Track simulation

FIGURE 2.5 Density-normalized stopping power of water (MeV.cmVg) as a function of energy, according to Pimblott et al (1996) [track simulation, full curve], Kaplan and Sukhonosov (1991) [circles], and Paretzke et al. (1986) [squares and diamonds], (a) Gas phase (b) liquid phase. Reproduced from Pimblott et al. (1996), with permission from Am. Chem. Soc. ... 

Figure 3 Density-normalized stopping power (MeV cm /g) of gaseous and liquid water as a function of electron energy according to track simulation by Pimblott et al. [35]. There is a noticeable phase effect, while a peak is seen at —100 eV in both phases.

The organization of this chapter is as follows. In the following section, Sec. 4.2, the elastic and inelastic interaction cross sections necessary for simulating track structure (geometry) will be discussed. In the next section, ionization and excitation phenomena and some related processes will be taken up. The concept of track structure, from historical idea to modern track simulation methods, will be considered in Sec. 4.4, and Sec. 4.5 deals with nonhomogeneous kinetics and its application to radiation chemistry. The next section (Sec. 4.7) describes some application to high temperature nuclear reactors, followed by special applications in low permittivity systems in Sec. 4.8. This chapter ends with a personal perspective. For reasons of convenience and interconnection, it is recommended that appropriate sections of this chapter be read along with Chapters 1 (Mozumder and Hatano), 2 (Mozumder), 3 (Toburen), 9 (Bass and Sanche), 12 (Buxton), 14 (LaVerne), 17 (Nikjoo), and 23 (Katsumura). 

Elastic collision cross sections are important for track simulation and diiferential cross sections are needed to calculate angular deviation in the track trajectory. Pimblott et al. [9] have given an elaborate analysis for gaseous water and compared the results with the experiments of Katase et al. [12]. In brief, the total elastic cross section... 

This section provides a brief description of theoretical bases of the Monte Carlo track simulation codes we have developed for electrons and ions. Our database of Monte Carlo track simulation codes include electrons (code kurbuc 10 eV to 10 MeV) [174], protons lephist —1 keV to 1 MeV) [175], alpha particles (leahist —1 keV to 8 MeV) [176], all ions... 

Recent particle tracking simulations in soil network models indicate that solute dispersion is more sensitive to the water retention curve than to the particular combination of pore-size distribution and topology that determine its shape (Vogel, 2000). Numerical particle tracking techniques have also been used to simulate solute dispersion in fractured media. Examples for two-dimensional randomly intersecting fracture networks include the models developed by Hull et al. (1987), Smith and Schwartz (1984), Robinson and Gale (1990), and Clemo and Smith (1997). Recently Nordqvist et al. (1996) and Margolin et al. (1998) have extended this approach to three-dimensional fracture networks. 

HI Simulation hid Distance Transform Direct Tracking -- Simulation... 

Another important application of the front-tracking method is to simulate the drop/bubble formation in flow-focusing devices. Production of mono disperse drops ubbles in microchannels is of fundamental importance for the success of the concept of lab-on-a-chip. It has been shown that flow-focusing can be effectively used for this purpose. Filiz and Muradoglu performed front-tracking simulations in order to understand the physics of the breakup mechanism and effects of the flow parameters on the droplet/ bubble size in the flow-focusing devices [11]. 

It must be noted that SAR mixers generally work at small Re. However, some secondary recirculation flows can be generated, as demonstrated by particle tracking simulation [90]. 

Theory has played an essential role in the development of radiation chemistry, especially in its early days when experiment was unable to probe the early events that set the stage for the observable chemical reactions. Three themes that were established early on were scattering processes, electronic structure determinations, and track simulations. Work done in the 1950s through 1970s depended greatly on formal development, both because the basic possibilities needed to be identified and because the available computational tools could not tackle the complexity of the problems. The decades that followed... 

On articulated vehicle modeling and SMC application, many researchers have revealed approaches. More analytically, in Ridley and Corke (2003), Lee and Yoo (2009), Nayl et al. (2012), kinematics model of articulated vehicle and error model between real and reference path are presented, and the path tracking simulation with model predictive control is applied, while in Petrov and Chakyrski (2009) the feedback controller based on Lyapunov approach is designed. The simulations in these literatures are non-real-time. The real-time feature is not verified. Moreover, in Korayem et al. (2012), the spatial cable robot path planning is presented, while in Aslam et al. (2014) the fuzzy SMC is used for path tracking of the four-wheel skid steer vehicle. Both the literatures have designed the controller of SMC. However, the models of the plants are distinct from the articulated vehicle. 

Figure 6. A tracking simulation of a structure and indicators on the quality of prediction of the cracking with and without taking into account the rate of corrosion.

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