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The classical theory of the interaction of light with the electron clouds of atoms and molecules will be discussed in this chapter. The discussion will begin with the interaction of a steady electric field with a collection of point charges, leading to the development of terms describing the electric dipole and quadrupole moments. The classical Lorentz model is then introduced to describe interaction of an oscillating electric field with the electron cloud of an atom, and the concepts of absorption and emission are introduced. The propagation of a light wave through a medium with electric dipoles is then discussed. Finally, the classical theory of radiation from an oscillating dipole is discussed.
By necessity, experimental studies have been the key to advancement in fluid dynamics for centuries. However, with the rapid increase of computational capabilities, numerical approaches have become an acceptable surrogate for experiments. Calculations must resolve the Navier–Stokes equations or approximate methods constructed from them. I will discuss the pros and cons of various types of approaches used, including direct numerical simulations, subgrid models, and implicit grid-discretization-based large-eddy simulation.
On the Experimental Advanced Superconducting Tokamak (EAST), the electron cyclotron wave (ECW) and lower hybrid wave (LHW) are actively used to achieve a high-performance plasma. Turbulence associated with the combined heating experiment is studied numerically based on the gyrokinetic toroidal code (GTC). The linear simulation results show that the unstable mode peaks at $k_{\theta }\rho _{s}\approx 0.65$ and $k_{\theta }\rho _{s}\approx 1.42$. Meanwhile, all of the frequencies of these instabilities are positive, which suggests that the collisionless trapped electron mode (CTEM) is the dominant instability. In the process of nonlinear simulations, a higher transport level is locally achieved during the two waves combined heating due to a formation of a steeper electron temperature gradient. In addition, a low-frequency geodesic acoustic mode (GAM) is observed in the nonlinear stage. Effects of the electron beta, the dimensionless ratio of $T_e/T_i$ and $R/L_{T_e}$ on the growth rate of instability, are also discussed in the paper.
This chapter contains a discussion of the coupling of a magnetic field, through the framework of magnetohydrodynamics (MHD), to the hydrodynamic body forces. This leads to an additional body force, namely the Lorentz force on electrical currents in the fluid. Due to their conductivity, this effect is especially important for ionized plasmas. The intuitive result is that the magnetic field lines follow the flow, and they have an effective tension that can stabilize the RTI. As with the RTI, the RMI can be suppressed by a magnetic field.
Laser absorption spectroscopy is widely used for sensitive and quantitative detection of trace species. In this chapter, the density-matrix approach is used to introduce laser absorption spectroscopy. Spectroscopic quantities that characterize the absorption process are defined, and the relationships among these quantities are discussed. Broadening processes for spectral line shapes are also discussed, and the Doppler, Voigt, and Galatry profiles are introduced. The chapter concludes with a detailed example calculation featuring NO absorption.
The challenge confronting researchers is significant in many ways. One can start by noting that multiple instabilities might exist simultaneously and interact with each other. As an example, oblique shocks generate all three instabilities: RT, RM, and KH. In this chapter, several combined instabilities are discussed: RTI and RMI, RTI and/or RMI with KHI.
The interaction of electromagnetic radiation with single-photon resonances in diatomic molecules is discussed in this chapter. The properties of the electric dipole moment of the molecule are determined primarily by the electron cloud that binds the two nuclei together, and these properties can be understood by considering a reference frame fixed to the molecule. However, the response of the molecule must be averaged over all possible orientations of the molecule in the laboratory frame. Using irreducible spherical tensors greatly simplifies the orientation averaging of the molecular response. The Born–Oppenheimer approximation is invoked to initially account for the effect of the electronic, vibrational, and rotational modes of the molecule. Corrections are applied to account for the coupling and interactions of the different modes, including Herman–Wallis effects. Tables of rotational line strengths are presented for singlet, doublet, and triplet electronic transitions. These tables incorporate the use of Hund’s case (a) basis state wavefunctions for increased insight into radiative interactions for levels intermediate between Hund’s cases (a) and (b).
In this chapter, we will focus on the statistical spectral dynamics which are paramount to understanding the development of the integrated mixing quantities described in Chapter 5. Reynolds flow averaging and the turbulent kinetic energy are introduced. In addition, I will discuss how the energy of the flows is transferred from large scale to small scale modes, as well as the impact of the shockwave and gravity on the isotropy of the flows. The flow spectra allow several important length scales to be defined. Numeric simulations and experimental data will be offered to provide insights on the mixing processes.
Active flow control based on reinforcement learning has received much attention in recent years. Indeed, the requirement for substantial data for trial-and-error in reinforcement learning policies has posed a significant impediment to their practical application, which also serves as a limiting factor in the training of cross-case agents. This study proposes an in-context active flow control policy learning framework grounded in reinforcement learning data. A transformer-based policy improvement operator is set up to model the process of reinforcement learning as a causal sequence and autoregressively give actions with sufficiently long context on new unseen cases. In flow separation problems, this framework demonstrates the capability to successfully learn and apply efficient flow control strategies across various airfoil configurations. Compared with general reinforcement learning, this learning mode without the need for updating the network parameter has even higher efficiency. This study presents an effective novel technique in using a single transformer model to address the flow separation active flow control problem on different airfoils. Additionally, the study provides an innovative demonstration of incorporating reinforcement-learning-based flow control with aerodynamic shape optimization, leading to collective enhancement in performance. This method efficiently lessens the training burden of the new flow control policy during shape optimization, and opens up a promising avenue for interdisciplinary intelligent co-design of future vehicles.
This chapter will provide a detailed presentation of the basic structure of the supernova and its core collapse process to illustrate the roles that RMI, RTI, and KHI play in the different stages of these processes. During the explosions, the shockwave passing through the onion-like supernova core will generate both RMI and RTI. The RTI is the key physical process creating the filament structures observed in the Crab Nebula. MHD RT instabilities will be presented to show how they can further improve the comparison between simulations and observations. Several additional applications where hydrodynamic instability plays an important role will also be examined. Geophysics and solar physics also present effective lenses to view the importance of hydrodynamic instabilities. In the case of solar physics, I will describe how RTI’s impact can be viewed through various phenomena, such as the plumes that rise from low density bubbles as well as eruptions that occur as material returns to the solar surface. Once again, MHD RT instabilities are relevant.
After the RM instability grows from a first shock, it can be hit by a second shock. These reshock scenarios have been found in the key applications of inertial confinement fusion implosions or supernova explosions. In this chapter, I will introduce the efforts to model the growth of the mixing layer induced by the first shock and subsequent reshock and describe how the turbulence kinetic energy and anisotropy might be affected by the reshock events. Data from shock tube experiments and numeric simulations will also be introduced to provide insight into the reshock RM induced flows.