User's guide to a system of finite-element supersonic panel flutter programs

The utilization and operation of a set of six computer programs for the prediction of panel flutter at supersonic speeds by finite element methods are described. The programs run individually to determine the flutter behavior of a flat panel where the finite elements which model the panel each have four degrees of freedom (DOF), a curved panel where the finite elements each have four DOF, and a curved panel where the finite elements each have six DOF. The panels are assumed to be of infinite aspect ratio and are subjected to either simply-supported or clamped boundary conditions. The aerodynamics used by these programs are based on piston theory. Application of the program is illustrated by sample cases where the number of beam finite elements equals four, the in-plane tension parameter is 0.0, the maximum camber to panel length ratio for a curved panel case is 0.05, and the Mach number is 2.0. This memorandum provides a user's guide for these programs, describes the parameters that are used, and contains sample output from each of the programs

A grammar of Nias Selatan

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Temporal-adaptive Euler/Navier-Stokes algorithm for unsteady aerodynamic analysis of airfoils using unstructured dynamic meshes

A temporal adaptive algorithm for the time-integration of the two-dimensional Euler or Navier-Stokes equations is presented. The flow solver involves an upwind flux-split spatial discretization for the convective terms and central differencing for the shear-stress and heat flux terms on an unstructured mesh of triangles. The temporal adaptive algorithm is a time-accurate integration procedure which allows flows with high spatial and temporal gradients to be computed efficiently by advancing each grid cell near its maximum allowable time step. Results indicate that an appreciable computational savings can be achieved for both inviscid and viscous unsteady airfoil problems using unstructured meshes without degrading spatial or temporal accuracy

Unstructured-grid methods development for unsteady aerodynamic and aeroelastic analyses

The current status of unstructured grid methods development in the Unsteady Aerodynamics Branch at NASA-Langley is described. These methods are being developed for unsteady aerodynamic and aeroelastic analyses. The flow solvers are highlighted which were developed for the solution of the unsteady Euler equations and selected results are given which show various features of the capability. The results demonstrate 2-D and 3-D applications for both steady and unsteady flows. Comparisons are also made with solutions obtained using a structured grid code and with experimental data to determine the accuracy of the unstructured grid methodology. These comparisons show good agreement which thus verifies the accuracy

Robustness Analysis of Real-Time Scheduling Against Differential Power Analysis Attacks

Item does not contain fulltextISVLSI 2014 IEEE Computer Society Annual Symposium on VLSI, 9-11 July 2014, Tampa, Florid

SoK: Design Tools for Side-Channel-Aware Implementations

Side-channel attacks that leak sensitive information through a computing device's interaction with its physical environment have proven to be a severe threat to devices' security, particularly when adversaries have unfettered physical access to the device. Traditional approaches for leakage detection measure the physical properties of the device. Hence, they cannot be used during the design process and fail to provide root cause analysis. An alternative approach that is gaining traction is to automate leakage detection by modeling the device. The demand to understand the scope, benefits, and limitations of the proposed tools intensifies with the increase in the number of proposals. In this SoK, we classify approaches to automated leakage detection based on the model's source of truth. We classify the existing tools on two main parameters: whether the model includes measurements from a concrete device and the abstraction level of the device specification used for constructing the model. We survey the proposed tools to determine the current knowledge level across the domain and identify open problems. In particular, we highlight the absence of evaluation methodologies and metrics that would compare proposals' effectiveness from across the domain. We believe that our results help practitioners who want to use automated leakage detection and researchers interested in advancing the knowledge and improving automated leakage detection

Reynolds number influences in aeronautics

Reynolds number, a measure of the ratio of inertia to viscous forces, is a fundamental similarity parameter for fluid flows and therefore, would be expected to have a major influence in aerodynamics and aeronautics. Reynolds number influences are generally large, but monatomic, for attached laminar (continuum) flow; however, laminar flows are easily separated, inducing even stronger, non-monatomic, Reynolds number sensitivities. Probably the strongest Reynolds number influences occur in connection with transitional flow behavior. Transition can take place over a tremendous Reynolds number range, from the order of 20 x 10(exp 3) for 2-D free shear layers up to the order of 100 x 10(exp 6) for hypersonic boundary layers. This variability in transition behavior is especially important for complex configurations where various vehicle and flow field elements can undergo transition at various Reynolds numbers, causing often surprising changes in aerodynamics characteristics over wide ranges in Reynolds number. This is further compounded by the vast parameterization associated with transition, in that any parameter which influences mean viscous flow development (e.g., pressure gradient, flow curvature, wall temperature, Mach number, sweep, roughness, flow chemistry, shock interactions, etc.), and incident disturbance fields (acoustics, vorticity, particulates, temperature spottiness, even electro static discharges) can alter transition locations to first order. The usual method of dealing with the transition problem is to trip the flow in the generally lower Reynolds number wind tunnel to simulate the flight turbulent behavior. However, this is not wholly satisfactory as it results in incorrectly scaled viscous region thicknesses and cannot be utilized at all for applications such as turbine blades and helicopter rotors, nacelles, leading edge and nose regions, and High Altitude Long Endurance and hypersonic airbreathers where the transitional flow is an innately critical portion of the problem

LDA-Based Clustering as a Side-Channel Distinguisher

Side-channel attacks put the security of the implementations of cryptographic algorithms under threat. Secret information can be recovered by analyzing the physical measurements acquired during the computations and using key recovery distinguishing functions to guess the best candidate. Several generic and model based distinguishers have been proposed in the literature. In this work we describe two contributions that lead to better performance of side-channel attacks in challenging scenarios. First, we describe how to transform the physical leakage traces into a new space where the noise reduction is near-optimal. Second, we propose a new generic distinguisher that is based upon minimal assumptions. It approaches a key distinguishing task as a problem of classification and ranks the key candidates according to the separation among the leakage traces. We also provide experiments and compare their results to those of the Correlation Power Analysis (CPA). Our results show that the proposed method can indeed reach better success rates even in the presence of significant amount of noise

Efficient Entropy Estimation for Mutual Information Analysis Using B-Splines

International audienceThe Correlation Power Analysis (CPA) is probably the most used side-channel attack because it seems to fit the power model of most standard CMOS devices and is very efficiently computed. However, the Pearson correlation coefficient used in the CPA measures only linear statistical dependences where the Mutual Information (MI) takes into account both linear and nonlinear dependences. Even if there can be simultaneously large correlation coefficients quantified by the correlation coefficient and weak dependences quantified by the MI, we can expect to get a more profound understanding about interactions from an MI Analysis (MIA). We study methods that improve the non-parametric Probability Density Functions (PDF) in the estimation of the entropies and, in particular, the use of B-spline basis functions as pdf estimators. Our results indicate an improvement of two fold in the number of required samples compared to a classic MI estimation. The B-spline smoothing technique can also be applied to the rencently introduced Cramér-von-Mises test

Energy Optimization of Unrolled Block Ciphers using Combinational Checkpointing

Energy consumption of block ciphers is critical in resource constrained devices. Unrolling has been explored in literature as a technique to increase efficiency by eliminating energy spent in loop control elements such as registers and multiplexers. However these savings are minimal and are offset by the increase in glitching power that comes with unrolling. We propose an efficient latch-based glitch filter for unrolled designs that reduces energy per encryption by an order of magnitude over a straightforward implementation, and by 28-32% over the best existing glitch filtering schemes. We explore the optimal number of glitch filters that should be used in order to minimize total energy, and provide estimates of the area cost. Partially unrolled designs also benefit from using our scheme with energies competitive to fully serialized implementations. We demonstrate our approach on the SIMON-128 and AES-256 block ciphers