TL;DR: In this paper, it is shown that time averages of properties of the simulated fluid are equal to averages over the isoenthalpic-isobaric, canonical, and isothermal-isboric ensembles.
Abstract: In the molecular dynamics simulation method for fluids, the equations of motion for a collection of particles in a fixed volume are solved numerically. The energy, volume, and number of particles are constant for a particular simulation, and it is assumed that time averages of properties of the simulated fluid are equal to microcanonical ensemble averages of the same properties. In some situations, it is desirable to perform simulations of a fluid for particular values of temperature and/or pressure or under conditions in which the energy and volume of the fluid can fluctuate. This paper proposes and discusses three methods for performing molecular dynamics simulations under conditions of constant temperature and/or pressure, rather than constant energy and volume. For these three methods, it is shown that time averages of properties of the simulated fluid are equal to averages over the isoenthalpic–isobaric, canonical, and isothermal–isobaric ensembles. Each method is a way of describing the dynamics of a certain number of particles in a volume element of a fluid while taking into account the influence of surrounding particles in changing the energy and/or density of the simulated volume element. The influence of the surroundings is taken into account without introducing unwanted surface effects. Examples of situations where these methods may be useful are discussed.
TL;DR: In this article, a geometric conservation law (GCL) is formulated that governs the spatial volume element under an arbitrary mapping and the GCL is solved numerically along with the flow conservation laws using conservative difference operators.
Abstract: Boundary-conforming coordinate transformations are used widely to map a flow region onto a computational space in which a finite-difference solution to the differential flow conservation laws is carried out. This method entails difficulties with maintenance of global conservation and with computation of the local volume element under time-dependent mappings that result from boundary motion. To improve the method, a differential ''geometric conservation law" (GCL) is formulated that governs the spatial volume element under an arbitrary mapping. The GCL is solved numerically along with the flow conservation laws using conservative difference operators. Numerical results are presented for implicit solutions of the unsteady Navier-Stokes equations and for explicit solutions of the steady supersonic flow equations.
TL;DR: In this paper, the authors focus on the scale over which homogenization is being carried out, called the mesoscale, separating the microscale (level of microheterogeneities) from the macroscale (Level of RVE).
TL;DR: This paper presents rendering techniques that use volumes as the basic geometric primitives, and a new method for the visualization of three-dimensional data resulting from numerical simulations and observations of natural phenomena.
Abstract: This paper presents rendering techniques that use volumes as the basic geometric primitives. It defines data structures composed of numerous subvolumes, in excess of 100,000. Over each subvolume, a scalar field describes the variation of some physical quantity. The two rendering methods described herein assume a trilinear variation of this scalar field within each volume element, unlike voxel-based techniques that assume a constant value for each subvolume. The result is a higher order approximation of the structures within the volume. In addition, solid texture mapping, atmospheric attenuation, and transfer functions relating the dynamic range of the scalar field to color and opacity are used to isolate important data features. The result is a new method for the visualization of three-dimensional data resulting from numerical simulations and observations of natural phenomena. This method continuously covers the gap between surface-based and voxel-based techniques.
TL;DR: In this article, an optical probe collects light emanating from a specimen that selectively and preferentially represents a localized volume element within the sample, with illuminationintensity and collection efficacy both dropping off away from the localized volume elements to limit the integrated contribution from outside the element.
Abstract: An optical probe collects light emanating from a specimen that selectively andpreferentially represents a localized volume element within the sample, with illuminationintensity and collection efficacy both dropping off away from the localized volume element to limit the integrated contribution from outside the element. For example, the optics provide high peak illumination and high collection efficiency which both overlap in volume elements of a limited size corresponding to a structure or process of the specimen. The resulting collected signal comprising one or more spectral segments is highly correlated with optical characteristics, such as absorbance, scattering or fluorescence characteristics of material in the small volume elements. A processor may apply a previously-derived vector or matrix transform to the collected responses to produce an output. The collected spectra or other responses have high signal strength and represent small or otherwise inaccessible or masked optical effects present in the sample, so that they are readily correlated to conditions of interest.