A study of symbolic processing and computational aspects in helicopter dynamics

Even research models of helicopter dynamics often lead to a large number of equations of motion with periodic coefficients; and Floquet theory is a widely used mathematical tool for dynamic analysis. Presently, three approaches are used in generating the equations of motion. These are (1) general-purpose symbolic processors such as REDUCE and MACSYMA, (2) a special-purpose symbolic processor, DEHIM (Dynamic Equations for Helicopter Interpretive Models), and (3) completely numerical approaches. In this paper, comparative aspects of the first two purely algebraic approaches are studied by applying REDUCE and DEHIM to the same set of problems. These problems range from a linear model with one degree of freedom to a mildly non-linear multi-bladed rotor model with several degrees of freedom. Further, computational issues in applying Floquet theory are also studied, which refer to (1) the equilibrium solution for periodic forced response together with the transition matrix for perturbations about that response and (2) a small number of eigenvalues and eigenvectors of the unsymmetric transition matrix. The study showed the following: (1) compared to REDUCE, DEHIM is far more portable and economical, but it is also less user-friendly, particularly during learning phases; (2) the problems of finding the periodic response and eigenvalues are well conditioned.

A Geostatistical Study pf Alumina-Content in Ores of An Indian Iron-Ore Deposit

Mining and blending operations in the high grade iron ore deposit under study are performed to optimize recovery with minimal alumina content while maintaining required levels of other chemical component and a proper mix of ore types. In the present work the regionalisation of alumina in the ores has been studied independently and its effects on global and local recoverable tonnage as well as on alternatives of mining operations have been evaluated. The global tonnage recovery curves for blocks (20m x 20m x 12m) obtained by simulation closely approximated the curves obtained theoretically using a change of support under the discretised gaussian model. Variations in block size up to 80m x 20m x 12m did not affect the recovery as the horizontal dimensions of the blocks are small in relation to the range of the variogram. A comparison of the local tonnage recovery curves obtained through multiple conditional simulations made with that obtained by the method of uniform conditioning of block grades on an estimate of panel 100m x 100m x 12m panel grade reveals comparable results only in panels which have been well conditioned and possesing an ensemble simulation mean close to the ordinary kriged value for the panel. Study of simple alternative sequence of mining on the conditionally simulated deposit shows that concentration of mining operations simultaneously on a single bench enhances the fluctuation in alumina values of ore mined.

MIMO Precoding With X- and Y- Codes

We consider a slow fading multiple-input multiple-output (MIMO) system with channel state information at both the transmitter and receiver. A well-known precoding scheme is based upon the singular value decomposition (SVD) of the channel matrix, which transforms the MIMO channel into parallel subchannels. Despite having low maximum likelihood decoding (MLD) complexity, this SVD precoding scheme provides a diversity gain which is limited by the diversity gain of the weakest subchannel. We therefore propose X- and Y-Codes, which improve the diversity gain of the SVD precoding scheme but maintain the low MLD complexity, by jointly coding information across a pair of subchannels. In particular, subchannels with high diversity gain are paired with those having low diversity gain. A pair of subchannels is jointly encoded using a 2 2 real matrix, which is fixed a priori and does not change with each channel realization. For X-Codes, these rotation matrices are parameterized by a single angle, while for Y-Codes, these matrices are left triangular matrices. Moreover, we propose X-, Y-Precoders with the same structure as X-, Y-Codes, but with encoding matrices adapted to each channel realization. We observed that X-Codes/Precoders are good for well-conditioned channels, while Y-Codes/Precoders are good for ill-conditioned channels.

