Search

Fluid-structure interaction (FSI) solvers based on vector extrapolation methods are discussed. The FSI solver framework builds on a Dirichlet-Neumann partitioning between general purpose fluid and structural solver. For strong coupling of the two fields vector extrapolation methods are employed to obtain a matrix free nonlinear solver. The emphasis of this presentation is on the embedding of well known vector extrapolation methods in a popular FSI solver framework and, in particular, the relation of these vector extrapolation methods to established fixed-point FSI schemes. [DOI: 10.1115/1.3057468]

Accurate global positioning system (GPS) vector determination is now one of the major applications in modem geodesy. Most of the errors are modeled either to smooth atmospheric effects or to remove biases, such as clock offsets. The network design criteria and the vector processing solutions are based in distances to the reference stations and in the time span of the vectors involved in the sessions. Thus, the final solutions are computed accurately and the residuals show the quality of the computations. What is not usually taken into account in the final vector computation is the bearing of the vector to be processed, as the cutoff angle is considered fixed. This note deals with the variation on the final solution due to different cutoff angles, and still more importantly to the bearing of the vector in highprecision GPS vector determination. If in the future, the International Global Navigation Satellite System Service starts to distribute orbits that are created using the ANTEX file, this elevation-angle dependency should diminish. DOI: 10.1061/(ASCE)0733-9453(2007)133:2(90) CE Database subject headings: Geographic information systems; Vector analysis; Geodetic surveys.

Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of methodology for predicting PPIs and protein interaction networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on a learning algorithm-support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids. More than 16,000 diverse PPI pairs were used to construct the universal model. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods because it is able to predict PPI networks. Different types of PPI networks have been effectively mapped with our method, suggesting that, even with only sequence information, this method could be applied to the exploration of networks for any newly discovered protein with unknown biological relativity. In addition, such supplementary experimental information can enhance the prediction ability of the method. conjoint triad | support vector machine

A novel approach to determine very accurately multiple parameter variations by exploiting the geometric shape of dynamic attractors in state space is presented. The approach is based on the analysis of sensitivity vector fields. These sensitivity vector fields describe changes in the state space attractor of the dynamics and system behavior when parameter variations occur. Distributed throughout the attractor in state space, these fields from a collection of snapshots for known parameter changes. Proper orthogonal decomposition of the parameter space is then employed to distinguish multiple simultaneous parametric variations. The parametric changes are reconstructed by analyzing the deformation of attractors which are characterized by means of the sensitivity vector fields. A set of basis functions in the vector space formed by the sensitivity fields is obtained and is used to successfully identity test cases involving multiple simultaneous parametric variations. The method presented is shown to be robust over a wide range of parameter variations and to perform well in the presence of noise. One of the main applications of the proposed technique is detecting multiple simultaneous damage in vibration-based structural health monitoring. [DOI: 10.1115/1.2346692]

Abstract: This study firstly presents a survey on basic classifiers namely minimum distance classifier (MDC), vector quantization (VQ), principal component analysis (PCA), nearest neighbour (NN) and k-nearest neighbour (kNN). Then [...]

A technique to localize damage in structures that can be treated as linear in the pre- and postdamage states is presented. Central to the approach is the computation of a set of vectors, designated as damage locating vectors (DLVs) that have the property of inducing stress fields whose magnitude is zero in the damaged elements (small in the presence of truncations and approximations). The DLVs are associated with sensor coordinates and are computed systematically as the null space of the change in measured flexibility. The localization approach based on the use of DLVs is not structure type dependent and can be applied to single or multiple element damage scenarios. Knowledge about the system is restricted to that needed for a static analysis in the undamaged state, namely, the undamaged topology and, if the structure is indeterminate, the relative stiffness characteristics. Numerical simulations carded out with realistic levels of noise and modeling error illustrate the robustness of the technique. DOI: 10.1061/(ASCE)0733-9399(2002)128:1(7) CE Database keywords: Damage; Vector analysis; Localization.

The kinematic analysis and the determination of the singularity loci of spatial four-degree-of-freedom parallel manipulators with prismatic or revolute actuators are discussed in this article. A new method for the derivation of the velocity equations and the corresponding Jacobian matrices is presented. The numerical determination of the workspace boundaries is then briefly discussed. Finally, the determination of the singularity loci is performed using the velocity equations and examples are given to illustrate the results obtained. Spatial four-degree-of-freedom parallel manipulators can be used in several robotic applications as well as in flight simulators. The determination of their singularity loci is a very important design issue.

