A practical approach for cross-functional vehicle body weight optimization

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

Algorithm for mining outliers in categorical data through ranking

The rapid growth in the field of data mining has lead to the development of various methods for outlier detection. Though detection of outliers has been well explored in the context of numerical data, dealing with categorical data is still evolving. In this paper, we propose a two-phase algorithm for detecting outliers in categorical data based on a novel definition of outliers. In the first phase, this algorithm explores a clustering of the given data, followed by the ranking phase for determining the set of most likely outliers. The proposed algorithm is expected to perform better as it can identify different types of outliers, employing two independent ranking schemes based on the attribute value frequencies and the inherent clustering structure in the given data. Unlike some existing methods, the computational complexity of this algorithm is not affected by the number of outliers to be detected. The efficacy of this algorithm is demonstrated through experiments on various public domain categorical data sets.

A note on new indices for the equatorial Indian Ocean oscillation

It is now well known that there is a strong association of the extremes of the Indian summer monsoon rainfall (ISMR) with the El Nio and southern oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO), later being an east-west oscillation in convection anomaly over the equatorial Indian Ocean. So far, the index used for EQUINOO is EQWIN, which is based on the surface zonal wind over the central equatorial Indian Ocean. Since the most important attribute of EQUINOO is the oscillation in convection/precipitation, we believe that the indices based on convection or precipitation would be more appropriate. Continuous and reliable data on outgoing longwave radiation (OLR), and satellite derived precipitation are now available from 1979 onwards. Hence, in this paper, we introduce new indices for EQUINOO, based on the difference in the anomaly of OLR/precipitation between eastern and western parts of the equatorial Indian Ocean. We show that the strong association of extremes of the Indian summer monsoon with ENSO and EQUINOO is also seen when the new indices are used to represent EQUINOO.

Robust Reentry Guidance of a Reusable Launch Vehicle Using Model Predictive Static Programming

A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

The April 2012 Indian Ocean earthquakes: Seismotectonic context and implications for their mechanisms

The 11 April 2012 earthquakes (M-w 8.6 and M-w 8.2) were sourced within the Northern Wharton Basin in the northeastern part of the Indo-Australian diffuse plate boundary. This unusually active oceanic intraplate region has generated many large earthquakes in the past, most of which are believed to have occurred by strike-slip motion, triggered by the NW-SE oriented compressional stresses acting across the Indian and Australian plates. In the aftermath of the 2004 megathrust earthquake along the nearby Sunda Trench, increased seismicity in the Northern Wharton Basin is attributed to the stress transfer from the Sumatra-Andaman plate boundary. Models proposed for the April 2012 earthquakes differ somewhat in details but partly attribute their complex rupture to the reactivation of pre-existing structures. These structures include previously mapped N-S trending fracture zones within the Northern Wharton Basin and E-W lineations across the Ninetyeast Ridge. In this paper, we review the regional tectonics and past seismicity on the Indo-Australian Plate in order to understand the seismotectonic setting of the April 2012 Indian Ocean earthquakes. (c) 2014 Elsevier B.V. All rights reserved.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Switching and Release Time Analysis of Electrostatically Actuated Capacitive RF MEMS Switches

This paper explains the reason behind pull-in time being more than pull-up time of many Radio Frequency Micro-Electro-Mechanical Systems (RF MEMS) switches at actuation voltages comparable to the pull-in voltage. Analytical expressions for pull-in and pull-up time are also presented. Experimental data as well as finite element simulations of electrostatically actuated beams used in RF-MEMS switches show that the pull-in time is generally more than the pull-up time. Pull-in time being more than pull-up time is somewhat counter-intuitive because there is a much larger electrostatic force during pull-in than the restoring mechanical force during the release. We investigated this issue analytically and numerically using a 1D model for various applied voltages and attribute this to energetics, the rate at which the forces change with time, and softening of the overall effective stiffness of the electromechanical system. 3D finite element analysis is also done to support the 1D model-based analyses.

Inferring biochemical routes from biochemical networks

Metabolism is a defining feature of life, and its study is important to understand how a cell works, alterations that lead to disease and for applications in drug discovery. From a systems perspective, metabolism can be represented as a network that captures all the metabolites as nodes and the inter-conversions among pairs of them as edges. Such an abstraction enables the networks to be studied by applying graph theory, particularly, to infer the flow of chemical information in the networks by identifying relevant metabolic pathways. In this study, different weighting schemes are used to illustrate that appropriately weighted networks can capture the quantitative cellular dynamics quite accurately. Thus, the networks now combine the elegance and simplicity of representation of the system and ease of analysing metabolic graphs. Metabolic routes or paths determined by this therefore are likely to be more biologically meaningful. The usefulness of the approach is demonstrated with two examples, first for understanding bacterial stress response and second for studying metabolic alterations that occurs in cancer cells.

Role of spectator ions in influencing the properties of dopant-free ZnO nanocrystals

Towards fundamental studies and potential applications, achieving precise control over the generation of defects in pure ZnO nanocrystals has been always intriguing. Herein, we explored the rote of spectator ions (Co2+ and Ni2+) in influencing the functional properties of ZnO nanocrystals. The crystalline quality, phase purity, and composition of as-prepared samples were thoroughly established by powder X-ray diffraction, electron microscopy (TEM and STEM), and by Raman and X-ray photoelectron spectroscopies (XPS). Despite the presence of Co2+ and Ni2+ ions in the reaction mixture, STEM-energy dispersive spectroscopy (EDS), XPS analysis, and inductively-coupled plasma mass spectrometry (ICP-MS) revealed that the ZnO nanocrystals formed are dopant-free. Even so, their luminescence and magnetic properties were substantially different from those of pure ZnO nanocrystals synthesized using a similar methodology. We attribute the origin of these properties to the defects associated with ZnO nanocrystals generated under different but optimized conditions.

