

In the case of complete separation, the concentrations of the component A in the raffinate and of the component B in the extract are, respectively, = C QpJQp = (a - p-)/(a - 1) and Cg = C Qp/Q = Cg ( - p-)/(a - l)p-. Following the equivalence of internal flow rates, it results that the inlet and outlet flow rates are the same for the two operating modes, and 

For nonlinear systems, however, the evaluation of the flow rates is not straightforward. Morbidelli and co-workers developed a complete design of the binary separation by SMB chromatography in the frame of Equilibrium Theory for various adsorption equilibrium isotherms the constant selectivity stoichiometric model [21, 22], the constant selectivity Langmuir adsorption isotherm [23], the variable selectivity modified Langmuir isotherm [24], and the bi-Langmuir isotherm [25]. The region for complete separation was defined in terms of the flow rate ratios in the four sections of the equivalent TMB unit  

While an unquenched single Gaussian distribution cannot be differentiated from a discrete double decay, does quenching lifetime data reveal the existence of the 

The noise-free Stern-Volmer lifetime plots are clearly curved, which indicates a failure of a two discrete site model. However, this is a difficult nonlinear least-squares fitting problem, and the unquenched apparent lifetimes are within a factor of two of each other. Thus, for real data, it is much more difficult to pick up on the nonlinearities and exclude a discrete two-site model. For distributions with smaller R s, of course, fitting becomes too difficult for reliable model testing at least at 104 counts in the peak channel. 

Can an unquenched double Gaussian be differentiated from a discrete double or triple exponential decay We fit a double Gaussian distribution (Tcenter = 5 and 15 R s = 0.2 50% intensity from each) to discrete double and triple exponentials. Even with the double exponential fit, the n sare well below the SPC noise level and the triple was essentially a perfect fit. Therefore, a discrete double or triple exponential decay would be indistinguishable from the true underlying double Gaussian distribution at 104 peak counts.(55) 

Of course, the problem in decay time measurements is improved noticeably if the noise level can be reduced. This is possible, but expensive. SPC instruments with peak counts of 500,000 have been developed. 59  

We turn now to intensity quenching measurements (/o// versus [Q]). As we will show, these measurements are even less sensitive for detecting complex models than are lifetime measurements. On the plus side, however, they show a remarkable ability 

There are two controllers. The proportional reactor level control has a gain of 5. The reactor temperature controller is tuned by running a relay-feedback test. The manipulated variable is the cooling water flowrate in the condenser. With a 50-K temperature transmitter span and the cooling water control valve half open at design conditions, the resulting tuning constants are Kc = 4.23 and = 25 min. 

Thus the autorefrigerated reactor system provides yet another example of the importance of heat transfer area and the increased difficulty of controlling reactors that do not have high conversion rates. Keep in mind that we are considering exothermic reactions that are irreversible. Control problems are much less severe in reactors with endothermic reactions or with reversible reactions because of the inherent self-regulatory nature of the chemistry. 

When feeding the gas mixture at realistic flue gas temperatures (which are generally lower than 250 C) during the capture step, insufficient heat is stored in the packing to evaporate previously condensed water again. A possibility would be to introduce extra heat into the bed in the initial period of the recovery step. However, more practical is to carry out the H2O capture step in a separate smaller bed, which can be cooled down to temperatures much higher than the initial bed temperature of the CO2 capture bed. 

Two types of disturbances are used to test the proposed control strategy. The first is + 20% changes in the fresh feed flowrate. With these changes, the OR flowrate will be adjusted to hold the R/F ratio (OR/feed to heterogeneous azeotropic column). The reflux flow of the preconcentrator/recovery column will also be adjusted to hold the reflux ratio at a constant value. 

With the +20% changes in the flesh feed flowrate, the IPA product flowrate and water product flowrate also increase/decrease correspondingly to their new values. For example, with +20% in the fresh feed flowrate, the IPA product flowrate changes from 832.50 to 998.62 mol/min (also a +20% increase) and the water product flowrate changes from 834.17 to 1000.83 mol/min (also a +20% increase). 

This desirable result is mainly due to the combined pieconcentrator/recovery column dampening the large disturbance from fresh feed, thus making the feed variations to the more sensitive Cl colimin small and easier to handle. The three-column system should also have this desirable feature. However, it requires more process, instrumentation, and control equipment, and the TAC is also higher than the proposed design. 

The feasible designs of three different heterogeneous azeotropic column systems have been illustrated in this chapter with real industrial applications. With the aid of liquid-liquid separation, the products of a column sequence can be located in different distillarion regions. 

Wang C. J., D. S. H. Wong, I. L. Chien, R. F. Shih, W. T Liu, and C. S. Tsai, Critical reflux, parametric sensitivity, and hysteresis in azeotropic distillation of isopropyl alcohol -I- water -I-cyclohexane. Ind. Engng. Chem. Res., 37, 2835-2843 (1998). 