With a blocking index as the response function, the adjoint sensitivity formalism is used to assess the impact of normal modes, adjoint modes, and regional singular vectors on prediction of block onset in a two-layer model. The authors focus on three blocks excited by perturbing the model's state vector at times preselected using the maximal perturbation that defines the direction in phase space associated with the largest possible change in the response function. The sets of normal modes, adjoint modes, and regional singular vectors (using the total energy or the [L.sub.2] norm) are computed on instantaneous basic-state flows for the preselected times and sensitivity results are presented for a time window of 3 days. When ordered by decreasing values of the growth rates of the normal modes, the authors find that some distant normal modes and adjoint modes can produce larger changes in the response function than some of their leading counterparts. In contrast, the sets of regional singular vectors contain easily identifiable subsets of structures associated with relatively large changes in the response function. The largest changes are produced by less than the first 20 regional singular vectors. Some of these individual regional singular vectors capture the onset of the block when used as perturbations to the initial condition in a nonlinear model integration, a result of the importance for ensemble forecasting. It is found that the first five most explosive regional singular vectors of the energy ([L.sub.2]) norm explain over 20% (60%) of the norm contained in the maximal perturbation at initial time. Despite the failure of all individual normal modes to excite the block, as opposed to adjoint modes and regional singular vectors, the authors argue that, paradoxically, the normal mode concept remains a viable tool to explain the dynamics of block onset.

Generalized tangent linear and adjoint equations are derived for a vector equation that contains a parameterized source term with discontinuous on/off switches controlled by a threshold condition. As an extension of Part I, the key results here include a pair of interface matching conditions for coupled tangent linear and adjoint vectors across a switch point. Each matching condition can be expressed in either a forward form or a backward form that connects the vector values on the two sides of the switch point via a forward- or backward-matching matrix. The forward- and backward-matching matrices are mutually invertible. The backward/forward-matching matrix for the adjoint vector is the transpose of the forward/backward matrix for the tangent linear vector. By using the matching condition, the classic tangent linear (or adjoint) solution can be extended through a switch point, so a fundamental set of generalized tangent linear (or adjoint) solutions can be constructed, which leads to an explicit expression of the generalized tangent linear (or adjoint) resolvent - the inverse of the generalized tangent linear (or adjoint) operator. The generalized resolvents provide a complete description of the adjoint properties and yield an integral formulation for the gradient of the costfunction. When the parameterized process produces strong negative feedback, on-off oscillations can be produced numerically in vector forms due to essentially the same mechanism as previously illustrated by one-dimensional examples, and the oscillatory states yield to a marginal state in the limit of vanishing time steps in the numerical integration. Marginal states can impose multiple constraints on the tangent linear vector and thus cause multiple reductions in the effective dimension of the data-forcing vector in the backward integration of the adjoint equation. This extends the previous one-dimensional results.

Vibration normal modes and static correction modes have been previously used to model flexible bodies for dynamic analysis of mechanical systems. The efficiency and accuracy of using these modes to model a system depends on both the flexibility of each body and the applied loads. This paper develops a generalized method for the generation of a set of Ritz vectors to be used in addition to vibration normal modes to form the modal basis to model flexible bodies for dynamic analysis of multibody mechanical systems. The Ritz vectors are generated using spacial distribution of the D'Alembert force and the kinematic constraint forces due to gross-body motion of a flexible body. Combined with vibration normal modes, they form more efficient vector bases for the modeling of flexible bodies comparing to using vibration normal modes alone or using the combination of static correction modes and vibration normal modes. Ritz vectors can be regenerated when the system undergoes significant changes of its configuration and the regeneration procedure is inexpensive. The effectiveness of using the combination of vibration normal modes and the proposed Ritz vectors is demonstrated using a planar slider-crank mechanism.

Byline: Xia Hong, W.S. Harwin Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

The experimental demonstration of a fluidic, multiaxis thrust vectoring (MA TV) scheme is presented for a structurally fixed, afterburning nozzle referred to as the conformal fluidic nozzle (CFN). This concept for jet flow control features symmetric injection around the nozzle throat to provide throttling for jet area control and asymmetric injection to sub-sonically skew the sonic plane for jet vectoring. The conceptual development of the CFN was presented in a companion paper (Miller et al. [1]). In that study, critical design variables were shown to be the flap length and expansion area ratio of the nozzle, and the location, angle, and distribution of injected flow. Measures of merit were vectoring capability, gross thrust coefficient, and discharge coefficient. A demonstration of MATV was conducted on a 20 percent scale CFN test article across a range of nozzle pressure ratios (NPR), injector flow rates, and flow distributions. Both yaw and pitch vector angles of greater than 8 deg were obtained at NPR of 5.5. Yaw vector angles greater than 10 deg were achieved at lower NPR. Values of thrust coefficient for the CFN generally exceeded published measurements of shock-based vectoring methods. In terms of vectoring effectiveness (ratio of vector angle to percent injected flow), fluidic throat skewing was found to be comparable to shock-based vectoring methods. [DOI: 10.1115/1.1361109]