The central region of meso-3,4-diphenylhexane-2,5-dione

As with 1,2-diphenylethane (dpe), X-ray crystallographic methods measure the central bond in meso-3,4-diphenylhexane-2,5-done (dphd) as significantly shorter than normal for an sp(3)-sp(3) bond. The same methods measure the benzylic (ethane C-Ph) bonds in dphd as unusually long for sp(3)-sp(2) liaisons. Torsional motions of the phenyl rings about the C-Ph bonds have been proposed as the artifacts behind the result of a 'short' central bond in dpe. While a similar explanation can, presumably, hold for the even 'shorter' central bond in dphd, it cannot account for the 'long' C-Ph bonds. The phenyl groups, departing much from regular hexagonal shape, adopt highly skewed conformations with respect to the plane constituted by the four central atoms. It is thought that-the thermal motions of the phenyl rings, conditioned by the potential wells in which they are ensconced in the unit cell, are largely libratory around their normal axes. In what appears to be a straightforward explanation under the 'rigid-body' concept, it appears that these libratory motions of the phenyl rings, that account, at the same time, for the 'short' central bond, are the artifacts behind the 'long' measurement of the C-Ph bonds. These motions could be superimposed on torsional motions analogous to those proposed in the case of dpe. An inspection of the ORTEP diagram from the 298 K data on dphd clearly suggests these possibilities. Supportive evidence for these qualitative explanations from an analysis of the differences between the mean square displacements of C(1) and C(7)/C(1a) and C(7a) based on the 'rigid-body model' is discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Incremental natural-gradient actor-critic algorithms

We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic rein- forcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated by stochastic gradient descent. Methods based on policy gradients in this way are of special interest because of their com- patibility with function approximation methods, which are needed to handle large or infinite state spaces. The use of temporal difference learning in this way is of interest because in many applications it dramatically reduces the variance of the gradient estimates. The use of the natural gradient is of interest because it can produce better conditioned parameterizations and has been shown to further re- duce variance in some cases. Our results extend prior two-timescale convergence results for actor-critic methods by Konda and Tsitsiklis by using temporal differ- ence learning in the actor and by incorporating natural gradients, and they extend prior empirical studies of natural actor-critic methods by Peters, Vijayakumar and Schaal by providing the first convergence proofs and the first fully incremental algorithms.

Design and developement of a pulsed power system for a Vircator based HPM source

Pulse Forming Line (PFL) based high voltage pulsed power systems are well suited for low impedance High Power Microwave (HPM) sources such as a virtual cathode oscillator (VIRCATOR) operating in nanosecond regimes. The system under development consists of a primary voltage source that charges the capacitor bank of a Marx pulser over a long time duration. The Marx pulser output is then conditioned by a PFL to match the requirement of the HPM diode load. This article describes the design and construction of an oil insulated pulse forming line for a REB (Relativistic Electron Beam) diode used in a VIRCATOR for the generation of high power microwaves. Design of a 250 kV/10 kA/60 ns PFL, including the PSPICE simulation for various load conditions are described.

Evolving Random Geometric Graph Models for Mobile Wireless Networks

We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. We derive properties similar to those above.

Smooth DMS-FEM: A new approach to solving nearly incompressible nonlinear elasto-static problems

The DMS-FEM, which enables functional approximations with C(1) or still higher inter-element continuity within an FEM-based meshing of the domain, has recently been proposed by Sunilkumar and Roy [39,40]. Through numerical explorations on linear elasto-static problems, the method was found to have conspicuously superior convergence characteristics as well as higher numerical stability against locking. These observations motivate the present study, which aims at extending and exploring the DMS-FEM to (geometrically) nonlinear elasto-static problems of interest in solid mechanics and assessing its numerical performance vis-a-vis the FEM. In particular, the DMS-FEM is shown to vastly outperform the FEM (presently implemented through the commercial software ANSYS (R)) as the former requires fewer linearization and load steps to achieve convergence. In addition, in the context of nearly incompressible nonlinear systems prone to volumetric locking and with no special numerical artefacts (e.g. stabilized or mixed weak forms) employed to arrest locking, the DMS-FEM is shown to approach the incompressibility limit much more closely and with significantly fewer iterations than the FEM. The numerical findings are suggestive of the important role that higher order (uniform) continuity of the approximated field variables play in overcoming volumetric locking and the great promise that the method holds for a range of other numerically ill-conditioned problems of interest in computational structural mechanics. (C) 2011 Elsevier Ltd. All rights reserved.

Wrinkled and slack membranes: nonlinear 3D elasticity solutions via smooth DMS-FEM and experiment

