Analytical Modeling of Graphene Plasmons

The two-dimensionality of graphene and other layered materials can be exploited to simplify the theoretical description of their plasmonic and polaritonic modes. We present an analytical theory that allows us to simulate these excitations in terms of plasmon wave functions (PWFs). Closed-form expressions are offered for their associated extinction spectra, involving only two real parameters for each plasmon mode and graphene morphology, which we calculate and tabulate once and for all. Classical and quantum-mechanical formulations of this PWF formalism are introduced, in excellent mutual agreement for armchaired islands with $>10\,$nm characteristic size. Examples of application are presented to predict both plasmon-induced transparency in interacting nanoribbons and excellent sensing capabilities through the response to the dielectric environment. We argue that the PWF formalism has general applicability and allows us to analytically describe a wide range of 2D polaritonic behavior, thus facilitating their use for the design of actual devices

RPPM : Rapid Performance Prediction of Multithreaded workloads on multicore processors

Analytical performance modeling is a useful complement to detailed cycle-level simulation to quickly explore the design space in an early design stage. Mechanistic analytical modeling is particularly interesting as it provides deep insight and does not require expensive offline profiling as empirical modeling. Previous work in mechanistic analytical modeling, unfortunately, is limited to single-threaded applications running on single-core processors. This work proposes RPPM, a mechanistic analytical performance model for multi-threaded applications on multicore hardware. RPPM collects microarchitecture-independent characteristics of a multi-threaded workload to predict performance on a previously unseen multicore architecture. The profile needs to be collected only once to predict a range of processor architectures. We evaluate RPPM's accuracy against simulation and report a performance prediction error of 11.2% on average (23% max). We demonstrate RPPM's usefulness for conducting design space exploration experiments as well as for analyzing parallel application performance

Analytical modeling of flash-back phenomena

To understand the flame flash-back phenomena more extensively, an analytical model was formed and a numerical program was written and tested to solve the set of differential equations describing the model. Results show that under a given set of conditions flame propagates in the boundary layer on a flat plate when the free stream is at or below 1.8 m/s

Analytical modeling of battery cycle life

An analytical model related to the physical and chemical processes involved in battery wear and failure is discussed. The model is described using the data from the Crane tests

Mechanical behavior of thermal barrier coatings for gas turbine blades

Plasma-sprayed thermal barrier coatings (TBCs) will enable turbine components to operate at higher temperatures and lower cooling gas flow rates; thereby improving their efficiency. Future developments are limited by precise knowledge of the material properties and failure mechanisms of the coating system. Details of this nature are needed for realistic modeling of the coating system which will, in turn, promote advancements in coating technology. Complementary experiments and analytical modeling which were undertaken in order to define and measure the important failure processes for plasma-sprayed coatings are presented. The experimental portion includes two different tests which were developed to measure coating properties. These are termed tensile adhesion and acoustic emission tests. The analytical modeling section details a finite element method which was used to calculate the stress distribution in the coating system. Some preliminary results are presented

Mesoscopic Modeling of Random Walk and Reactions in Crowded Media

We develop a mesoscopic modeling framework for diffusion in a crowded environment, particularly targeting applications in the modeling of living cells. Through homogenization techniques we effectively coarse-grain a detailed microscopic description into a previously developed internal state diffusive framework. The observables in the mesoscopic model correspond to solutions of macroscopic partial differential equations driven by stochastically varying diffusion fields in space and time. Analytical solutions and numerical experiments illustrate the framework

Analytical modeling of large-angle CMBR anisotropies from textures

We propose an analytic method for predicting the large angle CMBR temperature fluctuations induced by model textures. The model makes use of only a small number of phenomenological parameters which ought to be measured from simple simulations. We derive semi-analytically the $C^l$-spectrum for $2\leq l\leq 30$ together with its associated non-Gaussian cosmic variance error bars. A slightly tilted spectrum with an extra suppression at low $l$ is found, and we investigate the dependence of the tilt on the parameters of the model. We also produce a prediction for the two point correlation function. We find a high level of cosmic confusion between texture scenarios and standard inflationary theories in any of these quantities. However, we discover that a distinctive non-Gaussian signal ought to be expected at low $l$, reflecting the prominent effect of the last texture in these multipoles