Energy Conversion in Shape Memory Alloy Heat Engine Part I: Theory

Shape Memory Alloy (SMA) can be easily deformed to a new shape by applying a small external load at low temperature, and then recovers its original configuration upon heating. This unique shape memory phenomenon has inspired many novel designs. SMA based heat engine is one among them. SMA heat engine is an environment-friendly alternative to extract mechanical energy from low-grade energies, for instance, warm wastewater, geothermal energy, solar thermal energy, etc. The aim of this paper is to present an applicable theoretical model for simulation of SMA-based heat engines. First, a micro-mechanical constitutive model is derived for SMAs. The volume fractions of austenite and martensite variants are chosen as internal variables to describe the evolution of microstructure in SMA upon phase transition. Subsequently, the energy equation is derived based on the first thermodynamic law and the previous SMA model. From Fourier’s law of heat conduction and Newton’s law of cooling, both differential and integral forms of energy conversion equation are obtained.

Semi-analytic slope delay model for CMOS switch-level timing verification

A novel slope delay model for CMOS switch-level timing verification is presented. It differs from conventional methods in being semianalytic in character. The model assumes that all input waveforms are trapezoidal in overall shape, but that they vary in their slope. This simplification is quite reasonable and does not seriously affect precision, but it facilitates rapid solution. The model divides the stages in a switch-level circuit into two types. One corresponds to the logic gates, and the other corresponds to logic gates with pass transistors connected to their outputs. Semianalytic modeling for both cases is discussed.

Turbulent Modeling of ABL over Wavy Water Surface

A new model accounting for both turbulence and sea state effects has been proposed in this paper to describe momentum, heat and moisture exchanges through air-sea interface. While long wave components mainly change air flow profile, short wave components

Physical modeling of untrenched submarine pipeline instability

Wave-induced instability of untrenched pipeline on sandy seabed is a `wave-soil-pipeline' coupling dynamic problem. To explore the mechanism of the pipeline instability, the hydrodynamic loading with U-shaped oscillatory flow tunnel is adopted, which is quite different from the previous experiment system. Based on dimensional analysis, the critical conditions for pipeline instability are investigated by altering pipeline submerged weight, diameter, soil parameters, etc. Based on the experimental results, different linear relationships between Froude number (Fr) and non-dimensional pipeline weight (G) are obtained for two constraint conditions. Moreover, the effects of loading history on the pipeline stability are also studied. Unlike previous experiments, sand scouring during the process of pipe's losing stability is detected in the present experiments. In addition, the experiment results are compared with the previous experiments, based on Wake II model for the calculation of wave-induced forces upon pipeline. It shows that the results of two kinds of experiments are comparable, but the present experiments provide better physical insight of the wave-soil-pipeline coupling effects.

Magnetic switching and anisotropy in nanomagnets: the influence of size and shape

Arrays of nanomagnets were fabricated out of Ni80Fe14Mo5 in the lateral size range 500-30nm and the thickness range 3-20nm. Elliptical, triangular, square, pentagonal and circular geometries were all considered. The magnetic properties of these nanomagnets were probed rapidly and non-invasively using a high sensitivity magneto-optical method.

Modeling Ammonothermal Growth of GaN Single Crystals: The Role of Transport

Single crystal gallium nitride (GaN) is an important technological material used primarily for the manufacture of blue light lasers. An important area of contemporary research is developing a viable growth technique. The ammonothermal technique is an important candidate among many others with promise of commercially viable growth rates and material quality. The GaN growth rates are a complicated function of dissolution kinetics, transport by thermal convection and crystallization kinetics. A complete modeling effort for the growth would involve modeling each of these phenomena and also the coupling between these. As a first step, the crystallization and dissolution kinetics were idealized and the growth rates as determined purely by transport were investigated. The growth rates thus obtained were termed ‘transport determined growth rates’ and in principle are the maximum growth rates that can be obtained for a given configuration of the system. Using this concept, a parametric study was conducted primarily on the geometric and the thermal boundary conditions of the system to optimize the ‘transport determined growth rate’ and determine conditions when transport might be a bottleneck.

Modeling on Runoff Concentration Caused by Rainfall on Hillslopes and Application in Maoping Slope

Based on the fact that the concentration flowlines of overland flow depend on the surface landform of hillslope, a kinematic wave model was developed for simulating runoff generation and flow concentration caused by rainfall on hillslopes. The model-simulated results agree well with experimental observations. Applying the model to the practical case of Maoping slope, we obtained the characteristics of runoff generation and infiltration on the slope. Especially, the simulated results adequately reflected the confluent pattern of surface runoff, which offers a scientific foundation for designing the drainage engineering on the Maoping slope.