The smooth DMS-FEM, recently proposed by the authors, is extended and applied to the geometrically nonlinear and ill-posed problem of a deformed and wrinkled/slack membrane. A key feature of this work is that three-dimensional nonlinear elasticity equations corresponding to linear momentum balance, without any dimensional reduction and the associated approximations, directly serve as the membrane governing equations. Domain discretization is performed with triangular prism elements and the higher order (C1 or more) interelement continuity of the shape functions ensures that the errors arising from possible jumps in the first derivatives of the conventional C0 shape functions do not propagate because the ill-conditioned tangent stiffness matrices are iteratively inverted. The present scheme employs no regularization and exhibits little sensitivity to h-refinement. Although the numerically computed deformed membrane profiles do show some sensitivity to initial imperfections (nonplanarity) in the membrane profile needed to initiate transverse deformations, the overall patterns of the wrinkles and the deformed shapes appear to be less so. Finally, the deformed profiles, computed through the DMS FEM-based weak formulation, are compared with those obtained through an experiment on an ultrathin Kapton membrane, wherein wrinkles form because of the applied boundary displacement conditions. Comparisons with a reported experiment on a rectangular membrane are also provided. These exercises lend credence to the feasibility of the DMS FEM-based numerical route to computing post-wrinkled membrane shapes. Copyright (c) 2012 John Wiley & Sons, Ltd.

Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography

We have developed an efficient fully three-dimensional (3D) reconstruction algorithm for diffuse optical tomography (DOT). The 3D DOT, a severely ill-posed problem, is tackled through a pseudodynamic (PD) approach wherein an ordinary differential equation representing the evolution of the solution on pseudotime is integrated that bypasses an explicit inversion of the associated, ill-conditioned system matrix. One of the most computationally expensive parts of the iterative DOT algorithm, the reevaluation of the Jacobian in each of the iterations, is avoided by using the adjoint-Broyden update formula to provide low rank updates to the Jacobian. In addition, wherever feasible, we have also made the algorithm efficient by integrating along the quadratic path provided by the perturbation equation containing the Hessian. These algorithms are then proven by reconstruction, using simulated and experimental data and verifying the PD results with those from the popular Gauss-Newton scheme. The major findings of this work are as follows: (i) the PD reconstructions are comparatively artifact free, providing superior absorption coefficient maps in terms of quantitative accuracy and contrast recovery; (ii) the scaling of computation time with the dimension of the measurement set is much less steep with the Jacobian update formula in place than without it; and (iii) an increase in the data dimension, even though it renders the reconstruction problem less ill conditioned and thus provides relatively artifact-free reconstructions, does not necessarily provide better contrast property recovery. For the latter, one should also take care to uniformly distribute the measurement points, avoiding regions close to the source so that the relative strength of the derivatives for measurements away from the source does not become insignificant. (c) 2012 Optical Society of America

Linearization and Reconstruction of Non-linear Diffuse Optical Tomographic Image

Diffuse optical tomography (DOT) is one of the ways to probe highly scattering media such as tissue using low-energy near infra-red light (NIR) to reconstruct a map of the optical property distribution. The interaction of the photons in biological tissue is a non-linear process and the phton transport through the tissue is modelled using diffusion theory. The inversion problem is often solved through iterative methods based on nonlinear optimization for the minimization of a data-model misfit function. The solution of the non-linear problem can be improved by modeling and optimizing the cost functional. The cost functional is f(x) = x(T)Ax - b(T)x + c and after minimization, the cost functional reduces to Ax = b. The spatial distribution of optical parameter can be obtained by solving the above equation iteratively for x. As the problem is non-linear, ill-posed and ill-conditioned, there will be an error or correction term for x at each iteration. A linearization strategy is proposed for the solution of the nonlinear ill-posed inverse problem by linear combination of system matrix and error in solution. By propagating the error (e) information (obtained from previous iteration) to the minimization function f(x), we can rewrite the minimization function as f(x; e) = (x + e)(T) A(x + e) - b(T)(x + e) + c. The revised cost functional is f(x; e) = f(x) + e(T)Ae. The self guided spatial weighted prior (e(T)Ae) error (e, error in estimating x) information along the principal nodes facilitates a well resolved dominant solution over the region of interest. The local minimization reduces the spreading of inclusion and removes the side lobes, thereby improving the contrast, localization and resolution of reconstructed image which has not been possible with conventional linear and regularization algorithm.