For a small amplitude oscillatory shear in which the ER suspensions are in the linear response region, the rheological behavior was simulated on the basis of the point-dipole approximation [100, 101]. With the increase of 

As mentioned above, experimental protocols are challenging in order to directly probe isolated polyelectrolyte chains, such as their sizes, counterion distributions, and electric potential variations inside and outside the coils. These quantities are sometimes deduced from measurements of other quantities, such as the electrophoretic mobility. The interpretation of data in these indirect measurements also depends heavily on reliable theories. The theoretical 

With the repulsive LJ potential, polymer collapse due to hydrophobic effect is not addressed. The same form of Equation 4.21 is also used to capture the nonelectrostatic excluded volume interactions among the polymer beads and counterions, the difference appearing in the choice of the hardcore distance a. The electrostatic interaction among the charged beads and ions is taken to be the Coulomb energy, 

When the Coulomb interaction parameter is large enough such that F 0.5, attraction between the oppositely charged beads and some counterions begins to contribute significantly. Close examination of the position of counterions near 

As the placement of the reactive products directly determines the yield of recombination, an inaccurate treatment would obviously lead to an incorrect yield. For example, placing the reactive products too close would lead to more recombination 

From the analysis of the recombination yield, it is seen that at the parameter space investigated, the first passage approach accurately describes the spatial distribution of reactive products which results in the correct recombination yield. In the case of the diffusion approach, a greater recombination yield of both R2 and is predicted in all cases, especially for the case when the hydroxyl radicals are close together 

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From the analytical results, it is possible to generate a model of the mixture consisting of an number of constituents that are either pure components or petroleum fractions, according to the schematic in Figure 4.1. The real or simulated results of the atmospheric TBP are an obligatory path between the experimental results and the generation of bases for calculation of thermodynamic and thermophysical properties for different cuts. 

Figure 3 comparison between the simulation results and the measured Bscan (segmented data)... 

As in the experiments, the simulation results also show dynamie sealing at late times. The sealing fimetion (kR(x)) at late times has the large /x behaviour. S (y) known as Porod s law [13, 16]. This result is... 

One of the flexibilities of eomputer simulation is that it is possible to define the themiodynamie eonditions eorresponding to one of many statistieal ensembles, eaeh of whieh may be most suitable for the purpose of the study. A knowledge of the underlying statistieal meehanies is essential in the design of eorreet simulation methods, and in the analysis of simulation results. Flere we deseribe two of the most eommoir statistieal ensembles, but examples of the use of other ensembles will appear later in the ehapter. 

This section presents some of the simulation results obtained by simulating systems of sizes 4000, 6912, 10976, 16384 and 32000 atoms on the IBM-SP/2. The simulations were performed on 4, 8 and 16 processors, respectively. Although, the simulated system size and the number of processors can be scaled easily, this section does not show all results. 

Visuahzation and analysis of structure and dynamics simulation results. Free of charge for academic use. Available for different platforms. Imports TINKER results and accepts various file formats. hitp //www.csc.ji/gopenmol/... 

When the structure is submitted its 3D coordinates arc calculated and the structure is shown at the left-hand side in the form of a 2D structure as well as a rotatable 3D structure (see Figure 10.2-11). The simulation can then be started the input structure is coded, the training data are selected, and the network training is launched. After approximately 30 seconds the simulation result is given as shown in Figure 10,2-11. 

With the Monte Carlo method, the sample is taken to be a cubic lattice consisting of 70 x 70 x 70 sites with intersite distance of 0.6 nm. By applying a periodic boundary condition, an effective sample size up to 8000 sites (equivalent to 4.8-p.m long) can be generated in the field direction (37,39). Carrier transport is simulated by a random walk in the test system under the action of a bias field. The simulation results successfully explain many of the experimental findings, notably the field and temperature dependence of hole mobilities (37,39). 

Step 4 deals with physical and chemical properties of compounds and mixtures. Accurate physical and chemical properties ate essential to achieve accurate simulation results. Most simulators have a method of maintaining tables of these properties as well as computet routines for calculations for the properties by different methods. At times these features of simulators make them suitable or not suitable for a particular problem. The various simulators differ ia the number of compounds ia the data base number of methods for estimating unknown properties petroleum fractions characterized electrolyte properties handled biochemical materials present abiUty to handle polymers and other complex materials and the soflds, metals, and alloys handled. 

I am pleased to acknowledge that the simulation results presented in this chapter were obtained from calculations carried out in collaboration with Kechuan Tu, Mike Klein, and Kent Blasie. The calculations and fitting of the neutron scattering spectra benefited from discussions with Mounir Tarek. Financial support was provided by the School of Physical Sciences at the University of California at Irvine and a grant from the donors of The Petroleum Research Fund, administered by the American Chemical Society (ACS-PRF 33247-G7). 

Preliminary simulation results shall be available six weeks after Seller receives all the agreed to information from the Purchaser. The intent is to have results in time for necessary modifications or design changes to be incorporated into the process design without affecting the train startup. 

Kister shows how the McCabe-Thiele Diagram is an excellent tool for analyzing computer simulation results. It can be used to... 

The numerical solution of the energy balance and momentum balance equations can be combined with flow equations to describe heat transfer and chemical reactions in flow situations. The simulation results can be in various forms numerical, graphical, or pictorial. CFD codes are structured around the numerical algorithms and, to provide easy assess to their solving power, CFD commercial packages incorporate user interfaces to input parameters and observe the results. CFD... 

T he total or global solar radiation has a direct part (beam radiation) and a diffuse part (Fig. 11.31). In the simulation, solar radiation input values must be converted to radiation values for each surface of the building. For nonhorizontal surfaces, the diffuse radiation is composed of (a) the contribution from the diffuse sky and (b) reflections from the ground. The diffuse sky radiation is not uniform. It is composed of three parts, referred to as isotropic, circumsolar, and horizontal brightening. Several diffuse sky models are available. Depending on the model used, discrepancies for the boundary conditions may occur with the same basic set of solar radiation data, thus leading to differences in the simulation results. 

Figure 6.17 Simulation results of Mumtaz etal. (1997) plotted as efficiency against the correlating parameter M (Hounslow etal., 2001)...

FIG. 1 The equation of state for hard spheres, obtained from the BGY equation. The dot-dashed and dotted curves give the pressure and compressiblity results, respectively. The points give the computer simulation results. The quantity p = Nd /V. 

As is seen in Fig. 2(b), the results of Eqs. (33) and (34) are in fair agreement with computer simulation results. Carnahan and Starling (CS) [18] have made the observation that the result... 

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