Probabilistic Modeling of Rosette Formation

英文摘要: Rosetting, or forming a cell aggregate between a single target nucleated cell and a number of red blood cells (RBCs), is a simple assay for cell adhesion-mediated by specific receptor-ligand interaction. For example, rosette formation between sheep RBC and human lymphocytes has been used to differentiate T cells from B cells. Rosetting assay is commonly used to determine the interaction of Fc gamma-receptors (Fc gamma R) expressed on inflammatory cells and IgG-coated on RBCs. Despite its wide use in measuring cell adhesion, the biophysical parameters of rosette formation have not been well characterized. Here we developed a probabilistic model to describe the distribution of rosette sizes, which is Poissonian. The average rosette size is predicted to be proportional to the apparent two-dimensional binding affinity of the interacting receptor-ligand pair and their site densities. The model has been supported by experiments of rosettes mediated by four molecular interactions: Fc gamma RIII interacting with IgG, T cell receptor and coreceptor CD8 interacting with antigen peptide presented by major histocompatibility molecule, P-selectin interacting with P-selectin glycoprotein ligand 1 (PSGL-1), and L-selectin interacting with PSGL-1. The latter two are structurally similar and are different from the former two. Fitting the model to data enabled us to evaluate the apparent effective two-dimensional binding affinity of the interacting molecular pairs: 7.19x10(-5) mu m(4) for Fc gamma RIII-IgG interaction, 4.66x10(-3) mu m(4) for P-selectin-PSGL-1 interaction, and 0.94x10(-3) mu m(4) for L-selectin-PSGL-1 interaction. These results elucidate the biophysical mechanism of rosette formation and enable it to become a semiquantitative assay that relates the rosette size to the effective affinity for receptor-ligand binding.

Progress In Modeling Of Fluid Flows In Crystal Growth Processes

Modeling of fluid flows in crystal growth processes has become an important research area in theoretical and applied mechanics. Most crystal growth processes involve fluid flows, such as flows in the melt, solution or vapor. Theoretical modeling has played an important role in developing technologies used for growing semiconductor crystals for high performance electronic and optoelectronic devices. The application of devices requires large diameter crystals with a high degree of crystallographic perfection, low defect density and uniform dopant distribution. In this article, the flow models developed in modeling of the crystal growth processes such as Czochralski, ammonothermal and physical vapor transport methods are reviewed. In the Czochralski growth modeling, the flow models for thermocapillary flow, turbulent flow and MHD flow have been developed. In the ammonothermal growth modeling, the buoyancy and porous media flow models have been developed based on a single-domain and continuum approach for the composite fluid-porous layer systems. In the physical vapor transport growth modeling, the Stefan flow model has been proposed based on the flow-kinetics theory for the vapor growth. In addition, perspectives for future studies on crystal growth modeling are proposed. (c) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

Theory Of Phase Transformation And Reorientation In Single Crystalline Shape Memory Alloys

A constitutive model, based on an (n + 1)-phase mixture of the Mori-Tanaka average theory, has been developed for stress-induced martensitic transformation and reorientation in single crystalline shape memory alloys. Volume fractions of different martensite lattice correspondence variants are chosen as internal variables to describe microstructural evolution. Macroscopic Gibbs free energy for the phase transformation is derived with thermodynamics principles and the ensemble average method of micro-mechanics. The critical condition and the evolution equation are proposed for both the phase transition and reorientation. This model can also simulate interior hysteresis loops during loading/unloading by switching the critical driving forces when an opposite transition takes place.

Effects Of Subgrid-Scale Modeling On Lagrangian Statistics In Large-Eddy Simulation

The application of large-eddy simulation (LES) to turbulent transport processes requires accurate prediction of the Lagrangian statistics of flow fields. However, in most existing SGS models, no explicit consideration is given to Lagrangian statistics. In this paper, we focus on the effects of SGS modeling on Lagrangian statistics in LES ranging from statistics determining single-particle dispersion to those of pair dispersion and multiparticle dispersion. Lagrangian statistics in homogeneous isotropic turbulence are extracted from direct numerical simulation (DNS) and the LES with a spectral eddy-viscosity model. For the case of longtime single-particle dispersion, it is shown that, compared to DNS, LES overpredicts the time scale of the Lagrangian velocity correlation but underpredicts the Lagrangian velocity fluctuation. These two effects tend to cancel one another leading to an accurate prediction of the longtime turbulent dispersion coefficient. Unlike the single-particle dispersion, LES tends to underestimate significantly the rate of relative dispersion of particle pairs and multiple-particles, when initial separation distances are less than the minimum resolved scale due to the lack of subgrid fluctuations. The overprediction of LES on the time scale of the Lagrangian velocity correlation is further confirmed by a theoretical analysis using a turbulence closure theory.