Proteomic profiling of high glucose primed monocytes identifies cyclophilin A as a potential secretory marker of inflammation in type 2 diabetes

Hyperglycemia is widely recognized to be a potent stimulator of monocyte activity, which is a crucial event in the pathogenesis of atherosclerosis. We analyzed the monocyte proteome for potential markers that would enhance the ability to screen for early inflammatory status in Type 2 diabetes mellitus (T2DM), using proteomic technologies. Monocytic cells (THP-1) were primed with high glucose (HG), their protein profiles were analyzed using 2DE and the downregulated differentially expressed spots were identified using MALDI TOF/MS. We selected five proteins that were secretory in function with the help of bioinformatic programs. A predominantly downregulated protein identified as cyclophilin A (sequence coverage 98%) was further validated by immunoblotting experiments. The cellular mRNA levels of cyclophilin A in various HG-primed cells were studied using qRT-PCR assays and it was observed to decrease in a dose-dependent manner. LC-ESI-MS was used to identify this protein in the conditioned media of HG-primed cells and confirmed by Western blotting as well as ELISA. Cyclophilin A was also detected in the plasma of patients with diabetes. We conclude that cyclophilin A is secreted by monocytes in response to HG. Given the paracrine and autocrine actions of cyclophilin A, the secreted immunophilin could be significant for progression of atherosclerosis in type 2 diabetes. Our study also provides evidence that analysis of monocyte secretome is a viable strategy for identifying candidate plasma markers in diabetes.

In vitro cytotoxicity and in vivo osseointergration properties of compression-molded HDPE-HA-Al2O3 hybrid biocomposites

The aim of this study was to investigate the in vivo biocompatibility in terms of healing of long segmental bone defect in rabbit model as well as in vitro cytotoxicity of eluates of compression-molded High density polyethylene (HDPE)hydroxyapatite (HA)-aluminum oxide (Al2O3) composite-based implant material. Based on the physical property in terms of modulus and strength properties, as reported in our recent publication, HDPE-40 wt % HA and HDPE-20 wt % HA-20 wt % Al2O3 hybrid composites were used for biocompatibility assessment. Osteoblasts cells were cultured in conditioned media, which contains varying amount of composite eluate (0.01, 0.1, and 1.0 wt %). In vitro, the eluates did not exhibit any significant negative impact on proliferation, mineralization or on morphology of human osteoblast cells. In vivo, the histological assessment revealed neobone formation at the bone/implant interface, characterized by the presence of osteoid and osteoblasts. The observation of osteoclastic activity indicates the process of bone remodeling. No inflammation to any noticeable extent was observed at the implantation site. Overall, the combination of in vitro and in vivo results are suggestive of potential biomedical application of compression-molded HDPE- 20 wt % HA- 20 wt % Al2O3 composites to heal long segmental bone defects without causing any toxicity of bone cells.

Moisture Aided Degradation of Oil Impregnated Paper Insulation in Power Transformers

The presence of moisture in oil impregnated paper insulation (OIP) is detrimental to its long time performance. Until recently, it was thought insulation ageing was only a function of temperature and electrical stress. It has now been realized that moisture in all its forms causes rapid degradation of the electrical and mechanical properties with time. In this study, insulation paper samples were conditioned for desired level of moisture and were impregnated with premium quality transformer oil. The oil impregnated samples with 1 to 3 % moisture content were aged at 90 to 130 C. The indices for determining the extent of ageing considered in this work are degree of polymerization (DP), furan, carbon monoxide and carbon dioxide content. These quantities were monitored throughout the ageing experimental run. End-of-life (EOL) criterion used here is the reduction in the value of DP. Phenomenological models for estimating the service life of insulation are proposed and are validated against actual experimental data.

Hardware Accelerator for 3D Method of Moments based Parasitic Extraction

A Field Programmable Gate Array (FPGA) based hardware accelerator for multi-conductor parasitic capacitance extraction, using Method of Moments (MoM), is presented in this paper. Due to the prohibitive cost of solving a dense algebraic system formed by MoM, linear complexity fast solver algorithms have been developed in the past to expedite the matrix-vector product computation in a Krylov sub-space based iterative solver framework. However, as the number of conductors in a system increases leading to a corresponding increase in the number of right-hand-side (RHS) vectors, the computational cost for multiple matrix-vector products present a time bottleneck, especially for ill-conditioned system matrices. In this work, an FPGA based hardware implementation is proposed to parallelize the iterative matrix solution for multiple RHS vectors in a low-rank compression based fast solver scheme. The method is applied to accelerate electrostatic parasitic capacitance extraction of multiple conductors in a Ball Grid Array (BGA) package. Speed-ups up to 13x over equivalent software implementation on an Intel Core i5 processor for dense matrix-vector products and 12x for QR compressed matrix-vector products is achieved using a Virtex-6 XC6VLX240T FPGA on Xilinx's ML605 board.