DNA Assisted Self-Assembly of PAMAM Dendrimers

We report DNA assisted self-assembly of polyamidoamine (PAMAM) dendrimers using all atom Molecular Dynamics (MD) simulations and present a molecular level picture of a DNA-linked PAMAM dendrimer nanocluster, which was first experimentally reported by Choi et al. (Nano Lett., 2004, 4, 391-397). We have used single stranded DNA (ssDNA) to direct the self-assembly process. To explore the effect of pH on this mechanism, we have used both the protonated (low pH) and nonprotonated (high pH) dendrimers. In all cases studied here, we observe that the DNA strand on one dendrimer unit drives self-assembly as it binds to the complementary DNA strand present on the other dendrimer unit, leading to the formation of a DNA-linked dendrimer dimeric complex. However, this binding process strongly depends on the charge of the dendrimer and length of the ssDNA. We observe that the complex with a nonprotonated dendrimer can maintain a DNA length dependent inter-dendrimer distance. In contrast, for complexes with a protonated dendrimer, the inter-dendrimer distance is independent of the DNA length. We attribute this observation to the electrostatic complexation of a negatively charged DNA strand with the positively charged protonated dendrimer.

Generalized Model Predictive Static Programming and Angle-Constrained Guidance of Air-to-Ground Missiles

A new generalized model predictive static programming technique is presented for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. Two key features for its high computational efficiency include one-time backward integration of a small-dimensional weighting matrix dynamics, followed bya static optimization formulation that requires only a static Lagrange multiplier to update the control history. It turns out that under Euler integration and rectangular approximation of finite integrals it is equivalent to the existing model predictive static programming technique. In addition to the benchmark double integrator problem, usefulness of the proposed technique is demonstrated by solving a three-dimensional angle-constrained guidance problem for an air-to-ground missile, which demands that the missile must meet constraints on both azimuth and elevation angles at the impact point in addition to achieving near-zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Simulation studies include maneuvering ground targets along with a first-order autopilot lag. Comparison studies with classical augmented proportional navigation guidance and modern general explicit guidance lead to the conclusion that the proposed guidance is superior to both and has a larger capture region as well.

Regulation of Off-Network Pricing in a Nonneutral Network

Representatives of several Internet service providers (ISPs) have expressed their wish to see a substantial change in the pricing policies of the Internet. In particular, they would like to see content providers (CPs) pay for use of the network, given the large amount of resources they use. This would be in clear violation of the ``network neutrality'' principle that had characterized the development of the wireline Internet. Our first goal in this article is to propose and study possible ways of implementing such payments and of regulating their amount. We introduce a model that includes the users' behavior, the utilities of the ISP and of the CPs, and, the monetary flow that involves the content users, the ISP and CP, and, in pUrticular, the CP's revenues from advertisements. We consider various game models and study the resulting equilibria; they are all combinations of a noncooperative game (in which the ISPs and CPs determine how much they will charge the users) with a ``cooperative'' one on how the CP and the ISP share the payments. We include in our model a possible asymmetric weighting parameter (that varies between zero to one). We also study equilibria that arise when one of the CPs colludes with the TSP. We also study two dynamic game models as well as the convergence of prices to the equilibrium values.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

Stress Engineering using Si3N4 for stiction free release of SOI beams

We report on the effect of thin silicon nitride (Si3N4) induced tensile stress on the structural release of 200nm thick SOI beam, in the surface micro-machining process. A thin (20nm / 100nm) LPCVD grown Si3N4 is shown to significantly enhance the yield of released beam in wet release technique. This is especially prominent with increase in beam length, where the beams have higher tendency for stiction. We attribute this yield enhancement to the nitride induced tensile stress, as verified by buckling tendency and resonance frequency data obtained from optical profilometry and laser doppler vibrometry.

Poly(alkylene itaconate)s - an interesting class of polyesters with periodically located exo-chain double bonds susceptible to Michael addition

Itaconic acid is a bio-sourced dicarboxylic acid that carries a double bond; although several reports have dealt with the radical-initiated chain polymerization of dialkyl itaconates, only a few studies have utilized it as a di-acid monomer to prepare polyesters. In this study, we demonstrate that dibutyl itaconate can be melt-condensed with aliphatic diols to generate unsaturated polyesters; importantly, we show that the double bonds remain unaffected during the melt polymerization. A particularly useful attribute of these polyesters is that the exo-chain double bonds are conjugated to the ester carbonyl and, therefore, can serve as excellent Michael acceptors. A variety of organic thiols, such as alkane thiols, MPEG thiol, thioglycerol, derivatized cysteine etc., were shown to quantitatively Michael-add to the exo-chain double bonds and generate interesting functionalized polyesters. Similarly, organic amines, such as N-methyl-benzylamine, diallyl amine and proline, also add across the double bond; thus, these poly(alkylene itaconate)s could serve as potentially bio-benign polyesters that could be quantitatively transformed into a variety of interesting and potentially useful functionalized polymers.